JP2003232982A - Ranging apparatus - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To decrease computational complexity by performing a correlation value computation at each shift amount while shifting a pair of window ranges at every other prescribed intervals with the window range for one pixel component as a minimum interval and on the other hand, to prevent the degradation in the accuracy of ranging by performing a correlation value computation at each of the shift amounts of the minimum interval by narrowing the window ranges down to the prescribed ranges before and behind the reference which is the shift amount of the window ranges when the maximum correlation value among the correlation values determined in such a manner is obtained. <P>SOLUTION: A pair of the window ranges within the range of an adopted sensor are shifted at every other three (three pixels) and the correlation value computation is performed by each of every other three shift amounts. The correlation value computation (ordinary computation) is performed by each one shift amount within the prescribed range (recomputation range) before and behind the reference which is the shift amount of the window ranges when the maximum correlation value among the correlation values obtained by the correlation value computing means is obtained. <P>COPYRIGHT: (C)2003,JPO

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a distance measuring device, and more particularly to, for example, a camera distance measuring device using a passive AF sensor.

[0002]

2. Description of the Related Art A distance measuring device for a camera using a passive AF sensor, for example, images a distance measuring object by a pair of left and right line sensors and acquires left and right sensor images (AF data). A obtained from this pair of left and right line sensors
Of the F data, a pair of window ranges for obtaining a pair of AF data used for the correlation value calculation are determined, and the pair of window ranges are set in opposite directions in a pair of predetermined sensor regions (adopted sensors). While shifting, a pair of AF data used for the correlation value calculation is sequentially acquired. Alternatively, while fixing one window range and shifting the other window range, a pair of AF data used for the correlation value calculation is sequentially acquired. The correlation between the pair of AF data thus obtained is obtained, and the distance measurement object is determined based on the shift amount of the window range when the maximum correlation is obtained (when the left and right sensor images in the pair of adopted sensors match). The distance is calculated (Japanese Patent Laid-Open No. 8-285580,
Japanese Patent Laid-Open No. 11-23957 and Japanese Patent No. 3099603.
No.).

[0003]

[Problems to be Solved by the Invention]
Since the correlation value at each shift amount is calculated while shifting the window range pixel by pixel, and the shift amount of the window range when the maximum correlation is obtained from the calculated correlation value is detected, the pixels of the AF sensor are When the number is large, the number of times the correlation value is calculated increases, and there is a problem that the distance measurement time becomes long.

The present invention has been made in view of the above circumstances, and an object thereof is to provide a distance measuring device capable of shortening the distance measuring time without lowering the distance measuring accuracy.

[0005]

In order to achieve the above object, the invention according to claim 1 forms light from an object to be measured on a pair of line sensors composed of a plurality of light receiving elements, and each light receiving element is formed. AF data generating means for generating a pair of AF data for calculating a correlation value based on the signal obtained from (here, the AF data is obtained by integrating the signals output from the respective light receiving elements of the line sensor). The sensor data is used as it is, and the sensor data is subjected to contrast extraction processing and the like), and a pair of A from a pair of adopted sensor ranges used for distance measurement of the pair of line sensors.
AF data acquisition means for acquiring F data, and a pair of window ranges for acquiring a pair of AF data used for correlation value calculation within the pair of adopted sensor ranges are determined, and the pair of window ranges are defined as the window ranges. First correlation value calculation means for sequentially calculating correlation values while shifting in order to obtain the highest correlation within a pair of adopted sensor ranges, wherein the pair of windows when the pair of window ranges are shifted by one pixel Correlation value calculation using AF data in the pair of window ranges for each shift amount of the pair of window ranges when the pair of window ranges are shifted at predetermined intervals with the range shift amount interval as the minimum interval. First correlation value computing means for
Within the predetermined range before and after the shift amount of the window range when the highest correlation value among the correlation values obtained by the first correlation value calculating means is obtained, the pair of window ranges are Second correlation value calculation means for sequentially calculating correlation values while shifting at the minimum interval, and the window range when the highest correlation value among the correlation values obtained by the second correlation value calculation means is obtained. Distance measuring object distance calculating means for calculating the distance of the distance measuring object based on the shift amount.

That is, since the first correlation calculating means calculates the correlation value for each shift amount when the pair of window ranges are shifted at predetermined intervals, the calculation amount of the correlation value calculation can be reduced. Yes, on the other hand, the second correlation calculation means
Correlation is performed for each shift amount of the minimum interval within a predetermined range before and after the shift amount of the window range when the highest correlation value of the correlation values obtained by the first correlation value calculating means is obtained. Since the value is calculated, the ranging accuracy does not decrease.

The invention described in claim 2 is the same as claim 1
In the invention described in (1), the first correlation value calculation means is
A correlation value is calculated for each shift amount of the minimum interval within a predetermined range near the minimum and maximum shift amounts of the pair of window ranges.

That is, when the shift amount of the window range when the maximum correlation value is obtained is in the vicinity of the minimum value or the maximum value of the shift amount, the maximum value is obtained from the correlation values calculated only by the shift amount at the predetermined intervals. The shift amount when the correlation value is obtained may not be detected in some cases. According to the second aspect of the present invention, the shift amount when the highest correlation value is obtained can be appropriately detected even in such a case.

Further, as described in claim 3, the first correlation value calculating means has the highest correlation when there are a plurality of extreme values showing a high correlation due to the correlation value calculation within the adopted sensor range. The extreme value is set as the temporary first extreme value, and the extreme value having the next highest correlation is obtained as the temporary second extreme value, and the second correlation value calculation means calculates the temporary first extreme value and the temporary second extreme value. If the difference is within a predetermined reference value, the temporary second extreme value is obtained within a predetermined range before and after the shift amount of the window range when the temporary first extreme value is obtained is used as a reference. It is characterized in that the correlation value is calculated within a predetermined range before and after the shift amount of the window range at the time of reference.

That is, when the difference between the temporary first extreme value and the temporary second extreme value is within a predetermined reference value, it is unknown which extreme value is close to the maximum correlation value.

According to a fourth aspect of the present invention, the second correlation value calculating means has the first correlation value calculating means of the shift amount within the range in which the correlation value calculation is performed by the second correlation value calculating means. For the shift amount for which the correlation value has already been obtained by the above, the correlation value obtained by the first correlation value calculating means is not calculated and the correlation value obtained by the second correlation value calculating means is calculated. It is characterized by setting it as a value. That is, it is possible to prevent the correlation values having the same shift amount from being redundantly calculated and to shorten the distance measurement time.

As described in claim 5, the shift amount of the window range when the highest correlation value is obtained by the first correlation value computing means and the highest correlation value by the second correlation value computing means It is characterized in that it has a means for obtaining a difference from the shift amount of the window range when it is obtained, and a determining means for making distance measurement impossible when the obtained difference is equal to or more than a predetermined shift amount.

When the difference between the shift amounts when the maximum correlation value obtained by the first and second correlation value calculating means is obtained is a predetermined shift amount or more, the reliability of the shift amounts obtained respectively This is because the distance is low and the distance may be erroneously measured.

As described in claim 6, the shift amount of the window range when the maximum correlation value is obtained by the first correlation value calculating means and the maximum correlation value by the second correlation value calculating means are The second correlation value calculating means has means for obtaining a difference from the shift amount of the window range when it is obtained, and the second correlation value computing means exceeds the predetermined range by an additional correlation amount by the shift amount of the obtained difference. It is characterized by performing value calculation.

According to a seventh aspect of the present invention, the distance measuring object distance calculating means has the highest correlation value among the correlation values obtained by the second correlation value calculating means and the predetermined range before and after the highest correlation value. It is characterized in that the shift amount for obtaining the true highest correlation value is obtained by the interpolating value calculation based on the correlation value and the distance measurement target distance is calculated based on the shift amount.

The highest correlation value obtained by the second correlation value calculating means is the highest correlation value among the discrete correlation values, but according to the seventh aspect, the true highest correlation value that is not discrete is calculated. The shift amount can be calculated. According to the sixth aspect, when the true maximum correlation value is calculated by the interpolation value calculation, the correlation value used for the interpolation value calculation is not insufficient.

As described in claim 8, contrast determination means for determining whether the contrast of the pair of AF data acquired by the AF data acquisition means is higher or lower than a predetermined reference, and the pair of adopted sensor ranges. In which a pair of window ranges for obtaining a pair of AF data used for correlation value calculation are determined, and the pair of window ranges are sequentially shifted while obtaining the highest correlation within the pair of adopted sensor ranges. Third correlation value calculating means for calculating a correlation value, the third correlation value calculating means for calculating a correlation value using AF data at predetermined intervals of the AF data in the pair of window ranges; A predetermined value before and after the reference is based on the shift amount of the window range when the highest correlation value among the correlation values obtained by the third correlation value calculation means is obtained. It is a fourth correlation value calculating means for sequentially calculating a correlation value while shifting the pair of window ranges within the range, and a fourth correlation value calculating means for calculating a correlation value using all the AF data within the pair of window ranges. When the correlation value calculation means and the contrast determination means determine that the contrast of the pair of AF data is high, the correlation value calculation by the third correlation value calculation means and the fourth correlation value calculation means is selected. When the contrast determination means determines that the contrast of the pair of AF data is low, the correlation value calculation is selectively performed by the first correlation value calculation means and the second correlation value calculation means. A distance calculation object distance calculation means, wherein the distance measurement object distance calculation means is the second correlation value calculation means selected and executed by the correlation value calculation selection means or It is characterized by calculating the distance measuring object on the basis of the shift amount of the window range when the maximum correlation value is obtained among the correlation values obtained by the correlation value calculation means 4.

That is, as means for shortening the distance measuring time without lowering the distance measuring accuracy, in addition to the means described in claim 1, AF data at a predetermined interval among AF data within the window range is used.
A correlation value calculation is performed using the data (third correlation value calculation means) to shorten the distance measuring time, and then the highest correlation value among the correlation values calculated by the third correlation value calculation means is obtained. The correlation value calculation is performed using all the AF data within the window range within a predetermined range before and after the shift amount of the window range as a reference (fourth correlation value calculation means), and the correlation value obtained from this is the highest. It is possible to consider a calculation unit that detects the shift amount when the correlation value is obtained and obtains the distance to the distance measurement target based on the shift amount to prevent the distance measurement accuracy from decreasing. The third and fourth correlation value calculation means are effective when the contrast of the AF data is high, but when the contrast is low, the possibility of erroneous distance measurement increases. Therefore, when the contrast of the AF data is high. For the third and fourth correlation value calculating means,
On the other hand, if the contrast of the AF data is low, the first
Also, the correlation value calculation is performed using the second correlation value calculation means.

According to a ninth aspect of the present invention, the pair of adopted sensor ranges is a sensor in the total distance measuring area of the pair of line sensors, or the total distance measuring area of the pair of line sensors is divided into a plurality of divided areas. A sensor for each divided area. In the latter case, even when the distance measurement by a certain adopted sensor becomes impossible, the distance measurement by another adopted sensor may be possible.

[0020]

BEST MODE FOR CARRYING OUT THE INVENTION Preferred embodiments of the distance measuring apparatus according to the present invention applied to, for example, a camera will be described below in detail with reference to the accompanying drawings.

FIG. 1 is a front perspective view of a camera to which the present invention is applied. As shown in the figure, the camera 10 includes a zoom lens barrel 12 having a photographing lens for forming a subject image on a silver salt film, a strobe light emitting window 16 for emitting strobe light, and a photographer for confirming the subject. A finder window 18 for confirmation, an AF window 22 having a built-in passive type AF sensor for measuring the subject distance, a photometric window 25 having a photometric sensor for measuring the brightness of the subject, and a shutter for the photographer. A shutter button 34 or the like that is operated when instructing a release is provided.

FIG. 2 is a rear perspective view of the camera 10.
As shown in the figure, the camera 10 has an LCD display panel 38 for displaying the set shooting mode and date information.
A flash button 42 for setting the flash firing mode, a self-timer button 44 for setting the self-timer mode, a focus button 46 for setting the focus mode, a date button 48 for setting the date and time, and shooting. A zoom button 50 for indicating the angle of view in the wide direction or the tele direction is provided.

For example, when the flash button 42 is operated, a mode related to the flash (strobe) can be switched. As a mode selectable with the flash button 42, an auto mode in which a strobe light is automatically emitted when a subject is dark, and a main emission is performed. Red-eye reduction mode to reduce red-eye by performing pre-flash before, forced-flash mode to forcibly discharge strobe light, flash-off mode without flash, and night-view portrait mode to shoot person and night scene by flash is there. Further, when the focus button 46 is operated, a mode related to focus can be switched. As modes selectable by the focus button 46, there are an auto focus mode for automatically focusing, a distant view mode for shooting a distant view, and a macro shooting mode. There are modes such as macro mode for.

FIG. 3 is a block diagram showing the control unit of the camera 10. As shown in FIG.
A CPU 60 (information processing means) that controls the entire camera 10 is provided, and it is possible to acquire information from the following units and control the following units according to instructions from the CPU 60. The CPU 60 shown in FIG. 3 is an A composed of a CPU core unit and peripheral circuits such as an I / O, a watchdog timer, and an A / D converter.
It may be a SIC.

Further, as shown in FIG.
CPU6 boosts and stabilizes the battery voltage
0 and other peripheral circuits for supplying power to the peripheral circuits, and a lens barrel for driving the zoom lens barrel 12 by a motor to change the zoom position and the focus position and outputting position information of the zoom position and the focus position to the CPU 60. A drive unit 64 and a film feeding drive unit 66 that drives the film feeding motor to feed the film are provided.

Further, the camera 10 has a shutter drive unit 68 for opening and closing the shutter to expose the film at the time of exposure, and a photometric sensor for measuring the light quantity of the object based on the external light taken in through the photometric window 25 of FIG. 70, and a strobe device 72 that charges the main capacitor and also causes the strobe to emit light by the light emission energy charged in the main capacitor.
And a passive-type AF sensor 74 that acquires data necessary for distance measurement in autofocus from the subject light captured from the AF window 22 in FIG.

In the camera 10, a programmable ROM 82 (recording means such as EEPROM) for rewritably recording various information such as parameters and data relating to control of the camera 10, processing programs, information relating to distance measurement, and the like,
The LCD display panel 38 based on the instruction from the CPU 60
On the other hand, an LCD drive unit 84 for outputting a signal for displaying a figure, a character, a number or the like according to each mode is provided.

Various buttons such as the shutter button 34, the flash button 42, the self-timer button 44, the focus button 46, the date button 48 and the zoom button 50 shown in FIG. 2 are operated by the switches provided corresponding to the respective buttons. Is given to the CPU 60 as an ON / OFF signal. These switches are shown in FIG.
As shown. Regarding the shutter button 34, a half-pressed state (SP1 is ON) and a full-pressed state (SP2 is ON) are detected separately.

The driver 88 shown in FIG.
The zoom drive motor and the focus drive motor provided in the lens barrel drive unit 64 are controlled based on a command from 0,
It is possible to drive the film feeding motor provided in the film feeding driving unit 66. Further, the driver 88 can output the reference voltage and the driving power to the A / D conversion circuit and the photometric sensor 70 based on the command from the CPU 60. Further, the driver 88 is C
Based on a command from the PU 60, it is possible to output to the shutter drive unit 68 a control signal for the shutter that opens and closes during film exposure, and to output to the strobe device 72 a signal for instructing the strobe light emission / stop.

FIG. 4 shows a passive type AF sensor 7.
4 is a diagram showing a configuration of No. 4 of FIG. As shown in the figure, in the AF sensor 74, for example, a lens 92 for forming an image of a subject 90 composed of two colors of white and black on the light receiving surfaces of the left and right sensors, and an image on the light receiving surface. The R sensor 94 and the L sensor 96 are used for transmitting and receiving various data between the CPU 60 and the R (right) sensor 94 on the right side and the L (left) sensor 96 on the left side for photoelectrically converting the formed image and outputting it as a luminance signal.
There is provided a processing circuit 99 for controlling the above and data processing. The R sensor 94, the L sensor 96, and the processing circuit 99 are mounted on the same board, for example.

The R sensor 94 and the L sensor 96 are, for example, C
It is a MOS line sensor and is composed of a plurality of cells (light receiving elements) arranged in a straight line. It should be noted that sensor numbers 1, 2, 3, ... 233, 234 are assigned to the cells of the R sensor 94 and the L sensor 96 in order from the left side in the drawing. However, since the five cells on the left and right sides of the R sensor 94 and the L sensor 96 are not actually used as dummy cells, the effective sensor areas are sensor numbers 6 to 229. These R sensors 94
From each cell of the L sensor 96, a luminance signal corresponding to the amount of received light is sequentially output to the processing circuit 99 in association with the sensor number.

The processing circuit 99 switches the operating state and the non-operating state of the AF sensor 74 in response to an instruction signal from the CPU 60. When control data concerning the operation content is acquired from the CPU 60 in the operating state, the integration processing is performed based on the control data. Etc. start processing. Although details will be described later, the integration process integrates (adds) the brightness signals of the cells obtained from the R sensor 94 and the L sensor 96 for each cell, and integrates the brightness signal of each cell (integrated value of light amount). Is a process for generating. In addition, as a value indicating the integrated value of the luminance signal of each cell, A
When the data output from the light receiving cell of the F sensor 74 is referred to as sensor data, the value actually generated as the sensor data by the processing circuit 99 is a predetermined reference value (reference voltage VREF) that is the integrated value of the luminance signal of each cell. ), And when referred to as sensor data in the following description, this value is referred to. Therefore, the sensor data shows a lower value as the received light amount is larger. However, the sensor data output from the AF sensor 74 is a value based on a signal obtained by integrating the output from each cell for each cell.
If the data indicates the characteristics of the subject captured by the F sensor 74 (for example, the data indicating the contrast of the subject),
At least the processing described below can be similarly applied. Further, in the following description, when simply referred to as integration or integration processing, integration or integration processing for obtaining sensor data (integrated value of luminance signal) is shown.

The integration process is performed by, for example, the R sensor 94.
When the sensor data of any of the cells within the peak selection area, which will be described later, designated by the CPU 60 within the respective sensor areas (in the valid cells) of the L sensor and the L sensor 96 reaches a predetermined integration end value, that is, the peak When the peak value (minimum value) of the sensor data in the selected area reaches the integration end value, it is determined that sufficient sensor data for distance measurement has been obtained, and the process ends. At this time, the processing circuit 99 causes the CPU 6
A signal indicating the end of integration (an integration end signal) is output to 0.
Note that the case where the peak value of the sensor data reaches the integration end value as described above is not used as the integration end condition in the AF sensor 74, but, for example, the average value of the sensor data in the peak selection area reaches a predetermined value. If so, the integration end condition may be used, or another condition may be used as the integration end condition.

The CPU 60 receives the integration end signal and acquires the sensor data of each cell obtained by the integration processing from the processing circuit 99 in association with the sensor number. As a result, the CPU 60 recognizes an image captured by the R sensor 94 and the L sensor 96 (hereinafter referred to as a sensor image). Then, as will be described later in detail, the R sensor 94 and the L sensor 96
Correlation value calculation is performed between the respective sensor images (or after performing the contrast extraction processing of the sensor image), the shift amount of the sensor image when the correlation becomes the highest is calculated, and the distance to the subject 90 is calculated. Yes (principle of triangulation). Figure 5,
FIG. 6 shows sensor images (sensor data) when the distance from the AF sensor 74 to the subject 90 is short and when they are far.
It is the figure which illustrated. When the distance to the subject 90 is short, as shown in FIG.
The sensor data up to 101 becomes a bright value (50),
The sensor numbers 101 to 150 have dark values (200). Since the R sensor 94 is provided at a position different from the L sensor 96, the sensor data of the sensor numbers 85 to 133 has a bright value (50), and the sensor number 1
From 33 to 148, the value is dark (200).

On the other hand, when the distance to the subject 90 is long (for example, when the distance is approximately infinity), the sensor data of the sensor numbers 87 to 117 of the L sensor 96 are bright values, as shown in FIG. (50) and sensor number 118
Up to 150, the value is dark (200). On the other hand, the R sensor 94 is provided at a position different from that of the L sensor 96, but since the subject position exists at a long distance, the sensor data of sensor numbers 85 to 116 is a bright value (5
0), and sensor values 117 to 148 have dark values (200). In this case, the CPU 60 can determine that there is almost no deviation between the sensor images of the R sensor 94 and the L sensor 96, and that the subject exists at approximately infinity. On the other hand, when the subject is present at a short distance as shown in FIG. 5, the shift amount of the sensor image becomes large.

Quantitatively, the subject distance is determined by the R sensor 94.
And the L sensor 96, the distance from each sensor to the lens 92, the pitch of each cell of the R sensor 94 and the L sensor 96 (for example, 12 μm), and the like can be calculated from the shift amount of the sensor image. . The shift amount of the sensor image is R
It can be obtained by performing a correlation value calculation between the sensor images of the sensor 94 and the L sensor 96, and the details will be described later.

Next, the contents of the AF distance measuring process for measuring the distance to the object using the AF sensor 74 having the above-described structure and focusing on the object will be described.

When the processing mode of the camera 10 is set to the imaging mode and the user half-presses the shutter button 34,
The CPU 60 obtains the ON signal of SP1 indicating that the shutter button 34 is half-depressed from the switch unit 86.
When the ON signal of SP1 is acquired, the CPU 60 sets the AE according to the brightness of the subject in order to image the subject, and starts the AF distance measurement process in which the subject is specified and the focus is adjusted.

FIG. 7 is a flow chart showing an outline of the processing procedure of AF distance measurement in the CPU 60. [Step S10 (Distance Measurement Area Setting Processing)] The taking lens can change the focal length by driving the zoom lens barrel 12, while the lens 92 for forming a sensor image on the AF sensor 74 has a fixed focus. It is a lens. Therefore, the distance measuring area is changed according to the lens position (angle of view) of the photographing lens. That is, when the taking lens is at the tele position, the distance measuring area is narrowed.

Here, as shown in FIG. 8, the sensor areas of the R sensor 94 and the L sensor 96 are subjected to processing such as correlation value calculation in units of five divided areas, and the subject distance is calculated for each area. It has become so. If these divided areas are called divided areas below,
The divided area is composed of "right area", "right middle area", "center area", "left middle area", and "left area" as shown in FIG. Further, each divided area shares a partial area (cell) with an adjacent divided area. When calculating the correlation value, the correlation value is calculated individually between the corresponding divided areas of the R sensor 94 and the L sensor 96 (between divided areas having the same name). In the present embodiment, the divided area is formed by dividing the sensor area into five, but the number of divided areas may be other than five.

The distance measuring area includes R sensor 94 and L sensor 9
Of the six sensor areas, the areas are used for distance measurement, and the divided areas are used to determine the areas. Details of the distance measurement area setting process will be described with reference to the flowchart of FIG.

First, the CPU 60 obtains information about the currently set zoom position (angle of view setting angle) from the lens barrel driving section 64, and the current zoom position is on the tele side or the wide side of the predetermined zoom position. It is determined whether (other than tele) (step S10A). For example, the zoom variable range is Z1
When divided into six ranges of Z6, when the current zoom position is set to the tele end side range Z6, it is determined to be the tele side, and when it is set to the other range Z1 to Z5, it is not the tele range. To determine. When the macro mode is set, it is determined to be other than tele.

If it is determined that the tele side,
As shown in (4), in the sensor area of the R sensor 94 and the L sensor 96 (angle of view is ± 6.5 °), the distance measurement area used for distance measurement is the range corresponding to the angle of view of the photographing lens (angle of view). Is within ± 3.9 °). That is, when it is determined to be the tele, the central part “right middle area”, the “center area”, and the “left middle area” among the entire sensor areas (5 areas) of the R sensor 94 and the L sensor 96 are divided into three areas. An area composed of one divided area is set as a distance measuring area (3 area setting) (step S10B). On the other hand, when it is determined that the area is other than tele, the area including the five divided areas of “right area”, “middle right area”, “center area”, “middle left area”, and “left area” is measured. The area is set (5 areas are set) (step S10C). [Step S12 (AF data acquisition process)] Step S
In 12, the acquisition method of AF data (described later) is switched according to the brightness of the subject.

That is, when the brightness of the subject is extremely high or high, the sensor sensitivity (gain of the brightness signal) of the AF sensor 74 is set to low sensitivity and the distance measuring area is set to 3 areas. In the case where the distance measurement area is set to 5 areas, the integration processing is individually performed in the “center area”, the “left middle area”, and the “right middle area” that configure the distance measurement area (see the area in FIG. 10). Performs the integration processing individually in the "center area", "left middle and left area", and "right middle and right area" that constitute the distance measurement area (see the area in FIG. 10). In addition, "left middle and left area" is "left middle area"
And "left area", and "middle right and right area" indicate an area composed of "middle right area" and "right area". Further, the sensor sensitivity of the AF sensor 74 can be switched between two levels of high sensitivity and low sensitivity.

Here, the "center area", "left middle area" (or "left middle and left area"), and "right middle area" (or "right middle and right area") which constitute the distance measuring area In the case of performing the integration processing separately in, when any sensor data in the "central area" reaches the integration end value, the sensor data in the "central area" is acquired, and then the sensor data is reset and integrated. When the sensor data of any cell in the "left middle area" (or "left middle and left area") reaches the integration end value, the "left middle area" (or "left middle and left area") is started. )) Sensor data, then reset the sensor data and start integration, and the sensor data of any cell in the “right middle area” (or “right middle and right area”) is the integration end value. When you reach the "right middle area" ( The "right and in the right area")
It means to acquire the sensor data of. In this way, by individually performing the integration processing of multiple areas, even if a high-intensity light enters one of the areas and the sensor data in that area is inadequate, the effective sensor from other areas Data can be acquired. For example, when the distance measuring area is set to 5 areas, it is assumed that a person who is a main subject as shown in FIGS. 11A and 11B and a high-intensity light behind the person exist in the distance measuring area. To do.
At this time, for example, when the integration processing is performed with the entire area of the distance measurement area as the selection area (peak selection area), FIG.
As shown in, the signal level of the sensor data in the right area corresponding to the high-intensity light becomes appropriate, and the signal level of the sensor data in the central area corresponding to the person who is the main subject becomes small. Therefore, if the subject distance is to be obtained for each divided area, it is determined that distance measurement cannot be performed for the central area, and as a result, the rear light is focused. On the other hand, when the distance measurement area is divided into a plurality of areas and the integration processing is individually performed as described above, as shown in FIG. 11B, it corresponds to the person who is the main subject in the integration processing of the central area. The signal level of the sensor data becomes appropriate, and as a result, the person can be focused.

If the brightness of the subject is medium,
The sensor sensitivity of the AF sensor 74 is set to low sensitivity, and 3
Integral processing is collectively performed in the range-finding areas in which the areas are set or five areas are set. For example, in the case of setting three areas, a "center area", a "left center area", and a "right center area" that configure a distance measurement area (see the area in FIG. 10).
The integration processing of
When the sensor data of one of the cells in the "left middle area" and the "right middle area" reaches the integration end value, the sensor data of the "center area", "left middle area", and "right middle area" are collected. Get in bulk.

Further, when the brightness of the subject is low,
The sensor sensitivity of the AF sensor 74 is set to high sensitivity, and 3
Integral processing is collectively performed in the range-finding areas in which the areas are set or five areas are set. If the sensor data of the cell in the distance measurement area does not reach the integration end value even after the integration time reaches a predetermined time, the sensor sensitivity of the AF sensor 74 is switched to a low sensitivity after the integration is completed. Then, integration is started and auxiliary light for autofocus is emitted from the strobe device 72 (AF pre-emission). In this case,
Integral processing is collectively performed in the distance measurement areas set in 3 areas or 5 areas.

Here, the data output from the light receiving cell of the AF sensor 74 is used as the sensor data, and the image data used after the following contrast detection processing 1 is not limited to the sensor data itself. In some cases, the sensor data may be subjected to contrast extraction processing, etc., so in the processing after the contrast detection processing 1,
AF data is used as a general term for data obtained by directly using sensor data for processing and data obtained by subjecting sensor data to contrast extraction processing. [Step S14 (Contrast Detection Processing 1)] In step S14, it is determined whether or not the AF data acquired in step S12 has a contrast necessary for distance measurement. When it is determined that the AF data does not have the contrast necessary for distance measurement (low contrast determination), distance measurement is impossible.

Here, in the distance measuring area setting process of step S10, when three areas are set as the distance measuring areas, the contrast is set for each of the divided areas of the right middle area, the center area, and the left middle area. Make a decision,
The processing such as the correlation value calculation using the AF data of the divided area determined to have the low contrast is not performed.
Similarly, when 5 areas are set as the distance measuring areas, the contrast determination is performed for each of the divided areas of the right area, the right middle area, the central area, the left middle area, and the left area, and the low contrast is determined. AF of divided areas
The processing such as correlation value calculation using data is not performed. [Step S16 (Correlation Value Calculation Processing)] Step S16
Then, the R sensor 94 and the L sensor 96 of the AF sensor 74
Correlation value calculation is performed between the sensor images (AF data) respectively captured from the above, and the shift amount (shift amount between the left and right AF data) of the sensor images when the correlation is highest is obtained.
The distance of the subject can be obtained from the shift amount between the left and right AF data.

When three areas are set as the distance measuring areas, the correlation value is calculated for each of the divided areas of the right middle area, the center area, and the left middle area, and five areas are set as the distance measuring areas. If it is, the correlation value is calculated for each of the divided areas of the right area, the middle right area, the center area, the middle left area, and the left area. The correlation value calculation is not performed in the divided area in which

Next, the correlation value calculation will be described with reference to FIG.

In FIG. 12, 94A and 96A are sensors of a certain divided area of the R sensor 94 and the L sensor 96 (hereinafter referred to as "adopted sensor").
Also, 94B and 96B are adopted sensors 94A, respectively.
And AF used for correlation value calculation from 96A AF data
An R window and an L window for extracting data.

Here, the shift amount between the R window 94B and the L window 96B is n (n = -2, -1, 0, 1,).
, MAX (= 38)), when n = -2, the R window 94B is located at the left end of the adopted sensor 94A, and the L window 96B is located at the right end of the adopted sensor 96A.
Then, when n = -1, the L window 96B is shifted to the left by one cell from the right end of the adopted sensor 96A, and n =
When it is 0, the R window 94B is shifted to the right by one cell from the left end of the adopted sensor 94A, and similarly, each time n is increased by 1, the R window 94B and the L window 96B.
And move alternately one cell at a time. Then, when n = MAX, the R window 94B is located at the right end of the adopted sensor 94A, and the L window 96B is located at the left end of the adopted sensor 96A.

Assuming that the correlation value between the R window 94B and the L window 96B at a certain shift amount n is f (n), the correlation value f (n) is

[0055]

[Equation 1] Can be expressed as In the formula (1), i is a number indicating the position of the cell in the window (i = 1, 2, ... wo (= 42)), and R (i) and L (i) are R window respectively. It is AF data obtained from the cell at the same cell position i of 94B and L window 96B. That is, as shown in the equation (1), the correlation value f (n) is the sum of the absolute values of the differences of the AF data obtained from the cells at the same cell position in the R window 94B and the L window 96B, and the correlation is high. The closer to zero.

Therefore, the correlation value f (n) is changed by changing the shift amount n.
Then, the distance of the object can be obtained from the shift amount n when the correlation value f (n) is the smallest (when the correlation is the highest). It should be noted that when the subject distance is infinity, the correlation is highest when the shift amount is n = 0, and when the subject distance is at the close end, the subject image is R so that the correlation is highest when the shift amount is n = MAX. An image is formed on the sensor 94 and the L sensor 96. Further, the calculation formula for obtaining the correlation is not limited to the above formula (1), and other calculation formulas can be used. In that case, the higher the correlation is, the larger the correlation value may be. In this case, the magnitude relation of the correlation values in the following description is inverted and the present embodiment is applied to the arithmetic expression. For example, the minimum value of the correlation value calculated by the above formula (1) becomes the maximum value, and the phrase such as small or large for the correlation value calculated by the above formula (1) is inverted to the phrase such as large or small. And can be applied. [Step S18 (Contrast Detection Processing 2)] In step S14, it is determined whether or not the AF data in the divided area has a contrast necessary for distance measurement, whereas in step S18, the correlation is maximum. It is determined whether or not the AF data within the window range when the shift amount is n has the contrast necessary for distance measurement. If it is determined that the contrast is low, it is determined that distance measurement is impossible, and distance measurement based on the shift amount n at that time is not performed. [Step S20 (L, R Channel Difference Correction Processing)] In step S20, the left and right AF data obtained from the AF sensor 74 are compared with each other in the minimum value of the left and right AF data within the window range where the correlation is maximum. To do. Then, when the absolute value of the difference between the minimum values of the left and right AF data is greater than or equal to the first reference value and less than or equal to the second reference value, the AF data of the channel that does not exceed the dynamic range is corrected.
If the correlation value when the correlation becomes maximum is small, it can be judged that the result of the correlation value calculation is highly reliable without correcting the AF data. The AF data may be corrected only when the value is equal to or larger than the third reference value.

When the AF data is corrected, the correlation value is calculated again to obtain the minimum correlation value. And
The minimum correlation value after correction is compared with the minimum correlation value before correction, and the shift amount of the correlation value having the higher degree of coincidence is adopted. [Step S22 (Interpolation Value Calculation Processing)] Step S22
Then, after obtaining the correlation value f (n) (minimum minimum value) when the correlation is highest, the shift amount is within 1 (cell of the AF sensor 74) by using the minimum minimum value and the correlation values before and after. Of 1
Interpolation value within the pitch) is calculated.

In the interpolation value, when the shift amount at which the minimum minimum value is obtained is n, the minimum minimum value and the shift amount n
Based on the correlation values in a plurality of shift amounts before and after (at least three correlation values), the intersection of two straight lines passing through these correlation values and intersecting in a V shape is obtained, and the position of the intersection and the shift amount. It is calculated as a difference value from n. [Step S24 (AF error processing)] Step S24
Then, if it is determined that the distance measurement is impossible in all the distance measurement areas of the three area setting or the five area setting, the photographing lens is set so as to focus on the preset object distance.

That is, when the auxiliary light for autofocus is emitted and it is determined that there is an error due to insufficient AF data amount in all distance measuring areas, the taking lens is set so that it is focused at infinity.

When an auxiliary light for autofocus is emitted and it is determined that an error occurs due to insufficient AF data amount in all distance measuring areas, the fixed focus set distance that can reach the strobe is switched according to the film sensitivity. For example,
For ISO 400 or higher, set the fixed focus set distance to 6
When ISO is less than 400, the fixed focus set distance is 3 m. Further, the fixed focus set distance for focusing may be switched depending on the type of error. [Step S26 (Distance Calculation Processing)] In step S26, the shift amount n when the correlation value of the minimum minimum value is obtained by the correlation value calculation in step S16, and step S22
The subject distance is calculated based on the interpolation value calculated in.
Note that the subject distance is calculated for each of all the distance measuring areas set in the three areas or the five areas. [Step S28 (area selection processing)] If no error occurs during AF distance measurement processing, 3 is set when 3 areas are set.
One subject distance is calculated, and when five areas are set, five subject distances are calculated. When a plurality of subject distances are calculated, the closest subject distance is basically adopted.

Five object distances are calculated when the five areas are set. Of these object distances, the object distance corresponding to either the left area or the right area is the super close distance, and other than that. When all the subject distances corresponding to the area are beyond the intermediate distance, the super close result is not adopted, and the closest object distance among the object distances beyond the intermediate distance is adopted. {Details of AF data acquisition process (step S12 in FIG. 7)}
Next, the AF data acquisition process in step S12 of FIG. 7 will be described in detail.

First, the peak selection area will be described. The peak selection area is a cell for monitoring whether or not the peak value (minimum value) of the sensor data has reached the integration end value in the integration processing of the AF sensor 74. A range. FIG.
FIG. 6 is a diagram showing a mode of a peak selection area set in an AF data acquisition process described below. The peak selection area is configured with the divided areas described in FIG. 8 as a unit, and the divided areas of the R sensor 94 and the L sensor 96 are shown in FIG. 13A. On the other hand, the peak selection regions are shown in FIGS. 7B to 7H, and the peak selection regions can be switched to seven types of regions to.

The area shown in FIG.
The L sensor 96 is composed of three divided areas of “center area”, “middle right area”, and “middle left area”. The area shown in FIG.
“Center area”, “right middle area” in the sensor 96,
5 of "right area", "left middle area", and "left area"
It consists of two divided areas. The area is shown in FIG.
The area is equal to the area when the three areas are set, and the area is
This is equal to the area when 5 areas are set as shown in FIG. Areas shown in (D), (E), and (F) of the same figure are the “center area”, “left middle area”, and “right middle area” of the R sensor 94 and the L sensor 96, respectively. The area shown in (G) is an R sensor 94 and an L sensor 96.
In the left middle area and the left area in FIG.
It consists of the right middle area and the right area.

FIG. 14 is a flow chart showing the procedure of AF data acquisition processing. First, the CPU 60 refers to the signal output of the light amount output by the photometric sensor 70, and determines whether or not the light amount obtained from the subject is equal to or higher than a predetermined threshold value for determining the ultra-high brightness (step S50). When the determination is NO, the CPU 60 causes the AF sensor 74 (processing circuit 99 of the AF sensor 74) to start the collective gain high integration processing (step S52). In the following description, the processing circuit 99 of the AF sensor 74 does not describe the processing circuit 99, but simply describes it as the AF sensor 74.

In the collective high gain integration, an area in the same range as the distance measuring area set by the distance measuring area setting process of step S10 shown in FIG. 7 is set as the peak selection area, and
This is a process in which the sensor sensitivity of the AF sensor 74 is set to high and the sensor data of each cell in the distance measurement area is collectively acquired. When the distance measurement area is set to three areas in the distance measurement area setting process (when the zoom position is tele),
The peak selection area is set to the area shown in FIG. On the other hand, when the distance measuring area is set to 5 areas (when the zoom position is other than tele), the peak selection area is set to the peak selection area shown in FIG. 13 (C). Note that the collective gain high integration is an integration process for acquiring sensor data when the subject brightness is low,
As will be understood from the description below, this is also processing for determining whether the subject brightness is in high brightness, medium brightness, or low brightness. Instead of the collective gain high integration process of step S52, another method for determining the subject brightness may be adopted.

After the start of the high-integration of the collective gain by the AF sensor 74, the CPU 60 waits for the AF sensor 74 to output an integration end signal indicating the end of the integration process. The time (integration time) required for the integration process to end after the integration process starts is less than 2 ms, or 2 ms or more and 4 m
It is determined whether it is less than s or 4 ms or more (whether the integration process is not completed even after 4 ms has elapsed) (step S54).

If the integration time is less than 2 ms, the AF sensor 74 judges that the subject has high brightness.
Sensor data is reset, and the process is switched to the three-part low gain integration process, the details of which will be described later (step S56). If the integration time is 2 ms or more and less than 4 ms, it is determined that the subject has medium brightness, the sensor data of the AF sensor 74 is reset, and the process is switched to the collective gain low integration process described in detail later (step S58). . 4m integration time
If it is s or more, it is determined that the subject has low brightness, and low-luminance processing, which will be described in detail later, is executed (step S60).

Here, in step S50, YE
S, that is, 2 m when the subject is determined to have ultra-high brightness
Similar to the case where the processing ends in less than s, the 3-division gain low integration processing is executed (step S56).

In the processing of the 3-division gain low integration in step S56, the sensor sensitivity of the AF sensor 74 is set to low sensitivity,
Further, it is a process of the CPU 60 which divides the distance measuring area set in the distance measuring area setting process into three, and causes the AF sensor 74 to perform the integration process by setting each of the divided areas as a peak selection region in order.

That is, when the distance measurement area is set to three areas in the distance measurement area setting process of step S10 in FIG. 7 (when the zoom position is tele), the distance measurement areas are the "center area", the "left middle area" and the It consists of the "right middle area". The distance measuring area is divided into three areas, that is, a "center area", a "left middle area", and a "right middle area", and the integration processing is executed by sequentially using each of the divided areas as a peak selection area. In the aspect of the peak selection area shown in FIG. 13, the areas of (D), (E) and (F) of FIG.
Are sequentially set as peak selection regions. In particular,
As shown in the flowchart of FIG. 15, first, the central area (area) is set as the peak selection area (step S8).
0), the sensor sensitivity of the AF sensor 74 is set to low sensitivity (step S82), and the integration process is started (step S).
84). When this integration processing is completed and the CPU 60 acquires the sensor data of the area (step S86), the distance measuring area is set to three areas (step S88), and subsequently, the left middle area (area) is set as the peak selection area. (Step S90) Further, the sensor sensitivity of the AF sensor 74 is set to low sensitivity (Step S92), and the integration process is started (Step S94). This integration process ends, and the CPU 6
When 0 acquires the area sensor data (step S9)
6) Subsequently, the right middle area (area) is set as the peak selection area (step S98), the sensor sensitivity of the AF sensor 74 is set as low sensitivity (step S100), and the integration process is started (step S102). When this integration processing is completed and the CPU 60 acquires the sensor data of the area (step S104), the three-division gain low integration processing is completed. As a result, the sensor data of each divided area within the distance measurement area necessary for the distance measurement calculation thereafter is acquired.

On the other hand, in the distance measuring area setting process, 5
When the area is set (when the zoom position is other than tele), the distance measurement area consists of "center area", "left middle area", "left area", "right middle area", and "right area". . This distance measuring area is shown in FIG.
(G) and (H) area are divided into three areas, and the integration processing is executed using each area as a peak selection area in order. Specifically, with the flowchart in FIG. 15, as in the case of the above-described three-area setting, first, the central area (area) is set as the peak selection area (step S8).
0), the sensor sensitivity of the AF sensor 74 is set to low sensitivity (step S82), and the integration process is started (step S).
84). When this integration process is completed and the CPU 60 acquires the sensor data of the area (step S86), the distance measuring area is set to 5 areas (step S88), and then the left middle area and the left area (area) are peaked. The selected area (step S106), and the AF sensor 74
The sensor sensitivity of is set to low sensitivity (step S108) and the integration process is started (step S110). When this integration processing ends and the CPU 60 acquires the sensor data of the area (step S112), subsequently, the right middle area and the right area (area) are set as the peak selection area (step S11).
4) Further, the sensor sensitivity of the AF sensor 74 is set to low sensitivity (step S116), and the integration process is started (step S118). When the integration processing is completed and the CPU 60 acquires the sensor data of the area (step S120),
The process of 3-division gain low integration is completed. As a result, the sensor data of each divided area within the distance measurement area necessary for the distance measurement calculation thereafter is acquired.

In the above description, when the distance measuring area is set to five areas, the distance measuring area is divided into three areas, but the present invention is not limited to this, and each divided area is divided into five areas. The sensor data may be acquired by performing the integration process by sequentially setting the divided areas as the peak selection area. That is, the number of areas into which the distance measuring area is divided is not limited to the case of this embodiment, and the setting can be changed arbitrarily.

The process of collective gain low integration in step S58 of FIG. 14 switches the sensor sensitivity of the AF sensor 74 from high sensitivity to low sensitivity without changing the peak selection region adopted in the collective gain high integration of step S52. A
This is the processing of the CPU 60 that causes the F sensor 74 to execute the integration processing.

That is, when the distance measuring area is set to three areas in the distance measuring area setting process (when the zoom position is tele), the peak selection area is set to the area shown in FIG. , The sensor sensitivity of the AF sensor 74 is set to low sensitivity, and the AF sensor 74 is caused to execute the integration process. On the other hand, when the distance measuring area is set to five areas in the distance measuring area setting process (when the zoom position is other than tele), the peak selection area is set to the area shown in FIG. The sensor sensitivity of the sensor 74 is set to low sensitivity and the AF sensor 74 is caused to execute the integration process.

When the above integration processing is completed, the CPU 60
Acquires sensor data in the distance measuring area from the AF sensor 74. As a result, the sensor data of each divided area within the distance measurement area necessary for the distance measurement calculation is acquired.

The low-luminance process in step S60 of FIG. 14 is a process of continuing the collective gain high integration process in step S52 until the integration process is completed within the maximum allowable integration time.

The maximum allowable integration time differs depending on the photographing mode. If the photographing mode is set to the light emission prohibition mode, the maximum allowable integration time is 200 ms (maximum after the integration time of the collective gain high integration in step S52 is 4 ms or more). The integration process is continued as it is with the allowable integration time) as the limit.
If the integration process ends normally within 200 ms (when the integration ends because the peak value of the sensor data in the peak selection area reaches the integration end value (the same applies below)), the sensor at that point AF sensor 74 data
To get from. On the other hand, if the integration processing does not end normally after 200 ms has elapsed, the integration processing is forcibly ended by the instruction signal from the CPU 60, and the sensor data at that time is acquired from the AF sensor 74.

If the photographing mode is not the light emission prohibition mode, first, the integration process is continued as it is with 100 ms as a limit (maximum allowable integration time) even after the integration time of the collective gain high integration in step S52 has passed 4 ms or more. Let it continue. If the integration process ends normally within 100 ms, the sensor data is sent to the AF sensor 7 at that time.
Get from 4. On the other hand, if the integration processing does not end even after the integration time reaches 100 ms, the integration processing is forcibly ended by the instruction signal from the CPU 60. And
The integration process is restarted while the AF pre-emission is performed by the auxiliary light emitted from the strobe device AF72. In addition, when the mode is set to capture the night view and the person in front of the camera at the same time as in the night view portrait mode, the integration time of the collective gain high integration is set to prevent the trouble of focusing on the night view. Is limited to 25 ms instead of 100 ms, and if the integration process does not end normally even if the integration time reaches 25 ms, the integration process is forcibly ended and the integration process is started together with the AF pre-emission. Note that, hereinafter, the process of performing integration while the AF pre-emission is performed is referred to as pre-emission process.

When the integration processing by the pre-light emission processing is started, the peak sensitivity region adopted in the high gain integration of the collective gain in step S52 is not changed, and the sensor sensitivity of the AF sensor 74 is switched from high sensitivity to low sensitivity. To start the integration process. Further, the AF pre-emission is performed by setting a predetermined upper limit number of times by intermittent pulse emission. As a result, if the integration process ends normally before the pre-flash reaches the upper limit number of times, the sensor data at that time is set to A.
It is acquired from the F sensor 74. On the other hand, if the integration process does not end normally even if the pre-light emission reaches the upper limit number of times, the integration process is forcibly ended and the sensor data at that time is acquired from the AF sensor 74.

In the above embodiment, the range-finding area is divided into a plurality of areas (peak selection areas) only when the subject brightness is high brightness or ultra-high brightness, and the sensor data is acquired for each area. However, even when the subject brightness is medium brightness or low brightness, the distance measurement area may be divided into a plurality of areas and the sensor data may be acquired for each area as in the case of high brightness.

Further, in the above-described embodiment, the case where the subject brightness is ultra-high brightness, high brightness, medium brightness, and low brightness is divided into cases, and the acquisition processing of the sensor data corresponding to each case is performed. However, the present invention is not limited to this, and the subject brightness level may be divided into finer or rougher cases than in the above-described embodiment and the acquisition processing of the sensor data corresponding to each subject brightness level may be performed.

Next, the processing operation of the CPU 60 and the AF sensor 74 (processing circuit 99) when executing the AF data acquisition processing will be described in detail. As shown in FIG. 16, the CPU 6
Various signals are transmitted and received between 0 and the AF sensor 74 by a plurality of signal lines. The signal line of the signal transmitted from the CPU 60 to the AF sensor 74 is AF
A signal for switching the sensor 74 to an operating state or a non-operating state is transmitted / AFCEN, a signal for instructing setting of control data is transmitted / AFRST, a signal indicating the content of control data is transmitted AFAD, READ / WRIGH.
There is AFCLK etc. in which the T-clock pulse is transmitted.
As a signal line of a signal transmitted from the AF sensor 74 to the CPU 60, a signal indicating that the integration process is completed is transmitted / AFEND, and the peak value (minimum value) of the sensor data in the peak selection region is transmitted as analog data. MDATA, R sensor 94 and L sensor 96
There is AFDATAP or the like in which the sensor data of each cell is transmitted as analog data. In the following, the type of signal transmitted from each signal line is identified by the name of the signal line (/ AFCEN signal, / AFRST signal, etc.).

The operation timing of transmission and reception of the above signals in the CPU 60 and the AF sensor 74 will be described with reference to the operation timing chart of FIG. When the CPU 60 sets the / AFCEN signal to 1 (High level), the AF sensor 74 is in the inoperative state, and the CPU 6
When 0 switches the / AFCEN signal to 0 (Low level), the AF sensor 74 switches to the operating state (time T1
0).

When a predetermined time (10 ms) elapses after the AF sensor 74 is switched to the operating state, the CPU 60 switches the / AFRST signal from 1 to 0 to switch the AF sensor 7
4 is instructed to set the control data (see time T20). Then, the CPU 60 transmits the control data by the AFAD signal to the AF sensor 74, and
A clock pulse is transmitted by the AFCLK signal (see the period from time T20 to T30). AF sensor 74 is / A
When the FRST signal is switched from 1 to 0, AFCL
AF in synchronization with the clock pulse given by the K signal
Read the signal level of the AD signal. As a result, data necessary for integration processing such as the peak selection area and sensor sensitivity is set in the AF sensor 74. As the control data, 128 pieces of data represented by 1 or 0 from D0 to D127 are transmitted in time series, and the contents of the control data will be described later.

The final data (D12
7) is transmitted (see time T30), and 100 μs has elapsed (see time T40), the CPU 60 causes / AFRST.
The signal is switched from 0 to 1 and the start of integration processing is instructed. As a result, the AF sensor 74 starts light reception by each cell of the R sensor 94 and the L sensor 96 after 150 μs when the sensor sensitivity is set to high sensitivity and after 30 μs when the sensor sensitivity is set to low sensitivity. Along with
The integration of the luminance signal sequentially output from each cell is started (see time T50). At the same time, the AF sensor 74
The FEND signal is switched from 1 to 0, and the start of integration is transmitted to the CPU 60. Also, the peak value of the sensor data in the peak selection area is output as analog data by the MDATA signal.

After the integration process is started, when the peak value of the sensor data reaches a predetermined integration end value VEND (for example, 0.5V), the AF sensor 74 ends the integration of the brightness signal and outputs the / AFEND signal. Switch from 0 to 1 (see time T60). In addition, 0 to 1 of / AFEND signal
The changeover to becomes the integration end signal.

The CPU 60 detects the integration time by detecting the time when the / AFEND signal is set to 0 (the period from time T50 to T60), and
It is detected that the integration is completed by switching the D signal from 0 to 1.

When the integration is completed, the CPU 60 sends a clock pulse by the AFCLK signal to the AF sensor 74 to instruct the reading of the sensor data (time T7).
0). When the peak value of the sensor data in the peak selection area reaches the integration end value, the AF sensor 74
Has an automatic end mode in which the integration is automatically ended, and an external end mode in which the integration is ended by an instruction from the outside (CPU 60) regardless of whether or not the peak value of the sensor data reaches the integration end value. In the former case, the CPU 60 maintains the state in which the AFAD signal is set to 1, and transmits the clock pulse, and in the latter case, the AFAD signal is set to 0.
Then, the clock pulse is transmitted after the integration of the AF sensor 74 is completed. Even in the former case, the CPU 60 can forcibly end the integration in the AF sensor 74 by switching the AFAD signal from 1 to 0.

The AF sensor 74 uses the sensor data obtained by integrating each cell in synchronism with the clock pulse given by the AFCLK signal as analog data from the sensor number 1 to the sensor number 23 of the L sensor 96 and the R sensor 94.
Up to 4 are transmitted to the CPU 60 alternately. This makes CP
U60 acquires the sensor data from the AF sensor 74.

Next, the content of the control data transmitted / received by the AFAD signal will be described. As described above, the control data is composed of 128 pieces of 1 or 0 data from D0 to D127 (time T20 to T30 in FIG. 17).
See period). Of these, D0 to D111 are peak selection region setting data indicating peak selection regions to be set in the AF sensor 74, and D112 to D118 are peak selection region number data indicating the number of peak selection regions.
Details of the peak selection area setting data and the peak selection area number data will be described later.

D119 to D120 are dummy data (0), and D121 is sensitivity data indicating the sensor sensitivity to be set. In the present embodiment, the sensor sensitivity can be switched in two steps of high and low, and D121 is set to 1
In the case of, high sensitivity is set, and in the case of D121 is 0, low sensitivity is set.

D122 is integration mode data indicating a mode relating to the end of integration. When D122 is 1, it indicates the setting of the external end mode in which integration is ended by an instruction from the outside, and when D122 is 0, the peak is set. The sensor data in the selected area has a predetermined integration end value (integration end voltage) V
The setting of the automatic end mode in which the AF sensor 74 automatically ends the integration process when reaching END is shown.

D123 is automatic integration end voltage setting data for setting the integration end value VEND in the automatic end mode. In this embodiment, when D123 is 1, the voltage L is set, and D123 is In the case of 0, the setting of the voltage H is shown.

D124 to D126 are reference voltages VREF.
Is VREF selection data for setting. Eight kinds of reference voltages can be set by 3-bit data.
D127 is end data indicating the end of the control data and is always set to 1.

Next, the peak selection area setting data D0 to D
111 and peak selection area number data D112 to D118
Will be explained in detail. The R sensor 94 and the L sensor 96 are
As shown in FIG. 18, each is composed of 234 cells of sensor numbers 1 to 234. The left and right five cells (sensor numbers 1 to 5 and sensor numbers 230 to 234) of each of the sensors 94 and 96 are dummy cells,
Actually effective cells (effective pixels) are sensor numbers 6 to 229.
Up to 224.

In the processing of the CPU 60 and the AF sensor 74, the cells of the sensor numbers 6 to 229 in the effective pixel range are managed on a block-by-block basis with four adjacent cells as one block, as shown in FIG. L sensor 96
, From sensor number 229 to sensor number 6 in units of four, block numbers D0, D1, ..., D55 (5 blocks)
6) is assigned, the sensor number 229 of the R sensor 94
Block number D5 in units of 4 from sensor number 6 to sensor number 6
6, D57, ..., D111 (56 blocks) are assigned.

The data of D0 to D111 transmitted and received as control data between the CPU 60 and the AF sensor 74 are
The peak selection area setting data D0 to D111 corresponding to the block numbers thus assigned are shown in FIG.
9, the setting data for the L sensor 96 is D0 to D55 which are not surrounded by the dotted line, and the setting data for the R sensor 94 is D56 to D111 which is surrounded by the dotted line. . For example, setting data D
0 and D56 indicate setting data for the sensor numbers 226 to 229 of the L sensor 96 and the R sensor 94, respectively, and setting data D55 and D111 set to the sensor numbers 6 to 9 of the L sensor 96 and the R sensor 94, respectively. Show the data.

Peak selection area setting data D0 to D111
Indicates whether or not the four cells having the block number corresponding to the setting data are set as cells in the peak selection area. When the setting data is 1, the block number 4 corresponding to the setting data is set to 4. One cell is set as a cell within the peak selection area, and when the setting data is 0, four cells with block numbers corresponding to the setting data are set as cells outside the peak selection area. For example, when the setting data D0 is 1, the cells 229, 22 of the L sensor 96
8, 227 and 226 are set as cells in the peak selection area.

The peak selection area number data D transmitted and received as control data together with the peak selection area setting data D
Reference numerals 112 to D118 represent the number of blocks to be set as the peak selection area in accordance with the peak selection area setting data in a binary number. As shown in FIG. 20, D112 is the most significant bit and D118 is the least significant bit. The bit data represents the number of blocks set as the peak selection area. As shown in (A) of the figure, when only D115 is 1, the number of blocks set as the peak selection region is 8.
When D112 to D114 are 1 and D115 to D118 are 0 as shown in FIG. 7B, the number of blocks set as the peak selection region is 112.

Next, the procedure for generating the peak selection area setting data will be described. The peak selection area is set to any one of areas 1 to 3 as shown in FIG. The peak selection area setting data when setting each area (1) to (3) as the peak selection area is generated as follows.

For example, as shown in FIG. 21, the R sensor 94
Alternatively, when the region P (hatched portion) in the sensor region S of the L sensor 96 is set as the peak selection region, the sensor numbers of the cells at the right and left ends of the region P are obtained, and the sensor numbers of the cells at the right and left ends of the region P are calculated. The cells between the sensor numbers are the cells in the peak selection area.

Here, it is assumed that the sensor number of each cell indicates the address of each cell, and in particular, the right end address of the area P is the peak selection start address PS and the left end address is the peak selection end address PE.

On the other hand, the area P is used as information for specifying the area P.
It is assumed that the address S1 at the right end, the address S2 of a predetermined cell in the region P, and the number of cells (the number of sensors) D from the cell at the address S2 to the leftmost cell of the region P are given in advance as reference data. At this time, the peak selection area start address PS and the peak selection area end address PE of the area P
Is

[0104]

[Equation 2] PS = S1 (2) PE = S2 + D-1 (3) In the R sensor 94, the peak selection start address PS, the peak selection end address PE, and the reference data S1, S2, D for the area to be the peak selection area are PSR, PER, SR, respectively.
1, SR2, DR, and the peak selection start address PS, peak selection end address PE, and reference data S1 for the area to be the peak selection area in the L sensor 96.
S2 and D are PSL, PEL, SL1 and SL respectively
2, identified as DL.

A specific description will be given of the case where each of the areas shown in FIG. 13 is set as the peak selection area.
The address of the cell at the right end of each divided area of the R sensor 94 and the L sensor 96 and the number of adopted sensors (the number of cells) of each divided area are used as reference data when setting each area to the peak selection area.

In the present embodiment, the R sensor 94 and L
FIG. 22 shows a specific numerical example of the address of the cell at the right end of each divided area used for the sensor 96 and the number of adopted sensors in each divided area. The R sensor 94 is indicated by a numerical value without parentheses, and the L sensor 96 is indicated by a numerical value in parentheses.

For example, when the area is the peak selection area, the reference data SR1 and SR for the R sensor 94 are used.
2 and DR are the address 46 of the cell at the right end of the middle left area, the address 126 of the cell at the right end of the middle right area, and the number of adopted sensors 62 in the middle right area, respectively. Similarly, L sensor 9
The reference data SL1, SL2, and DL for 6 are the address 48 of the cell at the right end of the left middle area, the address 128 of the cell at the right end of the right middle area, and the adopted sensor number 62 of the right middle area, respectively. Using these reference data as the above formula (2),
Substituting into (3), the peak selection start addresses PSR, PSL of the area in the R sensor 94 and the L sensor 96,
The peak selection end addresses PER and PEL are calculated.
That is,

[0108]

## EQU3 ## PSR = 46 PER = 126 + 62-1 = 187 PSL = 48 PEL = 128 + 62-1 = 189 is calculated. Therefore, when the area is set as the peak selection area, the sensor numbers 46 to 18 for the R sensor 94 are used.
It is determined that the cell No. 7 is a cell within the peak selection area, and for the L sensor 96, the cells with sensor numbers 48 to 189 are each required to be a cell within the peak selection area.

In the case where the areas other than the area 1 to 3 are set as the peak selection area, the peak selection start addresses PSR, PSL, and the peak selection end address PE are similarly set as described above.
R and PEL can be calculated. That is, in the peak selection area to be set, the rightmost address in the rightmost divided area is set as the reference data SR1 and SL1, and the rightmost address in the leftmost divided area is set as the reference data SR2 and SL2. Further, the numbers of adopted sensors in the divided area at the left end are DR and DL. Then, by substituting these values into the above equations (2) and (3), the peak selection start addresses PSR and PSL and the peak selection end addresses PER and PEL in the case of setting each area to as the peak selection area are calculated. can do. FIG. 22
, Also in the case of regions, PSR =
6, PER = 227, PSL = 8, PEL = 229, in the case of a region, PSR = 86, PER = 147, PS
L = 88, PEL = 149, PSR in case of area
= 46, PER = 107, PSL = 48, PEL = 10
In case of 9, area, PSR = 126, PER = 18
7, PSL = 128, PEL = 189, in the case of a region, PSR = 6, PER = 107, PSL = 8, PEL
= 109, PSR = 126, PER in case of area
= 227, PSL = 128, and PEL = 229.

The right area, the right middle area, the central area,
The address of the cell at the right end of each divided area in the R sensor 94 in the order of the middle left area and the left area is RSR, RMS
R, MSR, LMSR, LSR, the number of adopted sensors in each area is RWR, RMWR, MWR, LMWR, LWR, and the address of the rightmost cell of each divided area in the L sensor 96 is RSL, RMSL, SL, LMSL,
LSL, the number of sensors used in each area is RWL, RMWL,
Assuming MWL, LMWL, and LWL, the above-mentioned SR is applied when each region to is a peak selection region as shown in FIG.
1, SR2, SL1, SL2, DR, and the address assigned to DL and the number of sensors correspond to each other.

As described above, when the peak selection start address PS and the peak selection end address PE of the area to be used as the peak selection area are obtained, next, as shown in FIG. D55, D56 ~
The range of the peak selection area is obtained by D111. At this time, the four cells of the block number including the peak selection start address PS and the peak selection end address PE are cells in the peak selection area.

Therefore, for each of the L sensor 96 and the R sensor 94, the block number at the left end of the peak selection region is the peak selection start block number DSL, DSR, and the block number at the right end of the peak selection region is the peak selection end block number DEL, Assuming DER,

[0113]

(4) DSL = INT ((229-PEL) / 4) (4) DEL = 55-INT ((PSL-6) / 4) (5) DSR = 56 + INT ((229-PER) / 4) (6) DER = 111-INT ((PSR-6) / 4) (7) gives DSL, DEL, DSR, and DER. However, if DSL <0, set DSL = 0 and then DEL>
In the case of 55, DEL = 55, in the case of DSR <56, DSR = 56, and in the case of DER> 111, DE
Let R = 111.

For the R sensor 94, the peak selection area is the range from the block number DSR to DER,
For the L sensor 96, block numbers DSL to DE
Since the range is up to L, the peak selection area setting data D
0-D111 is set to 1 in those ranges,
It is set to 0 in other ranges.

At this time, the number of peak selection areas is set to DP.
Let S be the number of peak selection regions DPS,

[0116]

## EQU5 ## DPS = DEL-DSL + 1 + DER-DSR + 1 (8) Peak selection area number data D112 to D
118 is obtained by expressing DPS by a binary number.

FIG. 24 shows the above equation based on the numerical example shown in FIG. 22 when each of the areas from FIG.
Peak selection area setting data D generated by (4) to (8)
0 to D111 and peak selection area number data D112 to D
It is the figure which showed 118. For example, when the area is the peak selection area, the peak selection start addresses PSR, PS
Since L is 46 and 48, respectively, and peak selection end addresses PER and PEL are 187 and 189, respectively, substituting these numerical values into the above equations (4) to (7), the peak selection start block numbers DSL and DSR. Are each 1
0 and 66, and the peak selection end block number DEL,
The DERs are 45 and 101, respectively. Therefore, FIG.
Peak selection area setting data D0 for area 4
As shown in D111, D0 to D9 are 0, D10 to D4
5 is 1, D46 to D55 is 0, D56 to D65 is 0, D
66 to D101 are 1 and D102 to D111 are 0.
Also, the number of peak selection regions is 1 according to the above equation (8).
12, and as shown in the peak selection region number data D112 to D118 for the region of FIG. 24, each data value becomes 1001000 in order.

As described above, when each of the areas 1 to 3 is set as the peak selection area, the peak selection area setting data D0 is set.
To D111 and peak selection area number data D112 to D11
Since 8 is generated as the reference data using the address information indicating the range of each divided area, it is not necessary to register a huge amount of data as shown in FIG. 24 in the memory in advance, which saves the memory. be able to. In the above embodiment, the case where the right end address of each divided area and the number of adopted sensors are referred to as the address information indicating the range of each divided area has been described. Peak selection area setting data D with the right and left edge addresses of the area as reference data
0 to D111 and peak selection area number data D112 to D1
18 can also be generated. Further, as long as it is address information indicating the range of each divided area, even if it is address information other than the above, the peak selection area setting data D0 to D111
The peak selection area number data D112 to D118 can be generated.

Next, the processing when the / AFEND signal is not normally output from the AF sensor 74 will be described. For example, step S52 and step S5 in FIG.
6. In each integration process in step S58, the / AFRST signal is normally 0 to 1 as shown in FIG.
After switching to (see time T40), integration is started after a lapse of a predetermined time (150 μs when the sensor sensitivity is high sensitivity, 30 μs when the sensor sensitivity is low) / AFEN
The D signal switches from 1 to 0 (see time T50). When the peak value of the sensor data in the peak selection area reaches the integration end value, the / AFEND signal switches from 0 to 1 (see time T60). CPU60 is this / AF
The change of the END signal from 0 to 1 is detected as an integration end signal, and the end of integration is recognized.

On the other hand, when the subject brightness is low,
If the subject brightness exceeds a certain level, or / AF
In the case of a connection error of the END signal, the / AFEND signal may not be normally output even after the maximum allowable integration time has elapsed.

The reason why the / AFEND signal is not normally output when the subject brightness is low (the / AFEND signal does not switch from 0 to 1) is that the peak value of the sensor data has not reached the integration end value. For example, when the subject is bright, a peak is generated after the / AFEND signal is switched from 1 to 0 (after the integration process is started) and before the maximum allowable integration time elapses, as shown in FIG. Since the peak value of the sensor data in the selected area reaches the integration end value (see the MDATA signal in the same figure), the / AFEND signal switches from 0 to 1 (the integration end signal is output). On the other hand, when the subject is dark, FIG.
As shown in (C), since the / AFEND signal is switched from 1 to 0 and before the maximum allowable integration time elapses, the peak value of the sensor data in the peak selection area does not reach the integration end value (MDATA in the figure). Signal), / AFEND signal is 0 to 1 before the maximum allowable integration time elapses
The integration end signal is not output without switching to. When the maximum allowable integration time is reached, the CPU 60 causes the AF sensor 7
4 signal forcibly ending the integration process (FIG. 26 (B)).
AFAD = “L”) is given, the integration processing is terminated by the signal when the maximum allowable integration time has elapsed,
The / AFEND signal switches from 0 to 1.

On the other hand, the / AFEND signal is not normally output when the subject brightness exceeds a certain brightness (/ AF
END signal does not switch from 1 to 0, and / AF
The fact that the END signal does not switch from 0 to 1) is a problem in the characteristics of the AF sensor 74. That is, if the integration processing is normally performed and the subject brightness is extremely high even if the peak value of the sensor data reaches the integration end value, the AF sensor 7
In some cases, the / AFEND signal may not be output normally due to the characteristics of No. 4, and for example, the / AFEND signal may have the following output form (particularly, this is likely to occur during the gain sensitive integration in step S32 of FIG. 14). . When the subject brightness exceeds a certain level, as shown in FIG. 25, / AFRS
The / AFEND signal, which should originally be switched to 0 at the start of integration after a predetermined time has elapsed after the T signal was switched from 1 to 1, does not switch to 0 (in the case of FIG. 9A). In this case, of course, / AFEN is set even at the end of the integration process.
The D signal does not switch from 0 to 1, and the integration end signal is not output. On the other hand, when the subject brightness becomes higher than this, the / AFEND signal comes to be output normally (in the case of FIG. 7B), but since the integration time is extremely short, the / AFEND signal changes from 1 to 0. Switching and 0 to 1
The switch to may not be recognized normally. When the subject brightness becomes higher and the sensor operation limit is exceeded, / A
Even if the integration is completed while the FEND signal is switched from 1 to 0, it will not be switched to 1 (in the case of (C) in the figure),
In this case also, the integration end signal is not output.

In this way, when the subject brightness exceeds a certain brightness (especially when the integration is executed with high sensitivity (S52)), (a) / AFEND signal does not switch from 1 to 0 as the brightness increases. (b) After the / AFEND signal switches from 1 to 0,
When the / AFEND signal switches from 0 to 1 for a very short time. (c) / AFDEN signal goes from 1 to 0, but then /
When the AFEND signal does not switch from 0 to 1. In some cases, the / AFEND signal may not be output normally.

If the / AFEND signal does not switch from 1 to 0, it exceeds a certain brightness (in this case, /
It is assumed that a connection error of the AFEND signal is also possible), and it is determined by MDATA described later whether or not the brightness has actually exceeded a certain constant level.

Also, after the subject brightness becomes higher than a certain level and the / AFEND signal switches from 1 to 0, the switching of the / AFEND signal from 0 to 1 is very short and the CPU normally operates. Even if the / AFEND signal cannot be recognized, the above / AFE is seen from the CPU side.
Since it recognizes that the ND signal does not switch from 1 to 0,
It is estimated that the brightness exceeds a certain level, and the
From A, it is determined whether the brightness actually exceeds a certain level.

The subject brightness becomes higher and / AFEND
If the signal changes from 1 to 0 and then the / AFEND signal does not switch from 0 to 1, the / AFEND signal changes when the subject brightness is low and the integration ends just within the maximum allowable integration time, and when the brightness is extremely high. It becomes impossible to judge that the state does not switch from 0 to 1 (because the sensor peak (the value of MDATA shown later) is the minimum value).

Therefore, in step S50 of FIG. 14, when the object to be measured is determined to have ultra-high brightness by the photometric sensor, step S52 (high sensitivity integration) of FIG. 14 is not executed and the three-division gain of step S56 is executed. A low integration is performed to prevent the above-mentioned misjudgment.

By the way, due to a circuit defect, / AFEN
It is also assumed that the D signal does not switch from 1 to 0.

Here, in the case of (a) / connection error of AFEND signal only (when integration is normally performed, but integration start and integration end cannot be determined) and (b) circuit integration operation error ( Connection error other than / AFEND signal, V _CC , GND, / AFCEN, / AFRS
It is conceivable that the integration is not performed due to a connection error of either T or AFCLK, and the integration is not performed due to damage of the AF sensor).

In case of connection error of / AFEND signal,
/ AFEND signal does not switch from 1 to 0
The ND signal is not output normally. Therefore, / AFEN
When the D signal does not switch from 1 to 0, not only the case where the subject brightness exceeds the constant brightness as described above is assumed, but also the case where a connection error of the / AFEND signal is assumed. Then, it is determined by MDATA described later whether or not the sensor data satisfies the integration end condition. / AFE
In the case of a connection error of the ND signal, the value of MDATA is not less than MC_JDG in FIG. 26B (almost the initial value (VRE
F)) (the subject brightness is extremely low and almost no signal is accumulated), it is determined that the distance measurement is impossible.

In the case of a connection error of the / AFEND signal, the value of MDATA is MC_JDG in FIG. 26 (B).
If less than (subject luminance is not extremely low and signal accumulation is performed to some extent), distance measurement is continued.

Also, in the case of an integration operation error of the circuit, /
AFEND signal does not switch from 1 to 0, / AFEN
D signal is not output normally. Therefore, / AFEND
When the signal does not switch from 1 to 0, not only the case where the subject brightness exceeds a certain brightness as described above, but also the case where an integration operation error of the circuit is assumed. Then, it is determined by MDATA described later whether or not the sensor data satisfies the integration end condition. In the case of an integration operation error of the circuit, the value of MDATA is almost the initial value (VRE
F) (no integration has been performed). in this case,
Judge that distance measurement is impossible.

On the other hand, when the subject brightness exceeds a certain brightness, the value of MDATA is about 0.
It becomes 6 V (integration is completed), and in this case, distance measurement is continued.

In terms of expression, the case where the signal amount of the sensor data is insufficient due to the low subject brightness is included in the category where the integration process is not normally performed. In addition, it is judged that distance measurement is impossible due to insufficient signal amount when, in fact, there is no change in the peak value of the sensor data from the start of integration processing, or when there is an extremely small change. Since it may be possible to measure the distance in other cases, it is determined that the integration process is normally performed.
It is not judged that distance measurement is impossible.

As described above, if the integration start signal or the integration end signal is not normally output from the / AFEND signal even after the integration time has passed a certain time, it is determined whether the integration processing is normally performed. It will be determined by the MDATA signal. Since the MDATA signal outputs the peak value of the sensor data in the peak selection area as analog data, if the integration process is performed, the / AFEND signal is not normally output as shown in FIG. It is possible to easily determine whether or not the peak value of the sensor data in the peak selection region is normally output from the MDATA signal and the integration process is normally performed.

Specifically, the processing contents of the CPU 60 will be described. After executing the batch gain high integration in step S52 of FIG. 14, the CPU 60 switches the / AFRST signal from 0 to 1 (see time T40 in FIG. 17). , The AF sensor 74 indicates the start of integration before the fixed time (eg, 500 μs) elapses from 1 to 0 of the AFEND signal.
If the switch to is not detected, MDATA
Read the signal. Then, if the value of the MDATA signal has reached the integration end value, 1 to 0 of the / AFEND signal
It was judged that the reason that the changeover to was not detected was that the subject brightness was high brightness (ultra high brightness), and as with the case where the integration time was less than 2 ms, the 3-division gain low integration The process shifts to (see steps S54 and S56 in FIG. 14). On the other hand, when the value of the MDATA signal is greater than or equal to a predetermined value, that is, when the value at the start of integration has not changed at all (in the case of the value of the reference voltage VREF), or a value that can be regarded as equivalent to no change. In this case, the distance cannot be measured as an integration operation error of the circuit. In cases other than the above, the integration process is continued as usual. The subsequent processing has been described in the flowchart of FIG.

At the time of executing the 3-division gain low integration in step S56 of FIG. 14 (step S8 of FIG. 15).
4, S94, S102, S110, and S118), the CPU 60 executes
After the AFRST signal is switched from 0 to 1, the AF sensor 74 does not have to wait a certain time (for example, 500 μs).
When the switching of the / AFEND signal indicating the start of integration from 1 to 0 is not detected, the MDATA signal is read. At this time, the value of the MDATA signal is a predetermined value (see FIG.
6 (B) MC_JDG) or more, that is, when there is no change from the value at the start of integration (the reference voltage VR described above).
In the case of the value of EF) or a value which can be regarded as equivalent to no change at all, distance measurement is impossible for the divided areas forming the peak selection area in the integration processing at that time (integration operation error of the circuit). ). On the other hand, the AF sensor 74 indicates the start of integration by the time the fixed time elapses / A
When the switching of the FEND signal from 1 to 0 is detected, the integration process is continued within the maximum allowable integration time. If the maximum allowable integration time elapses, the AF sensor 74 indicates the end of integration / AFEND signal 0 to 1
When the switch to is not detected, the MDATA signal is read when the maximum allowable integration time is reached. At this time, the value of the MDATA signal is a predetermined value (MC in FIG. 26B).
_JDG) or more, that is, when there is no change from the value at the start of integration (in the case of the value of the reference voltage VREF), or when the value can be regarded as equivalent to no change at all, then The distance measurement is disabled for the divided areas forming the peak selection area in the integration processing (2), and the distance measurement is disabled (the sensor data is invalidated).
In other cases, it is determined that the integration process has been normally performed, the sensor data accumulated in the CPU 60 until then is validated, and the sensor data at that time is read. If the value of the MDATA signal has not reached the integration end value even after the maximum allowable integration time has elapsed, the integration processing is continuing, so the CPU 60 forcibly stops the integration processing of the AF sensor 74. Then (after switching the AFAD signal from 1 to 0), the sensor data is read.

When the collective gain low integration is executed in step S58 of FIG. 14, the CPU 60 operates in the same manner as described above.
If the AF sensor 74 does not detect the switching of the / AFEND signal indicating the end of integration from 0 to 1 within a fixed time (for example, 500 μs) after switching the / AFRST signal from 0 to 1. Reads the MDATA signal. At this time, when the value of the MDATA signal is equal to or greater than a predetermined value, that is, when the value at the start of integration has not changed at all (in the case of the value of the reference voltage VREF), or
If the value is equivalent to no change at all, it is determined that distance measurement is impossible (integral operation error of the circuit). Since the peak selection area is set in the entire distance measuring area in the case of low gain integration in a lump, the distance measurement cannot be performed (the distance measurement itself cannot be performed) in all the divided areas forming the distance measuring area. on the other hand,
When the AF sensor 74 detects the switching of the / AFEND signal indicating the start of integration from 1 to 0 before the fixed time elapses, the integration process is continued within the maximum allowable integration time. If the maximum allowable integration time elapses, the AF sensor 74 indicates the end of integration / AFEN
When the switching of the D signal from 0 to 1 is not detected, the MDATA signal is read when the maximum allowable integration time is reached. At this time, when the value of the MDATA signal is equal to or larger than a predetermined value, that is, when the value at the start of integration does not change at all (in the case of the value of the reference voltage VREF), or a value that can be regarded as no change at all. In the case, the distance cannot be measured because the signal amount of the sensor data is insufficient (the sensor data is invalidated). In other cases, it is determined that the integration process has been normally performed, the sensor data accumulated in the CPU 60 until then is validated, and the sensor data at that time is read. Also in this case, similarly to the above, if the value of the MDATA signal has not reached the integration end value even after the maximum allowable integration time has elapsed, the integration process is continuing, so the CPU 60 forces the AF sensor to operate. After stopping the integration process of 74 (after switching the AFAD signal from 1 to 0), the sensor data is read.

Next, the process of reading sensor data by the CPU 60 will be described. As shown in the timing chart of FIG. 17, for example, when the CPU 60 detects that the / AFEND signal transmitted from the AF sensor 74 is switched from 0 to 1 and the integration is completed, the CPU 60 sends AFCLK to the AF sensor 74. A clock pulse is transmitted by the signal to start reading the sensor data. From the AF sensor 74, the sensor data of each cell is sequentially output as analog data AFDATAP in synchronization with the clock pulse.
The signal is output by the signal, and after the A / D conversion, the CPU 60
Entered in.

More specifically, L is set by the AFDATAP signal.
The sensor data of each cell of the sensor 96 and the R sensor 94 are alternately output in order from the sensor number 1 to the sensor number 234 and read by the A / D conversion circuit of the CPU 60.
Incidentally, after the sensor data of all cells of the L sensor 96 and the R sensor 94 are transmitted, several dummy data are transmitted.

Here, the reading speed of the sensor data by the clock pulse will be described. When a certain peak selection region is set in the AF sensor 74 as described above and the integration process is executed, the AF process is performed by the integration process.
Of the sensor data of each cell accumulated by the sensor 74,
The sensor data actually used by the CPU 60 in the subsequent distance measurement processing is limited to the sensor data of each cell within the range of the peak selection region formed by one or a plurality of divided areas, and the sensor data in each range other than that. No cell sensor data is required. Further, as described above, even within the range of the peak selection area, the peak selection area is set for the AF sensor 74 by a block unit (block numbers D0, D1,
..., D55, block numbers D56, D57, ..., D11
1)), there are actually cells that do not need to acquire sensor data even in the blocks at both ends of the peak selection region. Furthermore,
In the present embodiment, the necessary sensor data is limited to the peak selection area, but depending on the mode of the distance measurement calculation, the sensor data of cells outside the peak selection area may be necessary, not limited to the peak selection area. . Therefore, it is assumed that the range of cells that generate sensor data necessary for the subsequent processing of the CPU 60 is called a data acquisition range, and the range of cells that generate unnecessary sensor data for the subsequent processing of the CPU 60 is called a data non-acquisition range. , The CPU 60 does not output the clock pulse of a constant cycle, but rather than the clock cycle of the period T2 in which the sensor data of the cell of the data acquisition range is conveyed, as shown in FIG. 27, the sensor data of the cell of the data non-acquisition range. The clock cycle of the period T1 for transporting is shortened to shorten the reading time of unnecessary sensor data.

For example, when carrying sensor data of cells in the data acquisition range, the stable period cycle (“H”) of the AFDATAP signal is 16 μs, and the stable period cycle of A / D conversion is 18 μs (“L”). Then, when the sensor data of the cells in the data non-acquisition range is carried, the clock cycle is (“H”) 2 μs and (“L”) 2 μs.
With the clock pulse of (“H”) 16 μs and (“L”) 18 μs period, the value of the sensor data of each cell can be properly acquired by the A / D conversion circuit, but with the clock pulse of 2 μs period, It may not be possible to properly obtain the value of the sensor data of the cell. However, since the sensor data in the data non-acquisition range is unnecessary, the sensor data in the data non-acquisition range is (“H”) 2 μm.
There is no problem in carrying with a clock pulse of s, (“L”) 2 μs period.

Further, as shown in FIG. 27, when the conveyance of all the sensor data in the data acquisition range is completed, the AFCLK signal (clock pulse) is generated even when the conveyance of the sensor data in the non-data acquisition range remains. It is possible to further shorten the reading time of the sensor data by stopping the output of the above and not reading the sensor data in the data non-acquisition range after the data acquisition range.

When the transfer of the sensor data in the data non-acquisition range to the transfer of the sensor data in the data acquisition range is started, the transfer of the sensor data in the data acquisition range is started in consideration of the stability of the clock pulse and the like. The clock cycle from the immediately preceding cell is (“H”) 16 μs, (“L”) 1
It is designed to switch to 8 μs. However, the transition to the clock cycle when the sensor data in the data acquisition range is conveyed is not performed from the cell immediately before the start of the conveyance of the sensor data in the data acquisition range, but the sensor data in the data acquisition range. It may be carried out at the same time as the start of the transportation of the above, or it may be carried out from the cell two or more before.

Next, a process of generating AF data from sensor data will be described. As described above, the AF sensor 7
When the data output from the light receiving cell of No. 4 is sensor data, each sensor data output from the AF sensor 74 is acquired by the A / D conversion circuit, and the A / D conversion value itself of the acquired sensor data is stored in the CPU 60 thereafter. It is considered that the AF data is used in each of the processes, and that the AF data is obtained by subjecting the sensor data to a predetermined process to improve the distance measurement accuracy. CPU6 in the former case
0 does not require special processing for generating AF data, and the sensor data acquisition processing is AF data acquisition processing. In the latter case, the CPU 60 generates AF data after the sensor data acquisition. A special process for doing so will be performed. As an example of the latter case, the sensor data subjected to the contrast extraction processing can be used as AF data used in each subsequent processing. Hereinafter, in the case where the sensor data is subjected to the contrast extraction processing to generate the AF data. The process will be described.

In the contrast extraction processing, for example, when a cell having a certain sensor number (address i) is focused, the sensor data of the focused cell is separated from the focused cell by m cells (m pixels). This is a calculation process for calculating the difference (or ratio) from the sensor data of the cell with the sensor number (i + m). In other words, the R sensor 94 and the L sensor 9
It is a process of calculating the difference between the sensor data and the sensor data shifted by m pixels for each of the sensor data obtained from FIG. That is, the sensor data of the cell with the sensor number (i) in the R sensor 94 is set to R (i), L
If the sensor data of the cell of the sensor number (i) in the sensor 96 is L (i), the sensor data of the R sensor 94 can be expressed by the following equation:

[0147]

[Mathematical formula-see original document] The calculation of R (i) -R (i + m) (9) is performed, and for the sensor data of the L sensor 96, the following equation,

[0148]

[Equation 7] L (i) -L (i + m) (10) is calculated. The difference data obtained thereby indicates the contrast of the sensor image captured by each cell of the AF sensor 74. In this specification, the calculation process for calculating the data indicating the contrast based on the difference between the sensor data for two pixels is referred to as a two-pixel difference calculation.

The value of the cell interval m of the two sensor data for which the difference is taken can be a desired set value, but in the following description, m = 2. However, in the AF sensor 74, the charges accumulated in the cells having even numbers and the charges accumulated in the cells having odd numbers are transmitted and processed by different channels, and thus the difference data is also obtained by the sensors of the cells of the same channel. It is preferable to obtain it from the data,
It is desirable that the value of m be an even number. The above formula
The data obtained by (9) and (10) is reduced by m in comparison with the number of sensor data acquired from the AF sensor 74 by the CPU 60, but the data acquisition range is considered in consideration of the decrease in m in advance. It is possible to secure the necessary number of AF data by enlarging.

Conventionally, the difference data obtained by the above equations (9) and (10) is used as the AF data, but in the present embodiment, the processing of adding +255 to the difference data and 2 AF data is obtained by adding division processing. That is, A corresponding to the sensor number i of the R sensor 94
If F data is AFR (i) and AF data corresponding to the sensor number i of the L sensor 96 is AFL (i), m = 2
If,

[0151]

[Equation 8]   AFR (i) = (255 + R (i-1) -R (i + 1)) / 2 (11)   AFL (i) = (255 + L (i-1) -L (i + 1)) / 2 (12) The value obtained by is used as AF data.

Here, the AF data is simply expressed by the above equations (9) and (10).
Instead of using the difference data obtained by
The reasons (1) and (12) are for suppressing an increase in RAM usage and an increase in calculation time such as correlation value calculation. For example, it is assumed that the sensor data of each cell is obtained as 8-bit data. In this case, the values of the sensor data R (i) and L (i) are in the range of 0 to +255, as shown in FIG.
On the other hand, when the difference data obtained by the above equations (9) and (10) is used as the AF data (this case is called the conventional method), the value of the AF data is −2 as shown in FIG.
It is in the range of 55 to +255 and becomes 9-bit data. Since the RAM is used and operated in byte units, 9-bit data is processed as 16-bit (2 bytes) data.

On the other hand, when the difference data obtained by the above equations (11) and (12) is used as the AF data (this case is called the new method), the value of the AF data is as shown in FIG. 28C. Is in the range of 0 to +255, and is 8-bit data.
Therefore, in the use and calculation of the RAM, it is processed as 1-byte data. FIG. 29 (A),
In (B), the values of the AF data generated by the new method and the values of the AF data generated by the conventional method based on the same sensor data are illustrated.

By generating AF data so that it has the same number of bits as the sensor data as in the new method, the RAM usage amount is reduced and the processing time in each process such as correlation value calculation is reduced. To do. The above equation (1
In the new method by 1) and 12), the difference calculation result of the conventional method by the above equations (9) and (10) is halved. I'm sure it's not there.

Next, the specific processing contents when the AF data is generated by the new method will be described. Traditionally,
When the sensor data of each cell in the distance measuring area is read from the AF sensor, the read sensor data is stored in the RAM as it is. Then, when a process such as correlation value calculation using the AF data (image) is started, the AF data (image) is read from the RAM during the execution of the process, and Necessary difference data is sequentially generated by calculation. For example, in the correlation value calculation process using AF data (image), as shown in FIG. 12, each shift amount n (the number of adopted sensors 62, 62 When the window size is 42, n = -2,
The correlation value is calculated for each (-1, 0, 1, ..., MAX (= 38)) from the AF data (image) in each window range. Therefore, the AF data (image) of the same cell is repeatedly used, and each time the AF data (image) becomes R
The difference data is read from the AM and the difference data is generated by the 2-pixel difference calculation. In this way, each shift amount n (n = -2, -1, 0, 1, ..., MAX (= 3
FIG. 30 shows the processing procedure of the correlation value calculation for each of 8)). First, the sensor data L (i + 1) and L (i-1) are read from the RAM with i = 1 (steps S600 and S60).
2). In addition, i shown here is the R window 94B,
The cell position i in the L window 96B is shown. Then, the difference data AFL (i) = (255
+ L (i-1) -L (i + 1)) / 2 is calculated (step S604). Similarly, sensor data R (i +
1) and R (i-1) are read (steps S606 and S6).
08). Then, according to the above equation (11), the difference data AFR
(i) = (255 + R (i−1) −R (i + 1)) / 2 is calculated (step S610). Next, if | L (i) -R (i) | on the right side in the above equation (1) for obtaining the correlation value f (n) is set to f (ni), AFL (i)> AFR (i) It is determined (step S612). If YES is determined, f (n
i) = L (i) -R (i) (step S614), and if NO is determined, f (ni) = R (i) -L (i) is set (step S616). Then, f (ni) is added to the value (initial value 0) of the left side f (n) of the above equation (1) to make that value a new value of f (n). That is, f (n) = f (n) + f (ni) is set (step S618).

Next, i = (window size wo (= 42))
Is determined (step S620), YES
If it is determined that this processing is completed (step S6)
22). On the other hand, if NO is determined, i = i + 1 is set (step S624), the process returns to step S600, and the process is repeated from step S600. The above is the calculation for each shift amount n, and each shift amount n
The calculation process is repeated from i = 1 to i = wo every (n = −2 to 38).

As described above, when the difference data is generated when the correlation value calculation process using the AF data (image) is performed, the AF data (image) of the same cell is repeatedly used as shown in FIG. Then, it is necessary to perform the 2-pixel difference calculation. Therefore, the calculation takes time,
As a result, the problem that the time required for the distance measurement calculation becomes long occurs.

In order to solve the above problem, in the present embodiment, AF processing is performed in advance before starting the processing using the difference data.
Data (difference) is generated and the generated AF data (difference) is stored in the RAM. Figure 31
The processing procedure of the correlation value calculation when the AF data (difference) is previously generated and stored in the RAM before the execution of the correlation value calculation is shown in FIG. First, from i RAM to AF
The data (difference) AFL (i) and AFR (i) are read (steps S650 and S652). Note that i shown here indicates a cell position i in the R window 94B and the L window 96B. Next, if | L (i) -R (i) | on the right side in the above equation (1) for obtaining the correlation value f (n) is set to f (ni), AFL (i)> AFR (i) It is determined whether or not (step S654). If YES is determined, f (ni) = L (i)
-R (i) (step S656), and if NO is determined, f (ni) = R (i) -L (i) is set (step S65).
8). Then, f (ni) is added to the value (initial value 0) of the left side f (n) of the above equation (1) to make that value a new value of f (n). That is, f (n) = f (n) + f (ni) is set (step S6).
60).

Next, i = (window size wo (= 42))
Is determined (step S662), YES
If it is determined that this processing is completed (step S6)
64). On the other hand, if NO is determined, i = i + 1 is set (step S666), the process returns to step S650, and the process is repeated from step S650.

By thus generating the AF data (difference) in advance and storing it in the RAM, the necessary AF data (difference) is read from the RAM when each process using the AF data (difference) is executed. This is sufficient, and the time required for the processing for generating the difference data is significantly reduced. Comparing the processing times in the correlation value calculation shown in FIG. 30 and FIG. 31, in the processing of FIG. 31, the correlation for the time required for the processing of steps S602 and S604 of FIG. The time required for value calculation can be shortened. When the number of adopted sensors is 62 and the window size is 42, and there are 5 areas, the number of calculations of i is (i = 1 to 42 → 42 times) × (n = −
2 to 38 → 41 times) × 5 area = 42 × 41 × 5 = 86
10 times. Therefore, the total distance measurement time is 8610 times ×
(2 × 21 μs) ≈362 ms can be shortened.
When the AF data (difference) is generated in advance and stored in the RAM, the AF data (difference) is calculated from the sensor data.
The processing time required to generate the above is required separately from the time for calculating the correlation value, which will be described later.

There are two possible modes for carrying out the two-pixel difference calculation. In the first mode, the sensor data read from the AF sensor 74 is temporarily stored in the RAM (AF data (image)), and then,
The AF data (image) is read from the RAM, the difference data is generated by the above equations (11) and (12), and the 2-pixel difference calculation is performed. The second mode is the AF sensor 74.
When the sensor data is sequentially read from the sensor data of each sensor number i, when the sensor data necessary for the calculation of the above formulas (11) and (12) is obtained, the difference calculation (1
Perform 1) and 12), and sequentially generate the difference calculation results in RAM
(AF data (difference)).
Since the sensor data reading process in the first aspect is performed independently of the difference data generating process, the AF data (image) is obtained when the two-pixel difference calculation is not performed or when each process such as the correlation value calculation is performed. This is the same as the process of reading the sensor data when the is generated. On the other hand, in the process of reading the sensor data of the second aspect, since the two-pixel difference calculation is performed while reading the sensor data, the time required to read the sensor data becomes longer accordingly. However, considering that the two-pixel difference calculation is performed also in the first mode, the first mode is not advantageous over the second mode.

Here, when the difference data is generated at the time of executing the correlation value calculation or the like (hereinafter, this case is referred to as the conventional method).
32 shows the data flow of FIG. 32. The data of the case where the second mode is adopted as a case where AF data (difference) is generated in advance and stored in the RAM (hereinafter, this case is referred to as a new method) The flow is shown in FIG. As shown in FIG. 32, in the conventional method, the sensor data of each cell sequentially read from the AF sensor is stored in the RAM. Then, when the correlation value calculation is executed, the AF data (image) is read from the RAM, the difference data is generated by the above equation (11) or (12), and the correlation value f (n) is calculated. On the other hand, as shown in FIG. 33, in the second mode of the new method, the sensor data of each cell sequentially read from the AF sensor is subjected to the difference calculation processing according to the above formula (11) or (12) and the AF data ( R) as difference
Stored in AM. When performing the correlation value calculation, R
The AF data (difference) stored in the AM is read out and the correlation value f (n) is calculated. Although not shown in the figure, when the sensor data is converted into the AF data (difference) by the above formula (11) or (12) in the new method, two sensor data are required, so that two sensor data are read out. A until
A memory (RAM) for holding the sensor data previously read from the F sensor is required. However, it does not require a memory capacity for storing all sensor data. Specifically, the sensor data is L (i-1), R (i
-1), L (i), R (i), L (i + 1), R (i + 1), ...
Therefore, when the cell interval m of the two sensor data is 2, R which stores the five sensor data is read.
AM is enough. For example, L (i-1), R (i
−1), L (i), R (i), and L (i + 1) are stored, the AFL (i) of the above formula (12) is stored in the RAM as L (i
-1), L (i + 1). And
When the AFL (i) is obtained, the sensor data of L (i-1) is no longer necessary, so that data is erased, and then the sensor data R (i +) read from the AF sensor 74 is read.
By storing 1) at the erased address,
AFR (i) in the above equation (11) can be calculated from R (i-1) and R (i + 1). In this way, the five sensor data read from the AF sensor 74 are stored in the RAM, and when the new sensor data is read, the sensor data read out first among the sensor data stored in the RAM is stored. Erase and RA the new sensor data
By storing in M, the AF data (difference) can be sequentially created in the RAM having a small memory capacity.

Next, regarding the process of reading the sensor data, the case where the conventional method is adopted and the case where the second mode is adopted as the new method are compared. FIG. 34 is a flowchart showing a process of reading sensor data in the conventional method, and FIG. 35 is a diagram showing the AFCLK signal and AFDATA when reading the sensor data in the conventional system.
6 is a timing chart showing a P signal. The sensor data read processing in the conventional method will be described with reference to these drawings. First, the AFCLK signal is switched from “H” to “L” (step S700), and the AFDATAP signal indicating the sensor data is A / D converted. (Step S702). Then, the AFCLK signal is switched from "L" to "H" (step S704), and the sensor data R (i) or L (i) acquired by the A / D conversion is stored in the RAM (step S706). The above process is repeated. The periods of “H” and “L” of the AFCLK signal are 16 μs and 18 μs, respectively.

On the other hand, FIG. 36 is a flow chart of sensor data read processing in the new method (second mode), and FIG. 37 is a diagram showing the AFCLK signal and the AFDATAP signal when the sensor data is read in the new method. Is. The process of reading the sensor data in the new method will be described with reference to these figures. First, AFCL
The K signal is switched from "H" to "L" (step S75
0), A / D signal AFDATAP indicating sensor data
It is converted (step S752). Then, the AFCLK signal is switched from "L" to "H" (step S75).
4) The sensor data R (i) or L (i) acquired by the A / D conversion is stored in the RAM (step S756). Next, the sensor data R (i-2) or L (i-2) is read from the RAM (step S6-5), and AF data (difference) AFR (i-1) or AFL (i-
1) is calculated (step S760), and the calculated AF data (difference) AFR (i-1) or AFL (i-) is calculated.
1) is stored in the RAM (step S762). The above process is repeated.

As can be seen from the sensor data read processing procedures of the above new method and conventional method, in the new method, step S7 is performed.
It takes more time to read one sensor data than the conventional method by the operation time of 58, S760, and S762 (21 μs). Note that the processes of steps S758, S760, and S762 are performed when the AFCLK signal is "H".
As shown in FIG. 37, the period of "H" of the AFCLK signal is longer than that of the conventional method, and the reading time of the sensor data is longer.
It is μs. That is, considering only the reading time of sensor data, the new method is more disadvantageous than the conventional method. However, when the time for reading the sensor data and the time for the entire process including, for example, the correlation value calculation are compared, the new method can complete the process in a shorter time. An example of concrete calculation is shown in the table of FIG. In the table, in each of the new method, the conventional method, and the case where the two-pixel difference calculation is not performed (conventional method) for reference, the sensor data read time, the correlation value calculation time per time, the correlation value total calculation time ( 41 times, 5 areas set), total (sensor data read time + correlation value total calculation time) are shown.
The difference Δ between the new method and the conventional method and the difference Δ between the new method and the conventional method are shown.

The reading time of the sensor data is {AFCL
K signal (“H” time + “L” time)} × number of cells ×
2 (R sensor 94 and L sensor 96). In the case of the new method, the 2-pixel difference calculation cannot be performed in the sensor data reading period for the first 5 cells.
(Reading time of sensor data for cells) + (reading time of sensor data for remaining cells by the new method). Applying the numerical values used in the above explanation, (16 + 18) ×
5+ (37 + 18) × ((229-6 + 1) × 2-5)
= 24535 μs.

On the other hand, as the correlation value calculation time per time, the measured value is used in the case of the new method, and the measured value + calculation time increment is used in the case of the conventional method. The calculation time increment is set to 21 μs × 2 as shown in FIG.
In addition, the correlation value calculation time per time in the conventional method is 1.2
× 0.021 × 2 × 42 = 2.964 ms.

As can be seen from this table, in the new method, the read time of all sensor data is about 9 ms longer than in the conventional method. However, regarding the correlation value calculation, the new method shortens the processing time by about 361 ms as compared with the conventional method, so if the time required for other determination processing is the same, the new method also shortens the distance measurement time by 352 ms. Will be.

As described above, when the sensor data is subjected to the required processing to generate the AF data, the AF data is generated by the C
Although it is performed in the PU 60, it is not always the CPU 6
It is not necessary to perform the processing in 0, and the AF sensor 74 performs necessary processing on the sensor data to generate AF data,
The generated AF data may be given to the CPU 60. In addition, the correlation value calculation processing described later
Instead of U60, the AF sensor 74 may be used and the distance signal obtained as a result may be given to the CPU 60. {Details of Correlation Value Calculation Process (Step S16 in FIG. 7)} Next, the correlation value calculation process in step S16 in FIG. 7 will be described in detail. In the correlation value calculation processing as described above with reference to FIG.
Based on the AF data acquired by the AF data acquisition processing in step S14 of FIG. 7, the above formula (1) is calculated for each divided area forming the distance measurement areas of the sensor 94 and the L sensor 96.
Correlation value f (n) (n = -2, -1, 0, 1, ..., MAX
(= 38)) is calculated. Then, based on the calculated correlation value f (n), the shift amount n having the highest correlation is detected for each divided area. Note that the correlation value calculation process is not performed for the divided areas determined to have no contrast necessary for distance measurement in the contrast detection process 1 of step S14.

Here, the CPU 60 makes a determination of f (n-1) ≧ f (n) <f (n + 1) in order to obtain the minimum value, and as the shift amount with the highest correlation (highest correlation), The shift amount n at which the correlation value f (n) becomes the minimum minimum value is detected. In many cases, the minimum value of the correlation value is one, and the shift amount of the highest correlation is the shift amount n at which the minimum value is obtained.

On the other hand, the distribution of correlation values f (n) (f (n-1) ≧
f (n) <f (n + 1)), there may be a plurality of local minimum values. In that case, the shift amount of the highest correlation is, in principle, the smallest local minimum value (minimum local minimum value among the plurality of local minimum values. The shift amount n is the minimum value). However, when there are a plurality of local minimum values, there is a possibility of incorrect distance measurement. Therefore, in the local minimum value determination process described below, the minimum minimum value shift amount n should be adopted as the maximum correlation shift amount. To determine whether is appropriate. The minimum value fmin1 (or the minimum minimum value f (nmin1) is the minimum value and the shift amount when there is one minimum value, or the minimum minimum value and the shift amount when there are multiple minimum values. )
And the shift amount nmin1.

Next, the minimum value judgment processing will be described.
When there are two or more minimum values of the correlation value f (n) in a certain divided area, the CPU 60 causes the minimum minimum value fmin1.
And the second smallest local minimum value (referred to as the second local minimum value) are detected, and their difference (local minimum value difference) is obtained. The second minimum value is fmin2, and the minimum value difference is Δfmin (= fmin2-
It is represented by fmin1). As the outline of the process of the minimum value judgment,
When the minimum difference Δfmin is large, the shift amount nmin1 of the minimum minimum value fmin1 is adopted as the shift amount n of the highest correlation. On the other hand, when the minimum value difference Δfmin is small, there is a high possibility that erroneous distance measurement will occur, and distance measurement is impossible. In the following, the shift amount of the highest correlation is nmin and the correlation value at the highest correlation (highest correlation value) is fmin or f (n
min).

By the way, when there are a plurality of local minimum values of the correlation value f (n), it is judged whether the distance measurement is possible or not possible. In consideration of the following aspects, it is impossible to measure the distance more than necessary, or the possibility of erroneous distance measurement increases. That is, even if the minimum value difference Δfmin is small to some extent, distance measurement should be possible, and the minimum value difference Δfmin.
There are cases where distance measurement should be impossible even if min is large to some extent.

For example, the former case is shown in FIG. 39, and the latter case is shown in FIG. FIG. 39 (A),
(B) shows an example of AF data obtained from each cell in the central area of each R sensor 94 and L sensor 96 of the AF sensor 74. As shown in FIG. It is assumed that the obtained AF data has low contrast. In the following description, the divided area or its sensor (each cell) which is focused on in the description among the divided areas (each divided area forming the distance measuring area) in which the same processing is performed is referred to as an adopted sensor. . In such a case, the correlation value f (n) calculated by the correlation value calculation
Is a small value as a whole (compared with FIG. 40 described later) as shown in FIG. Further, in FIG. 7C, the minimum minimum value fmin1 is detected when the shift amount n = 8, and the second minimum value fm is detected when the shift amount n = 18.
Although in2 is detected, the minimum difference Δfmi between them is
n is also smaller than in the case of FIG. 40 described later. However, in the case of the embodiment of FIG. 39, the shift amount nmin1 (= 8) of the minimum minimum value fmin1 is a value that appropriately corresponds to the subject distance, and it should be determined that distance measurement is possible.

On the other hand, FIGS. 40A and 40B show an example in which AF data obtained from the adopted sensors (central area) of the R sensor 94 and the L sensor 96 changes periodically. Such AF data can be obtained, for example,
This is the case where an image of a striped object is captured. In this case, the correlation value f (n) calculated by the correlation value calculation is also shown in FIG.
, It changes periodically, and becomes a large value as a whole (by comparison with FIG. 39 described above). Further, as shown in the enlarged view of FIG. 7D, the minimum minimum value fmin1 is detected at the shift amount n = 14, and the second minimum value fmin2 is detected at the shift amount n = 20. The minimum value difference Δfmin is also larger than that in the case of FIG. 39 described above. However, in the case of the embodiment of FIG. 40, there is a high possibility that the shift amount nmin1 (= 14) of the minimum minimum value fmin1 does not properly correspond to the subject distance, and thus this adopted sensor should be unable to perform distance measurement. .

The CPU 60 concretely performs the following determination processing in order to appropriately determine whether the distance measurement should be possible as shown in FIG. 39 and the distance measurement be impossible as shown in FIG. ..

First, among the minimum values detected in the distribution of the correlation value f (n) of the adopted sensor, the minimum minimum value fmin.
1 and the second minimum value fmin2 are detected. And the following equation,

[0178]

## EQU9 ## It is determined whether fmin1 <reference value R3 (13) holds. This judgment is a judgment for separating the cases of FIG. 39 and FIG. 40, and the reference value R3 is set to an appropriate value for separating these cases. If the equation (13) is satisfied, that is, in the case of FIG. 39, then the minimum value difference Δfmin (= fmin2-fmin1).
And the following equation,

[0179]

[Equation 10] It is determined whether or not Δfmin <reference value R2 (14) holds. The reference value R2 is set to a value that is at least smaller than a reference value R1 described later in consideration of the case of FIG. If equation (14) holds,
Assuming that the minimum difference Δfmin is small, the distance measurement cannot be performed for this adopted sensor. When Expression (14) is not satisfied, distance measurement is possible and the shift amount n of the minimum minimum value fmin1 is n.
min1 is adopted as the shift amount nmin of the highest correlation value fmin.

On the other hand, when the above equation (13) does not hold, that is, in the case of FIG. 40, the following equation,

[0181]

[Equation 11] It is determined whether or not Δfmin <reference value R1 (15) holds. The reference value R1 is set to a value at least larger than the reference value R2 in consideration of the case of FIG. If the formula (15) is satisfied, FIG.
It is judged that there is a high possibility that the subject is a striped pattern or the like, and the distance measurement by this adopted sensor is disabled. If equation (15) does not hold, distance measurement is possible and the minimum minimum value fmin
The shift amount nmin1 of 1 is adopted as the shift amount nmin of the highest correlation value fmin.

By performing the minimum value determination processing as described above, the frequency of occurrence of defects such as erroneous distance measurement is reduced.

Next, a plurality of other modes for shortening the distance measuring time in the correlation value calculation processing will be described. First, a first embodiment for reducing the distance measurement time will be described. In the description of step S16 in FIG. 7 (see formula (1)), the correlation value f (n) (n = −2, −1, 0, 1, ..., MAX)
(= 38)) is R window 94B and L window 96B
The absolute value of the difference in AF data at the same cell position i (i = 1, 2, ... Wo (= 42)) (hereinafter, simply referred to as AF data difference) is added for all cell positions i. In the first embodiment, when obtaining the correlation value f (n) of each shift amount n, the cell positions i are set at regular intervals instead of adding the differences of the AF data for all the cell positions i. It shall be added. For example, the difference of AF data is added for every third cell position i.
In addition, in the following description, a cell to be calculated for adding the difference of AF data in the calculation of the correlation value f (n) is referred to as an adopted cell. Further, the correlation value calculation when the cells at every third cell position i are adopted cells is hereinafter referred to as “i every third calculation”.
Hereinafter, the correlation value calculation in the case where the cell of (1) is set as the adopted cell is referred to as "normal calculation".

FIG. 41 is a diagram showing cell positions i of adopted cells in the R window 94B and the L window 96B in every third i operation. As shown in the figure, in every third i operation, the R window 94B and the L window 96
In B, every third cell position i (=
, 1, 5, 9, 13, ...) are adopted as adopted cells. When the window size is 42 (when wo = 42)
The final cell position i of the adopted cell is 41. The calculation formula of the correlation value f (n) in this case is the same as the above formula (1).

[0185]

[Equation 12] , I is i = 1, 5, 9, 13, 17,
It is taken every third, such as 21,25,29,33,37,41. It should be noted that the cell positions i of the adopted cells may not be at every third cell position, and may not be from the cell position i = 1. Also, in the above equation (16), a factor that is four times that of the above equation (1) is added, but in the operation of every three i's, the number of data is 1/4 of that of the ordinary operation, and therefore, the normal operation and the numerical value are It is because I have combined.

Here, A obtained in each cell of the adopted sensor
42 and 43 show examples of calculation results when the correlation value f (n) is obtained by the normal calculation and the i-third operation based on the F data. As you can see from these figures,
The outline of the distribution of the correlation value f (n) is not much different from the normal calculation even in the case of every three i's operations, and in this example, the shift amount n (= 10) is the same as the normal operation in the case of every three i'th operations. The minimum minimum value is obtained.

When the CPU 60 calculates the correlation value f (n) for each shift amount n by every third i calculation as described above, the correlation value f (n) becomes the minimum value as in the case of the normal calculation. The shift amount n is detected. At this time, FIG.
As can be seen from FIG. 43, the correlation value f (n) calculated by every three i's has a larger variation and a lower accuracy than the correlation value f (n) calculated by the normal calculation. Therefore, the position of the minimum value in every third i calculation may be different from the position of the minimum value in the normal calculation. Therefore, if i3 is calculated every three times,
If the detected minimum value is one, the minimum value is set as the temporary minimum minimum value, and if the detected minimum values are multiple, the minimum minimum value is set as the temporary minimum minimum value, and the temporary minimum minimum value is set. The correlation value f (n) is calculated again by the normal calculation in the vicinity of the shift amount. When there are a plurality of detected minimum values and the difference between the second smallest local minimum value (temporary second local minimum value) and the temporary minimum local minimum value is small, near the shift amount of the temporary second local minimum value. Also calculates the correlation value f (n) by a normal calculation. Details of this case will be described later. Further, hereinafter, the provisional minimum minimum value is Tfmin1,
The shift amount at that time is represented by Tnmin1. The range in which the correlation value f (n) is recalculated by normal calculation is called the recalculation range.

The CPU 60 calculates the shift amount T by the normal calculation.
When the correlation value f (n) in the recalculation range near nmin1 is recalculated, the minimum value of the correlation value f (n) in the recalculation range and its shift amount are calculated by the normal calculation.
Detect based on (n). The minimum value and shift amount detected by this recalculation are detected when all the correlation values f (n) in the adopted sensors are calculated by normal calculation, except when it is determined that distance measurement is impossible (described later). The minimum minimum value fmin1 and the shift amount nmin1 correspond to the minimum minimum value fmin1 and the shift amount nmin, respectively.
Expressed as 1. In addition, when emphasizing what is detected by the recalculation, it is referred to as the recalculation minimum minimum value fmin1. Recalculation minimum local minimum value fmin1 detected by this recalculation processing
The shift amount nmin1 is the maximum correlation value fmin to be detected by the correlation value calculation process and the shift amount nmin, except when it is determined that distance measurement is impossible.

The recalculation range is, for example, the provisional minimum minimum value T
fmin1 is ± with respect to the obtained shift amount Tnmin1
The range of shift amount is 5. For example, in the case of FIG. 43, the shift amount Tnmi for which the provisional minimum minimum value Tfmin1 is obtained
Since n1 is 10, the recalculation range is the shift amount n = 5 to 15 as shown in FIG. When the recalculation is performed in this recalculation range, the same correlation value f (n) as in FIG. 42 is calculated in the recalculation range as shown in FIG. nmin1
Is detected by recalculation. In this example, the shift amount Tnmin1 of the provisional minimum minimum value Tfmin1 and the shift amount nmin1 of the recalculation minimum minimum value fmin1 match.

Here, when the shift amount Tnmin1 of the provisional minimum minimum value Tfmin1 detected by the operation of every three i's is within the short-distance warning range as shown in FIG. 45, the recalculation by the above-mentioned normal operation is not performed. , Tnmin1 = n
A short-distance warning is given as min1. The short-distance warning range is a short-distance range in which focusing cannot be performed in autofocus, and the above recalculation is performed only when the shift amount Tnmin1 of the provisional minimum local minimum value Tfmin1 is outside the short-distance warning range.

The CPU 60 uses the correlation value f (n) calculated by recalculation as described above to calculate the minimum recalculation minimum value fmin.
When the shift amount nmin1 of 1 is detected, the shift amount n
min1 is compared with the shift amount Tnmin1 of the provisional minimum minimum value Tfmin1 detected by the operation of every third i. Usually, these shift amounts match, but in some cases, they may not match. In this case, step S in FIG.
Since the correlation value f (n) (correlation value obtained by normal calculation) in the range required in the subsequent processing such as the interpolation value calculation processing of 22 is insufficient, the correlation value f (n) of the insufficient shift amount n Perform additional recalculation. That is, the recalculation minimum minimum value fmin
Shift amount of 1 nmin1 (shift amount of highest correlation nmi
n), at least a constant shift amount range (for example,
It is necessary to calculate the correlation value f (n) by the normal calculation within a range of ± 5), and the shift amount Tnmin1 of the temporary minimum minimum value Tfmin1 and the shift amount nmin1 of the recalculation minimum minimum value fmin1 do not match. In this case, the correlation value f (n) in the necessary shift amount range is insufficient with respect to the shift amount nmin1 of the recalculation minimum minimum value fmin1. In the present embodiment, the shift amount nmin of the recalculation minimum minimum value fmin1
The shift amount range in which the correlation value f (n) by the normal calculation is required for 1 is the same range as the recalculation range (range of ± 5).

Therefore, of the shift amount range necessary for the shift amount nmin1 of the recalculation minimum minimum value fmin1,
For shift amounts outside the recalculation range in which the correlation value f (n) has already been calculated by the normal calculation, the correlation value f by the normal calculation
Perform recalculation of (n) additionally. However, the provisional minimum minimum value Tf
Shift amount Tnmin1 of min1 and recalculation minimum minimum value f
Difference from the shift amount nmin1 of min1 (shift amount difference nS
When A) is equal to or larger than a predetermined value (for example, 3), there is a high possibility that the recalculation minimum local minimum value fmin1 is not the minimum local minimum value that should be originally detected, so that distance measurement is impossible. It should be noted that the case where the local minimum value is not detected as a result of the recalculation corresponds to this case and the distance measurement is impossible. Also, the correlation value f (n) for the shortage
The process for recalculating is referred to as the insufficient correlation value recalculation process, the details of which will be described later.

Next, there are a plurality of local minimum values in the correlation value f (n) obtained by calculating every third i, and the minimum local minimum value (temporary minimum local minimum value Tfmin1) and the second local minimum value (temporary second local minimum value) among them. ) Will be described when the difference is small. For example, all shift amounts n (n = -2) in the adopted sensor.
When the correlation value f (n) is calculated by a normal calculation for ~ (MAX (= 38)), there are a plurality of local minimum values as shown in FIG.
The shift amount nmin1 of the minimum minimum value fmin1 is detected with the shift amount n = 7, and the shift amount n of the second minimum value fmin2 is detected.
It is assumed that min2 is detected with the shift amount n = 32.
Then, when the correlation value f (n) is calculated for such AF data by calculating every third i, it is assumed that the correlation value distribution as shown in FIG. 47 is obtained. In this case, the CPU 60
First detects the minimum minimum value and the second minimum value in the distribution of the correlation value f (n) calculated by every third i calculation as shown in FIG. As described above, the minimum minimum value in every three i's is represented by the temporary minimum minimum value Tfmin1, the shift amount is represented by Tnmin1, the second minimum value is represented by the temporary second minimum value Tfmin2, and the shift amount is represented by Tnmin2.
Further, in FIG. 47, the shift amount Tnmin1 of the provisional minimum minimum value Tfmin1 is 32, and the provisional second minimum value Tfmin2.
The shift amount Tnmin2 of is detected at 6.

If i3 is calculated every third, the temporary minimum minimum value Tfmin1 and the temporary second minimum value Tfmin are detected.
2 (minimum value difference ΔTfmin = Tfmin2-Tf
If min1) is greater than or equal to the predetermined reference value, the CPU 60 performs recalculation (normal calculation) only within the recalculation range for the shift amount Tnmin1 of the provisional minimum minimum value Tfmin1 as described above. On the other hand, when the minimum value difference ΔTfmin is smaller than the reference value, the provisional minimum minimum value Tfmin1
The recalculation is performed for the recalculation range for the shift amount Tnmin1 and the recalculation range for the shift amount Tnmin2 of the provisional second minimum value Tfmin2. However, the minimum value difference ΔTfm
When in is smaller than the above reference value, the shift amount Tnmin1 of the provisional minimum local minimum value Tfmin1 and the provisional second value
If both of the minimum values Tfmin2 and the shift amount Tnmin2 are within the short-distance warning range, the short-distance warning is issued without recalculation. If either one is not within the short-range warning range, recalculation is performed in the vicinity of both shift amounts as described above.

FIG. 48 shows the minimum value difference ΔTf in FIG.
It is a figure showing the result of recalculation when it is judged that min is smaller than the above-mentioned standard value. As shown in the figure, the shift amount Tnmin1 of the provisional minimum minimum value Tfmin1
A shift amount range of ± 5 with respect to (= 32) (shift amount n =
27 to 37) are recalculated as the recalculation range, and the correlation value f (n) by the normal calculation is calculated in the recalculation range. In addition, the shift amount Tn of the provisional second minimum value Tfmin2
A shift amount range (shift amounts n = 1 to 11) of ± 5 is recalculated for min2 (= 6) as a recalculation range, and the correlation value f (n) is calculated by the normal calculation in the recalculation range. It Correlation value f recalculated in these recalculation ranges
(n) is equal to the value of the correlation value f (n) in the corresponding shift amount range of FIG.

When the CPU 60 recalculates in the vicinity of the shift amount Tnmin1 of the provisional minimum minimum value Tfmin1 and in the vicinity of the shift amount Tnmin2 of the provisional second minimum value Tfmin2 in this manner, the recalculation (normal calculation) is performed in the recalculation range. ), The minimum value and its shift amount are detected based on the correlation value f (n). The minimum minimum value and the second minimum value detected by this are respectively recalculated minimum minimum value fmin1,
Recalculation is represented by the second minimum value fmin2, and those shift amounts are represented by shift amount fmin1 and shift amount fmin2, respectively. Recalculation minimum minimum value fmin1 and its shift amount f
min1, recalculation second minimum value fmin2, and shift amount nmin2 thereof are determined to be distance-measuring impossible (described later).
Except for the above, the above-mentioned minimum minimum value f detected when all the correlation values f (n) in the adopted sensors are obtained by normal calculation.
min1 and its shift amount nmin1 and the second minimum value f
min2 and its shift amount nmin2, and the shift amount nmin1 of the minimum minimum value fmin1 is the shift amount nmi of the highest correlation value fmin to be detected by the correlation value calculation processing.
n.

Next, in the case where there are a plurality of temporary minimum local minimum values, the shift amount Tnmin1 of the temporary minimum local minimum value Tfmin1 detected by the operation of every three i and the shift amount of the recalculated minimum local minimum value fmin1 detected by the recalculation. n
A case where min1 does not match will be described. In this case, the recalculation minimum local minimum value fmin1 is the same as described above.
For the shift amount nmin1 of, the correlation value f (n) by the normal calculation is required at least within a certain shift amount range (for example, ± 5 range), and thus the recalculation of the insufficient correlation value f (n) is performed. (Normal operation) is additionally performed.

When the shift amount difference nSA is greater than or equal to a predetermined reference value, distance measurement is impossible. In this case, the shift amount difference nSA is the shift amount nm of the recalculation minimum minimum value fmin1.
in1 is the shift amount Tnm of the provisional minimum minimum value Tfmin1
If it is detected due to the recalculation of in1, it is appropriate to use the shift amount difference between them. When it is detected due to the recalculation of Tnmin2, it is appropriate to use the shift amount difference between the shift amount Tnmin2 of the provisional second minimum value Tfmin2 and the shift amount nmin1 of the minimum recalculation minimum value fmin1.

Therefore, the shift amount difference DIS1 (= | Tnm between the shift amount Tnmin1 of the provisional minimum minimum value Tfmin1 and the shift amount nmin1 of the recalculated minimum minimum value fmin1.
in1-nmin1 |) and the temporary minimum minimum value Tfmin
2 shift amount Tnmin2 and recalculation minimum minimum value fmin
The shift amount difference DIS2 (= |
Tnmin2-nmin1 |) is obtained, and the smaller value is used as the shift amount difference nSA to determine whether or not distance measurement is possible based on the shift amount difference nSA.

In the case shown in FIG. 48, the recalculation minimum minimum value f
Since the shift amount nmin1 of min1 is 7, the shift amount difference DIS1 has a value of 1 shown in the figure and the shift amount difference DIS2 has 25 shown in the figure. Therefore, whether or not distance measurement is possible is determined by the magnitude of the shift amount difference DIS1.

FIG. 49 is a flow chart showing the processing procedure of the shortage recalculation processing. Before executing the shortage recalculation processing, the CPU 60 calculates the correlation value f (n) by calculating every third i, and detects the shift amount Tnmin1 of the provisional minimum local minimum value Tfmin1. If the provisional second minimum value Tfmin2 is present other than the provisional minimum / minimum pole Tfmin1, the shift amount Tnmin2 is detected. Then, recalculation by normal calculation is performed in the recalculation range, and the shift amount nmin1 of the recalculation minimum minimum value fmin1 is detected in the recalculation range.

Subsequently, the process proceeds to the shortage recalculation process of FIG. First, the shift amount Tn of the provisional second minimum value Tfmin2
Whether or not min2 exists, that is, the temporary second minimum value Tf
It is determined whether or not min2 exists (step S15).
0). If NO, the process proceeds to step S168 described below. On the other hand, if YES, then the temporary second minimum value Tf
It is determined whether or not recalculation is performed with the range of the shift amount n of ± 5 for the shift amount Tnmin2 of min2 as the recalculation range (step S152). If NO is determined, the process proceeds to step S168 described below. On the other hand, if YES is determined, (shift amount nmin1
It is determined whether ≧ shift amount Tnmin1) (step S154). If YES, the temporary minimum minimum value Tfmi
The value DIS1 indicating the magnitude of the shift amount difference between n1 and the minimum recalculation minimum value fmin1 is set to (DIS1 = nmin1-Tn
min1) (step S156), if NO,
The shift amount difference DIS1 is (DIS1 = Tnmin1-nm
in1) (step S158).

Next, the CPU 60 (shift amount nmin
It is determined whether or not 1 ≧ shift amount Tnmin2) (step S160). If YES, the temporary second minimum value Tfm
The value DIS2 indicating the magnitude of the shift amount difference between in2 and the minimum recalculation minimum value fmin1 is set to (DIS1 = nmin1-T
nmin2) (step S162). If NO, the shift amount difference DIS2 is (DIS2 = Tnmin2-
nmin1) (step S164).

Next, it is determined whether or not (DIS1≤DIS2) (step S166), YES, that is, the recalculated minimum minimum value fmin1 is closer to the temporary minimum minimum value Tfmin1 than the temporary second minimum value Tfmin2. If it is determined that there is a provisional value ZANTEI = shift amount Tnmin
1 (step S168). If NO, that is, if it is determined that the recalculation minimum local minimum value fmin1 is closer to the temporary second local minimum value Tfmin2 than the temporary minimum local minimum value Tfmin1, the temporary value ZANTEI = shift amount Tnmi
n2 (step S170). Incidentally, step S15
0, or if NO in step S152, the process proceeds to step S168 to change the provisional value ZANT.
Let EI = shift amount Tnmin1.

Next, the CPU 60 causes (ZANTEI ≧ n
min1), that is, the recalculation minimum minimum value fmin1
The shift amount nmin1 of is + with respect to the provisional value ZANTEI
Whether it is on the side or the-side is determined (step S1).
72). If YES is determined, the shift amount difference nSA is set to (nSA = ZANTEI-nmin1) (step S174).

First, it is determined whether or not (nSA ≧ 3) (step S176). If YES is determined, it is determined that distance measurement is impossible (step S178), and the shortage recalculation process ends.

If NO in step S176, it is then determined whether or not (nSA = 2) (step S180). If YES is determined here, the correlation value f (nmin1-4) at the shift amount n = nmin1-4 and nmin1-5 and the correlation value f (nmi
n1-5) is recalculated by the normal calculation (step S1).
82).

If NO in step S180, it is then determined whether or not (nSA = 1) (step S184). If YES is determined, the correlation value f (nmin1-5) in the shift amount nmin1-5 is recalculated by normal calculation (step S186).

If NO is determined in step S184, the recalculation (recalculation of the shortage) is not performed (step S188), and the process of the shortage recalculation is ended.

If NO in step S172, the shift amount difference nSA = nmin1-ZAN.
TEI (step S190).

First, it is determined whether or not (nSA ≧ 3) (step S192). If YES is determined, it is determined that the distance measurement is impossible (step S194), and the shortage recalculation process ends.

If NO in step S192, it is subsequently determined whether or not (nSA = 2) (step S196). If YES is determined here, the correlation value f (nmin1-4) at the shift amount n = nmin1-4 and nmin1-5 and the correlation value f (nmi
n1-5) is recalculated by the normal calculation (step S1).
98).

If NO is determined in step S196, it is then determined whether or not (nSA = 1) (step S200). If YES is determined, the correlation value f (nmin1-5) at the shift amount n = nmin1-5
Is recalculated by normal calculation (step S202).

If NO is determined in step S196, the recalculation (recalculation of the shortage) is not performed (step S188), and the process of the shortage recalculation is ended.

The shortage recalculation range is the minimum value of n (-
If it is less than 2) or exceeds the maximum value (38) of n, the recalculation is not performed.

By the above shortage recalculation processing, the correlation value f (n) is obtained by the normal calculation of the necessary shift amount range with respect to the shift amount nmin of the highest correlation value fmin.

Next, the erroneous distance measurement peculiar to the above-mentioned calculation of every third i and the prevention thereof will be described. As for the erroneous distance measurement peculiar to the calculation every three i, the contrast extraction processing (2
This is a particular problem when AF data is obtained by performing pixel difference calculation. 50A and 50B are AF of the R sensor 94 and the L sensor 96 obtained by the 2-pixel difference calculation.
FIG. 6 is a diagram exemplifying AF data used in every third i calculation at a shift amount n = 0 among data. in this case,
Since the correlation value calculation uses data every 3rd, it is not possible to capture a portion with contrast. on the other hand,
Since the amount of contrast can be captured by the shift amount before and after this, the shift amount n = 0 is likely to be a minimum value. If the shift amount n deviates from this state by 8 (n = 8), the sensor number of the AF data used in the calculation every 3 i will be shifted by 4, so that n = 0 except for one at the end. The same AF data as in the above case will be used. At this time, if there is no contrast in the newly added AF data at the end, there is a high possibility that the shift amount n will be the minimum value again.

Such a phenomenon is repeated each time the shift amount is shifted by 8. FIG. 51 shows FIG.
The result of calculating the correlation value f (n) by performing calculation every three i's in the example of the AF data of (B) is shown, and as shown in FIG. A local minimum is detected at. Note that FIG. 52 shows the correlation value distribution when the normal calculation is performed using the example of the AF data of FIGS. 50 (A) and 50 (B). As described above, since the minimum value is detected at a position irrelevant to the true minimum value detected in the normal calculation, erroneous distance measurement may be caused.

Further, FIG. 53 shows the correlation value f (n) obtained by calculating every third i when the mode of the sensor data as shown in FIG. 50 is obtained by actual measurement. In this case, the provisional minimum minimum value Tf
min1 is detected by the shift amount Tnmin1 = 33, and the provisional second minimum value Tfmin2 is detected by the shift amount Tnmin2 = 2.
Detected in 6. In such an actual measurement, FIG.
There is almost no contrast in all sensor data used when calculating the correlation value of a certain shift amount n, such as 0 (A) and (B), and there is some contrast. In some cases, the local minimum value is not repeated at shift amount intervals of 8 and is observed at shift amount intervals of 7 or 9 with a shift of ± 1.

From the above, the provisional minimum local minimum value Tfmi
In the case where the difference between n1 and the temporary second minimum value Tfmin2 is smaller than the predetermined adjustment value a, the temporary minimum minimum value shift amount Tnmin1 and the temporary second minimum value shift amount Tnmin.
When the difference from 2 is a multiple of 8 or ± 1 of a multiple of 8, the correlation value calculation is performed by the above-described normal calculation instead of every three i's. That is,

[0221]

[Equation 13] Tfmin2-Tfmin1 <Adjustment value a and

[0222]

In the case of | Tnmin1−Tnmin2 | = (multiple of 8) or (± 1 of multiple of 8), the operation is switched to the normal calculation. By switching to the normal calculation, it is possible to prevent erroneous distance measurement peculiar to the calculation every 3 i. When the correlation value calculation is performed by the normal calculation instead of every three i's, the temporary minimum minimum value shift amount Tnmin1 and the temporary second minimum value shift amount Tnmin are calculated.
The difference from 2 is a multiple of 8 or ± 1 of a multiple of 8
Was used as one of the conditions, but the condition is not limited to the operation of every third i, but if this condition is generalized, if the cell position i is every xth ixth operation with respect to an arbitrary value x. Is the provisional minimum minimum shift amount Tnmin1 and the provisional second
The difference between the minimum shift amount Tnmin2 is (x + 1) ×
It is a multiple of 2 or ± 1 of a multiple of (x + 1) × 2
The condition is that

Next, a second embodiment for reducing the distance measuring time in the correlation value calculation processing will be described. In any of the above-described normal calculation and i3 every other calculation, all shift amounts n (n = -2, -1,
0, 1, ..., MAX (= 38)), the correlation value f (n) is calculated. However, in the second embodiment, the correlation value f (n) for all shift amounts n is calculated. ) Is not calculated, but the correlation value f (n) for the shift amount n at regular intervals is calculated. For example, the shift amount n is calculated every three. still,
The correlation value calculation when the shift amount n is every three is
This is referred to as "every nth calculation", whereas the correlation value calculation for obtaining the correlation value f (n) for all shift amounts n is called "normal calculation" in the description of the second embodiment ( (This is different from the meaning of "normal operation" in the first embodiment). Further, the shift amount n for calculating the correlation value f (n) in every nth third calculation is referred to as the adopted shift amount n.

In FIG. 54A, the number of employed sensors (that is, the number of employed sensors) is 62, and the window size is 4
In the case of 2, the example of the adopted shift amount n in every n nth calculation is shown, and the adopted shift amount n is the shift amount n = -2.
To n = 2, 6, 10, 14, ... Note that N1 in the figure refers to each of the adopted shift amounts n = − with respect to the right end of the adopted sensor 96A as shown in FIG.
.. indicates the shift amount of the L window 96B in 2, 2, 6, ..., And N2 indicates the shift amount of the R window 94B in each adopted shift amount with respect to the left end of the adopted sensor 94A.

However, in the operation of every n3 times, FIG.
In addition to the adopted shift amount shown in (A), it is desirable to calculate the correlation value f (n) as the adopted shift amount for the shift amounts n = -1, 0, 36, 37 shown in FIG. 54 (B). Figure 5
5, FIG. 56, and FIG. 57 show the case where the minimum minimum value fmin1 is obtained for each of the long distance, the medium distance, and the short distance when the correlation values f (n) are obtained for all the shift amounts n by the normal calculation. Assuming that the correlation value f (n) is calculated only with the adopted shift amount n (= 2, 6, 10, 14, ..., 38) shown in FIG.
Correlation value when the correlation value f (n) is calculated with the adopted shift amount n (= -1, 0, 36, 37) shown in FIG. 54B together with the adopted shift amount n shown in (A). It is a graph showing distribution. Incidentally, the correlation value distribution of only the adopted shift amount n in FIG. 54 (A) is shown by a distribution connecting points of “□” symbols in the figure,
The correlation value distribution of the adopted shift amount n in FIGS. 54 (A) and 54 (B) is shown by the distribution connecting the points of the symbol “▲” in the figures.

First, when the minimum minimum value fmin1 originally detected by the normal calculation exists in the shift amount at a long distance, and the minimum minimum value fmin1 is different from the shift amount n adopted in FIG. 54 (A). It is assumed that n = -1.
In this case, when the correlation value f (n) is calculated only with the adopted shift amount n in FIG. 54 (A), the correlation value distribution calculated by this is as shown in the correlation value distribution connecting the “□” symbols in FIG. Therefore, there occurs a situation in which the minimum value is not detected in the vicinity of the shift amount n = -1. On the other hand, FIG. 54 (B)
The correlation value f (n) in the adopted shift amount n (= -1, 0) of
Is calculated, the minimum minimum value is detected at the shift amount n = −1 as shown in the correlation value distribution connecting the “▲” symbols in FIG. 55, and the minimum minimum value fmin1 that should be originally detected on the far side is detected. The problem that is not done is solved.

Similarly, in the case where the minimum minimum value fmin1 originally detected by the normal calculation exists in the shift amount in the short distance, the minimum minimum value fmin1 is shown in FIG.
It is assumed that the shift amount n = −37, which is different from the adopted shift amount n of (A). In this case, the adopted shift amount n in FIG.
When the correlation value f (n) is calculated by only the correlation value distribution connecting the “□” symbols in FIG. 57, the correlation value distribution thus calculated has a minimum value near the shift amount n = −37. The value may not be detected. On the other hand, if the correlation value f (n) is calculated for the adopted shift amount n (= 36, 37) in FIG. 54B, the shift is performed as shown in the correlation value distribution connecting the “▲” symbols in FIG. 57. The problem that the minimum minimum value is detected at the amount n = -37 and the minimum minimum value fmin1 that should be originally detected on the short distance side is not detected is solved.

On the other hand, in the case where the minimum minimum value fmin1 originally detected by the normal calculation exists in the middle distance,
The above-mentioned problems hardly occur. For example, in FIG.
As indicated by the thin line 6 in FIG.
It is assumed that n1 is a shift amount n = 16 which is different from the adopted shift amount n in FIG. In such a case, FIG. 54 (A)
If the correlation value f (n) is calculated only with the adopted shift amount n, the correlation value f (n) in the vicinity of the shift amount n = 16, for example, the shift amount n = 18, as shown in the correlation value distribution connecting the “□” symbols in FIG. The minimum value is detected. Generally, the minimum minimum value fmin
When the shift amount nmin1 of 1 exists in the middle distance,
Since the correlation value distribution in which the correlation values decrease from both sides toward the shift amount n is shown, the adopted shift amount n in FIG.
Even when the correlation value f (n) is calculated only by itself, the minimum value is detected at least in the vicinity of the shift amount n of the minimum minimum value fmin1. If the existence of the local minimum value is known, the accurate shift amount nmin1 of the minimum local minimum value fmi1 detected by the normal calculation can be detected by the recalculation described later, and thus it is sufficient as the processing of every nth calculation.

From the above, in the case of every n3 operations, the calculation shown in FIG.
In addition to the adopted shift amount n shown in FIG.
Also for the adopted shift amount n shown in (B), the correlation value f (n)
Is preferably calculated. In the following, the correlation value f (n) is calculated for every three adopted shift amounts n as shown in FIG. 54A and the specific adopted shift amounts n for the long distance side and the short distance side as shown in FIG. Is calculated every n3 times. However, the correlation value calculation may be performed only with the adopted shift amount n in FIG. 54 (A), and in this case, a correlation value distribution without a minimum value as shown in FIGS. 55 and 57 is obtained. In such a case, it may be assumed that a local minimum value exists at a long distance or a short distance, and the recalculation described later may be performed.

When the CPU 60 calculates the correlation value f (n) at the adopted shift amount n by calculating every n3 as described above, the correlation value f (n) obtained from the adopted shift amount n is used to calculate the correlation value. The shift amount n at which f (n) has a minimum value is detected. If the minimum value detected at this time is one, the minimum value is set to the provisional minimum minimum value Tfmin1. The correlation value f (n) is recalculated again by the normal calculation in the vicinity of the shift amount of the minimum minimum value.
Note that this recalculation processing can use the same method as the above-mentioned recalculation in every third i calculation, and the recalculation range, the processing method in the case where the detected minimum value is plural, and the shortage correlation Detailed description of the value calculation and the like will be omitted. Also, the definition of terms is the same as that used in the explanation of every i3 operation.

The recalculation range is the provisional minimum local minimum value Tfmin.
For example, the range of the shift amount is ± 5 with respect to the shift amount Tnmin1 of 1, and in the example of FIG.
Since the shift amount Tnmin1 from which in1 is obtained is 18, the recalculation range is the shift amount n = 1 as shown in FIG.
3 to 23. However, for the adopted shift amount n for which the correlation value f (n) has already been calculated in every n3 calculation, it is not necessary to calculate the correlation value f (n) again by recalculation.
The adopted shift amount n = 1 included in the recalculation range as shown in
For 4, 18, and 22, the correlation value f is recalculated.
(n) is not calculated.

After calculating the correlation value f (n) in the recalculation range by the above recalculation, the CPU 60 detects the shift amount nmin1 of the minimum minimum value fmin1 based on the correlation value f (n) in the recalculation range. , The shift amount nmin1 of the highest correlation that should be detected in the correlation value calculation
And

Here, the number of calculations when i3 every other calculation or n3 every other calculation is shown, for example, in the case where the number of adopted sensors is 62 and the window size is 42, i3 every other calculation. Is 41/4 = 10.25, and the total number of recalculations 11 is 21.25. In every nth three operations,
The number of operations is 15, and the total number of reoperations 8 is 23. On the other hand, in the case of the normal calculation, since there are 41 calculations, it can be understood that the number of calculations is sufficiently reduced and the distance measuring time is shortened in the calculation of every 3 i and every 3 n.

I in the first embodiment described above
In every third calculation, the shift amount nmin1 of the provisional minimum minimum value Tfmin1 and the minimum minimum value fmin of the normal calculation
When the shift amount nmin1 of 1 does not match, if the shift amount difference is large, the number of calculations in the shortfall correlation value calculation increases, and the effect of time reduction decreases. Also, i
In every third calculation, the number of data becomes 1/4 of that in the normal calculation, so that the accuracy is lowered and the temporary minimum value may not appear. Such a phenomenon is often seen when the contrast of AF data is low.

Therefore, if the contrast of the AF data in the adopted sensor is larger than the predetermined reference value, i3
Most of such phenomena do not occur if every other calculation is performed, and if it is low, the normal calculation is performed. In addition, when the contrast is low, the calculation may be performed every n3 intervals in the second embodiment. {Details of Contrast Detection Process (Step S14, Step S18 in FIG. 7)} Next, the contrast detection process 1 in step S14 and the contrast detection process 2 in step S18 of FIG. 7 will be described in detail. The contrast detection is a process of detecting the presence / absence of contrast in the sensor image (AF data) based on the maximum value and the minimum value of the AF data obtained from the cells (sensor data) within the predetermined range of the AF sensor 74. In the present embodiment, the difference between the maximum value and the minimum value of the AF data is used as the contrast evaluation value,
If the contrast is equal to or higher than a predetermined reference value, it is determined that there is contrast, and if it is smaller than the reference value, it is determined that there is no contrast.

In the contrast detection processing 1 in step S14 of FIG. 7, contrast detection is performed with all cells of the divided areas, that is, all cells of the adopted sensor, as the target range for each divided area forming the distance measuring area, while the step is performed. The contrast detection processing 2 in S16 is performed by the minimum local minimum value f detected by the correlation value calculation in each divided area.
The shift amount nmin1 of min1, that is, the maximum correlation value fm
Contrast detection is performed with all cells in the window range within the shift amount nmin of in as the target range.

FIG. 59 is a flow chart showing the overall procedure of a series of contrast detection processing by the contrast detection processing 1 and the contrast detection processing 2. CPU60
When the AF data is acquired by the AF data acquisition process in step S12 of FIG. 7, the step S1 of FIG.
As one processing of the contrast detection processing 1 in 4, the contrast detection 1 in which each divided area of the R sensor 94 and the L sensor 96 forming the distance measuring area is set as an individual target range
Is performed (step S250). Now R sensor 94
And paying attention to a certain divided area corresponding to the L sensor 96,
The divided area of the R sensor 94 and the divided area of the L sensor 96 are respectively used as the sensor of the R sensor 94 and the L sensor 9
6 is adopted. Then, if the contrast detection 1 is performed for these adopted sensors,
The CPU 60 uses the R sensor 94 for A of all cells of the sensor.
The maximum value and the minimum value of the F data are detected. The maximum value of the AF data detected at this time is RMAX, and the minimum value is R.
Let it be MIN. Similarly, the maximum value and the minimum value of the AF data of all the cells of the sensor adopted by the L sensor 96 are detected. The maximum value of the AF data detected at this time is LMAX, and the minimum value is LMIN.

Next, the CPU 60 calculates the contrast of the sensor adopted by the R sensor 94 by the following equation:

[0239]

[Equation 15] RMAX-RMIN (17)

[0240]

[Expression 16] LMAX-LMIN (18) Next, the CPU 60 performs contrast determination 1 based on the contrast detected by the contrast detection 1 of step S250 as one process of the contrast detection process 1 in step S14 of FIG. 7 (step S252). That is, the contrast RMAX-RMIN of the above formula (17) in the sensor adopted by the R sensor 94 and the contrast LMAX-LMIN of the above formula (18) in the sensor adopted by the L sensor 96 are respectively set with respect to a predetermined reference value R4.

[0241]

[Equation 17] RMAX-RMIN <R4 (19) It is determined whether or not LMAX-LMIN <R4 (20). If either one of the above equations (19) and (20) is satisfied, it is determined that there is no contrast and distance measurement is disabled in those adopted sensors (the divided area of interest) (step S254).
When neither of the above equations (19) and (20) is true, it is assumed that there is contrast in the adopted sensors.

Next, the CPU 60 performs the correlation value calculation processing in step S16 of FIG. 7 for the divided areas determined to have the contrast in step S252 (step S256).

Next, the CPU 60 carries out the shift amount n of the maximum correlation detected by the correlation value calculation as one process of the contrast detection process 2 in step S18 of FIG.
R window 94B and L window 9 at min
Contrast detection 2 is performed with 6B as the target range (step S258). Now, paying attention to a corresponding divided area of the R sensor 94 and the L sensor 96, the divided area of the R sensor 94 and the divided area of the L sensor 96 are referred to as an adopted sensor of the R sensor 94 and an adopted sensor of the L sensor 96, respectively. And Then, assuming that contrast detection 2 is performed for these adopted sensors, the CPU 60 determines the maximum value of the AF data within the range of the R window 94B when the shift amount nmin of the highest correlation is obtained in the adopted sensor of the R sensor 94. Find the minimum value. The maximum value detected at this time is RWMAX, and the minimum value is RWMIN. Similarly, the L window 96 when the shift amount nmin with the highest correlation is obtained in the sensor employing the L sensor 96
The maximum value and the minimum value of AF data are detected in the range of B. The maximum value detected at this time is LWMAX, and the minimum value is LWM.
Let it be IN. Then, the CPU 60 calculates the contrast in the R window 94B by the following equation,

[0244]

[Expression 18] RWMAX-RWMIN (21) In addition, the contrast in the L window 96B is expressed by the following equation,

[0245]

[Formula 19] LWMAX-LWMIN (22) Ask by.

Subsequently, the CPU 60 performs contrast determination 2 based on the contrast obtained by the above equations (21) and (22) as one process of the contrast detection process 2 in step S18 of FIG. 7 (step S260). That is,
Contrast R of the above formula (21) in the R window 94B
WMAX-RWMIN and the contrast LWMAX-LWMIN of the above formula (22) in the L window 96B are respectively set with respect to the above-mentioned reference value R4.

[0247]

[Equation 20] RWMAX-RWMIN <R4 (23) It is determined whether or not LWMAX-LWMIN <R4 (24). If either one of the above equations (23) and (24) is satisfied, it is determined that there is no contrast and the distance measurement in those adopted sensors (the divided area of interest) is disabled (step S254).
If neither of the above equations (23) and (24) holds, the contrast in those windows is considered to be present. If there is contrast, the process moves to the next process.

A specific example of the case where it is determined by the above-mentioned contrast detection processing 1 and contrast detection processing 2 that distance measurement is impossible will be described. For example, when focusing on the central area of the R sensor 94 and the L sensor 96 as the adopted sensor, the AF data of the entire cell range of the adopted sensors is shown in FIG.
It is assumed that low contrast is exhibited as shown in 0 (A) and (B). In this case, the correlation value f is calculated by the correlation value calculation.
When (n) is calculated, the shift amount nmin1 of the minimum minimum value fmin1, that is, the maximum correlation value f is calculated as shown in FIG.
The shift amount nmin of min is detected with the shift amount n = 12. In such a case, as shown in FIGS. 9A and 9B, in the sensor used by the R sensor 94 and the sensor used by the L sensor 96, the window range at the shift amount nmin (the window range having the highest correlation value) ) AF
The data also shows low contrast, and if the shift amount n = 12 is set as the shift amount nmin having the highest correlation, there is a high possibility that the distance will be erroneously measured.

In this way, when the AF data shows low contrast in the entire cell range of the adopted sensor, the correlation value calculation process (1) in the contrast detection process 1 is not actually performed on the adopted sensor. In step S252) of FIG. 59, it is determined that distance measurement is impossible. Therefore, since the correlation value calculation is not performed for the adopted sensor that clearly shows AF data that cannot be measured,
Distance measurement time is shortened.

On the other hand, as shown in FIGS. 61 (A) and 61 (B), it is assumed that the AF data shows high contrast in the entire cell range of the adopted sensors of the R sensor 94 and the L sensor 96. In this case, the correlation value f (n) is calculated by the correlation value calculation.
Then, the shift amount nmin of the highest correlation value fmin is detected with the shift amount n = 12 as shown in FIG. However, in this case, as shown in (A) and (B) of the same figure, the AF data in the window range having the highest correlation value in the sensor adopted by the R sensor 94 and the sensor adopted by the L sensor 96 has low contrast. When the shift amount n = 12 is set as the shift amount nmin having the highest correlation, there is a high possibility that erroneous distance measurement will occur.

As described above, even when it is determined in the contrast detection processing 1 that all cells of the adopted sensor are in the target range and the contrast is detected, the window in the shift amount nmin of the highest correlation detected by the correlation value calculation is used. When the AF data shows low contrast in the range, it is determined that the distance measurement is impossible in the contrast determination 2 (step S260 in FIG. 59) in the contrast detection processing 2. Therefore, even if distance measurement is possible in the contrast detection processing 1, there is a high possibility that erroneous distance measurement will occur.
In the case of 1, it is appropriately determined by the contrast detection process 2 that distance measurement is impossible.

In the contrast detection processing described above,
After performing the correlation value calculation process (step S256 in FIG. 59), the contrast detection process 2 is performed for the window range at the shift amount nmin of the highest correlation (steps S258 and 260 in FIG. 59), but the correlation value calculation process is performed. Instead of performing the contrast detection process 2 after performing the process, the same process as the contrast detection process 2 described above may be performed before performing the correlation value calculation process. For example, it is assumed that the contrast detection processing 1 determines that there is contrast for the AF data of all cells in a certain divided area. In this case, next, targeting the window ranges in all the shift amounts n of the divided area,
The presence or absence of contrast is detected for each window range. As a result, the correlation value calculation is not performed for the shift amount n of the window range determined to have no contrast, and the correlation value calculation is performed only for the shift amount n of the window range determined to have the contrast to calculate the correlation value f (n). To do. Then, the shift amount nmin of the highest correlation value fmin is detected within the range of the shift amount n in which the correlation value f (n) is calculated.
In this case, the number of calculations in the correlation value calculation can be reduced, and the distance measurement time can be shortened. Note that the contrast detection process in this case may not be performed. When it is determined that there is no contrast in the window range for all shift amounts n, the correlation value calculation is not performed even once, and it is determined that distance measurement is impossible.

Furthermore, if there is a window with contrast even at one place, all correlation value calculations may be performed. {L and R channel difference correction processing (FIG. 7, step S20)
Details of L} Next, the L and R channel difference correction processing in step S20 of FIG. 7 will be described. The L and R channel difference correction processing is processing for matching the signal amounts of the AF data acquired from the R sensor 94 of the AF sensor 74 and the AF data acquired from the L sensor 96 of the AF sensor 74. In this processing, in the divided area determined to have the contrast in the contrast determination 2 (see FIG. 59) of the contrast detection processing 2, in the vicinity of the range (± 5n) of the R window 94B and the L window 96B where the highest correlation value is obtained. Perform on AF data.

First, the procedure of the L and R channel difference correction processing in the CPU 60 will be described with reference to the flowchart of FIG. The processing of the contrast determination 2 shown in step S300 of FIG.
Corresponding to the contrast determination 2 of 60, in this determination process, the divided area determined to have no contrast is incapable of distance measurement, and the divided area determined to have contrast has the following L and R channel difference corrections. Move to processing. Therefore, the following description will be made by focusing on a certain divided area determined as having contrast as an adopted sensor. First, the CPU 60 first determines whether the highest correlation value is obtained by the adopted sensor in order to determine whether correction is necessary. The minimum value of the AF data is detected and compared in the range of the window 94B and the range of the L window 96B, and it is determined whether the absolute value of the difference (left and right minimum value difference ΔDMIN) is large, small, or too large. (Step S3
02). Before or after this determination (between step S300 and step S302, or between step S302 and step S304), it is determined whether the highest correlation value in the adopted sensor is equal to or more than a predetermined reference value, It may be determined that the main correction is necessary only when the highest correlation value is equal to or higher than the reference value, and the main correction may not be performed when the highest correlation value is smaller than the reference value. Here, letting RWMIN be the minimum value of AF data in the R window 94B for which the highest correlation value was obtained and LWMIN the minimum value of AF data in the L window 96, the difference between the left and right minimum values ΔD.
MIN is the following equation,

[0255]

[Expression 21] ΔDMIN = | LWMIN−RWMIN | ... (25) Then, predetermined reference values R5 and R6
For (R5 <R6),

[0256]

When ΔDMIN <R5 (26) holds, it is determined that the left-right minimum value difference ΔDMIN is small,

[0257]

If R6 ≧ ΔDMIN ≧ R5 (27) holds, it is determined that the left-right minimum value difference ΔDMIN is large.

[0258]

If ΔDMIN> R6 (28) holds, it is determined that the left-right minimum value difference ΔDMIN is too large.

By the above determination processing, the left and right minimum value difference ΔD
When it is determined that MIN is small, the process shifts to the next process without performing the main correction, and when it is determined that the left-right minimum value difference ΔDMIN is large (correction is appropriate), the main correction is performed. The process proceeds to step S304. If it is determined that the left-right minimum value difference ΔDMIN is too large, distance measurement is impossible (step S306).

If it is determined that the left-right minimum value difference ΔDMIN is large, then the CPU 60 corrects the AF data in the correction range of the adopted sensors of the R sensor 94 and the L sensor 96 (step S304). For the correction of the AF data, for example, the difference amount between the minimum value of the AF data in the sensor adopted by the R sensor 94 and the minimum value of the AF data in the sensor adopted by the L sensor 96 is calculated, and one of the differences is reduced so that the difference amount decreases. For the AF data of the sensor, A of the other sensor
The signal amount of F data is adjusted. Details of AF data correction will be described later. Further, the correction range of the AF data is the AF range after the correction in the processing of the next step S308.
This is a range of AF data required when calculating the correlation value f (n) in a predetermined shift amount range in the correlation value calculation based on the data.

When the AF data is corrected, the corrected A
The correlation value calculation (correlation value calculation after correction) is performed again using the F data to obtain the correlation value f (n) ′ (step S30
8). The correlation value calculation after AF data correction may be performed for all shift amounts n, but in the present embodiment, in the vicinity of the shift amount nmin at which the highest correlation is obtained in the correlation value calculation before AF data correction. , For example, the shift amount n
It shall be performed only within the range of ± 5 with respect to min.

Next, the CPU 60 calculates the correlation value f after the AF data correction based on the correlation value f (n) 'obtained by the correlation value calculation after the AF data correction.
(n) ′ The minimum minimum value fmin ′ within the range of shift amount
And its shift amount nmin 'are detected. Then, based on the minimum minimum value fmin ', it is determined whether the AF data of the corrected R sensor 94 and the AF data of the L sensor 96 have a low degree of coincidence, a high degree of coincidence, or a degree of low coincidence (step S310). ). Specifically, for example,
The minimum minimum value fmin 'after AF data correction is calculated by the following equation with respect to a predetermined reference value R7.

[0263]

If fmin '> reference value R7 (29) is satisfied, it is determined that the degree of coincidence is too low. On the other hand, when the equation (29) is not satisfied, the minimum minimum value fmin ′ after the AF data correction and the maximum correlation value fm before the correction
in is the following equation,

[0264]

If fmin ≦ fmin ′ (30) is satisfied, it is determined that the degree of coincidence is low. Equation (30) does not hold, and the following equation,

[0265]

(27) fmin> fmin '(31) When is satisfied, it is determined that the degree of coincidence is high.

If it is determined by this determination processing that the degree of coincidence is too low, distance measurement is not possible for this employed sensor (step S306). If it is determined that the degree of coincidence is low, the result of the correlation value calculation before the AF data correction is used instead of the result of the correlation value calculation after the AF data correction in the subsequent processing (step S312). On the other hand, when it is determined that the degree of coincidence is high, the result of the correlation value calculation after AF data correction is adopted (step S314). When the result of the correlation value calculation after AF data correction is adopted, the terms correlation value f (n), maximum correlation value fmin, and its shift amount nmin used in the description of the subsequent processing are AF data correction. Later correlation value f
(n) ', minimum minimum value fmin' and its shift amount nnm
indicates in '.

An example of the AF data correction in step S304 will be described below. FIG. 63 shows the AF
The AF data of the R sensor 94 and the L sensor 9 are used to correct the data.
6 is a flowchart showing a processing procedure for correcting a signal amount difference of AF data of No. 6; First, the CPU 60
Determines which of the R sensor 94 and the L sensor 96 corrects the AF data (correction sensor) (step S
330).

Specifically, the minimum value RMIN of AF data in the R window in which the highest correlation is obtained is compared with the minimum value LMIN in the L window in which the highest correlation is obtained, and when RMIN> LMIN, The R sensor 94 is a correction sensor, and when RMIN <LMIN, the L sensor 96 is a correction sensor.

When the L sensor 96 is used as a correction sensor, R
The AF data before correction of the sensor 94 and the L sensor 96 is converted to R
And L, and AF data after correction are RH and LH,
The following equation,

[0270]

(28) LH = L−Signal amount difference RH = R (step S332). Here, the signal amount difference is LMIN-RMIN.

On the other hand, when the R sensor 94 is used as a correction sensor,

[0272]

## EQU29 ## LH = L RH = R-determined by the signal amount difference (step S334). Here, the signal amount difference is RMIN-LMIN.

The effects of the above L and R channel difference correction processing will be described. FIG. 64 is a diagram showing the effects of the L and R channel difference correction processing shown in FIG. Compared to the conventional method, the new method is different in the content of the determination process of whether or not to perform the correction in step S302 of FIG. 62,
Example of first conventional method (this method is called conventional method)
Is within the range of the R window 94B and the L window 96B where the highest correlation value is obtained as in the new method.
Instead of comparing the minimum value of the F data, the R sensor 94
The minimum value RMIN for all the AF data in the adopted sensor of the L sensor 96 and the minimum value LMIN for all the AF data in the adopted sensor of the L sensor 96 are compared, and if the minimum value difference is larger than a predetermined value, the AF data is compared. The method of correcting

As a second example of the conventional method (this method is referred to as a conventional method), the average value of the AF data in each of the adopted sensors of the R sensor 94 and the L sensor 96 is obtained, and the difference is a predetermined value. There is a method of correcting the AF data when it is larger than the above. It is a method of correcting the AF data of one sensor so that the average values match.

For example, in the sensor (for example, the central area) adopted by the R sensor 94 and the L sensor 96, FIG.
It is assumed that AF data as shown in (A) and (B) is obtained. The example of the AF data shows a case where correction is not necessary originally. Then, as a result of performing the correlation value calculation on the AF data in this adopted sensor, it is shown that the correlation value distribution before the AF data correction (without correction) shows the distribution connected by the "." Symbol in FIG. To do. In this correlation value distribution without correction, the shift amount nmin of the highest correlation is detected at the shift amount n = 10, and the ranges of the R window 94B and the L window 96B at that time are shown in FIG. In (B), the AF data distribution is in the range indicated by the thick line.

[0276] In such a case, AF is performed by the conventional method.
When it is determined whether or not to correct the data, FIG.
As is clear from the comparison of (B), there is a difference (difference shown as “conventional” in the figure) between the minimum values of the AF data in the adopted sensors of the R sensor 94 and the L sensor 96. AF data correction (correction of the above signal amount difference)
When the correlation value calculation is performed on the basis of the corrected AF data, the correlation value distribution shows the distribution connected by the symbol “Δ” in FIG. In the correlation value distribution obtained after this AF data correction, since the minimum minimum value is large, it is determined that the degree of agreement between the signal amounts of the AF data of the R sensor 94 and the AF data of the L sensor 96 is low, and it is determined that distance measurement is impossible. Result. Note that, conventionally, the correlation value calculation is not performed before the AF data correction like the new method. Therefore, when it is determined that the degree of matching is low, the correlation value calculation before the AF data correction is performed as in the new method. No measures have been taken to adopt the results of. As described above, in the conventional method, there is a possibility that the distance measurement becomes impossible due to the correction although the AF data which should not be supposed to be the distance measurement is obtained.

If it is determined whether the AF data should be corrected by the conventional method, the R sensor 94 and the L sensor 9 are detected.
There is a difference in the average value of the AF data in each of the six adopted sensors ("conventional" in the comparison of FIGS.
Therefore, the AF data is corrected (correction of the signal amount difference), and when the correlation value is calculated based on the corrected AF data, the correlation is calculated. The value distribution shows the correlation value distribution connected by the "x" symbol in FIG. In the correlation value distribution obtained after this AF data correction, since the minimum minimum value is large as in the conventional method, it is determined that the degree of coincidence between the signal amounts of the AF data of the R sensor 94 and the AF data of the L sensor 96 is low. The result is that it is determined that distance measurement is impossible. As described above, even in the conventional method, there may be a problem that the distance measurement becomes impossible due to the correction even though the AF data that should not be originally made impossible is obtained.

When it is determined whether or not the AF data is corrected by the new method in contrast to the conventional method as described above, it is within the range of the R window 94B and the L window 96B where the highest correlation value is obtained in the adopted sensor. Then, since there is no difference in the minimum value of the AF data, no correction is performed and it is not necessary to perform extra correlation value calculation. Therefore, the conventional method,
Such a problem does not occur. If correction is made, the correlation value distribution shows a distribution connected by the "□" symbols in FIG. 7C, and it is determined that the degree of coincidence is low as in the conventional method. However, even in this case, in the case of the new method, it is determined that the result of the correlation value calculation before the AF data correction is adopted instead of the distance measurement impossible, so that the AF data before correction can be measured without correction. In such a case, it is possible to avoid the problem that distance measurement becomes impossible even if the AF data is not properly corrected.

Next, the AF in step S304 is performed.
In the data correction, a case will be described in which another correction means is adopted instead of the signal amount difference correction shown in the flowchart of FIG. The AF data correction described here is
A of the sensors adopted by the R sensor 94 and the L sensor 96
Not only the signal amount difference of the F data but also the contrast ratio is corrected. The correction is performed on the AF data of the R sensor 94 or the L sensor 96, whichever does not exceed the dynamic range. The details of the correction process will be described below.

First, the contrast correction amount and offset correction amount used in the AF data correction formula will be described. The offset correction amount corresponds to the correction amount for correcting the signal amount difference. Here, the contrast correction amount is DLVCOMPA, the offset correction amount is DLVCOMPB, the maximum value and the minimum value of the AF data in the sensor adopted by the R sensor 94 are R1MAX and R1MIN, and the AF value in the sensor adopted by the L sensor 96, respectively.
The maximum and minimum values of data are L1MAX and L, respectively.
The minimum value of AF data in the R window 94B and the L window 96B for which the maximum correlation is obtained is 1 MIN and R2MIN and L2MIN, respectively.

The formula for obtaining the contrast correction amount DLVCOMPA and the offset correction amount DLVCOMP differs depending on the magnitude relationship between the minimum value R2MIN of AF data in the R window 94B and the minimum value R2MIN of AF data in the R window 94B in which the highest correlation is obtained. .
The following equation,

[0282]

[Equation 30] When L2MIN ≦ R2MIN (32) holds, the contrast correction amount DLVCOMPA
And offset correction amount DLVCOMPB are given by

[0283]

[Equation 31]   DLVCOMPA = (R1MAX-R1MIN) / (L1MAX-L1MIN )… (33)   DLVCOMPB = R1MIN-{(R1MAX-R1MIN) / (L1MA X-L1MIN)} × L1MIN (34) Required by.

On the other hand, the following equation,

[0285]

[Equation 32] When L2MIN> R2MIN (35) holds, the contrast correction amount DLVCOMPA
And offset correction amount DLVCOMPB are given by

[0286]

[Expression 33]   DLVCOMPA = (L1MAX-L1MIN) / (R1MAX-R1MIN )… (36)   DLVCOMPB = L1MIN-{(L1MAX-L1MIN) / (R1MA X-R1MIN)} × R1MIN (37) Required by.

From the above equation, the contrast correction amount DLVCO
Once the MPA and the offset correction amount DLVCOMPB are obtained, the calculation process for correcting the AF data of the correction range in the adopted sensor based on the contrast correction amount DLVCOMPA and the offset correction amount DLVCOMPB will be described. Here, the AF data before correction of the R sensor 94 and the L sensor 96 is R and L, and the AF data after correction is RH and LH.

The following equation,

[0289]

When L2MIN ≦ R2MIN (38) holds, the corrected AF data RH and LH are the contrast correction amount DLVC obtained by the above equations (33) and (34).
Using OMPA and offset correction amount DLVCOMPB, the following correction equation,

[0290]

[Equation 35]   LH = DLVCOMPA × L + DLVCOMPB (39)   RH = R (40) Is calculated by

On the other hand, the following equation,

[0292]

In the case of L2MIN> R2MIN (41), the corrected AF data RH and LH are as shown in the above equation (36),
Contrast correction amount DLVCOMPA calculated by (37)
And offset correction amount DLVCOMPB, the following correction formula,

[0293]

[Equation 37]   LH = L (42)   RH = DLVCOMPA × R + DLVCOMPB (43) Is calculated by

The above AF data correction processing procedure is shown in FIG.
It is shown in the flowchart. The CPU 60 controls the A in the R window 94B and the L window 96B for which the highest correlation is obtained by the correlation value calculation process in step S16 of FIG.
For the minimum values R2MIN and L2MIN of F data, the above equation (32), that is,

[0295]

[Equation 38] It is determined whether or not L2MIN ≦ R2MIN (32) holds (step S350). Y
If it is determined to be ES, then the contrast correction amount DLV
COMPA is expressed by the above formula (33), that is,

[0296]

(39) DLVCOMPA = (R1MAX-R1MIN) / (L1MAX-L1MIN) (33) (step S352). Further, the offset correction amount DLVCOMPB is expressed by the above equation (34), that is,

[0297]

[Formula 40]   DLVCOMPB = R1MIN-{(R1MAX-R1MIN) / (L1MA X-L1MIN)} × L1MIN (34) Is calculated (step S354).

Then, the corrected AF data RH and LH are represented by the above equations (39) and (40), that is,

[0299]

[Formula 41]   LH = DLVCOMPA × L + DLVCOMPB (39)   RH = R (40) Is calculated according to (step S356).

On the other hand, NO in the above step S350.
If it is determined that the contrast correction amount DLVCOM
PA is expressed by the above formula (36), that is,

[0301]

## EQU42 ## DLVCOMPA = (L1MAX-L1MIN) / (R1MAX-R1MIN) (36) is calculated (step S358). In addition, the offset correction amount DLVCOMPB is expressed by the above equation (37), that is,

[0302]

[Equation 43]   DLVCOMPB = L1MIN-{(L1MAX-L1MIN) / (R1MA X-R1MIN)} × R1MIN (37) Is calculated by (step S360).

Then, the corrected AF data LH and RH are expressed by the above equations (42) and (43), that is,

[0304]

[Equation 44]   LH = L (42)   RH = DLVCOMPA × R + DLVCOMPB (43) Is calculated by (step S362).

Next, regarding the effect of the AF data correction processing when the contrast correction and the offset correction (signal amount difference correction) described here are performed, the AF data correction processing (see FIG. 63) for performing only the signal amount difference correction described above is performed. Description will be made in comparison. The former is called the new method and the latter is called the conventional method (embodiment 1).

First, the correction result in the case where one of the R sensor 94 and the L sensor 96 is bright (when one sensor is irradiated with sunlight or the like → there is a signal amount difference and there is no contrast difference) To illustrate. FIG. 66
(A) and (B) are distributions of AF data before correction (without correction) in the sensors (center area in the figure) adopted by the R sensor 94 and L sensor 96 and AF after correction by the conventional method.
The distribution of data is shown.
This is done for F data.

On the other hand, FIGS. 67A and 67B show the distribution of AF data before correction (without correction) and the distribution of AF data after correction by the new method, which are the same as those in FIG.
This is performed on the AF data of the L sensor 96.

FIG. 68 is a correlation value when the correlation value f (n) is calculated based on the AF data before correction in FIGS. 66 and 67 and the AF data after correction by the new method and the conventional method, respectively. The distribution is shown.

As can be seen from the correlation value distribution of FIG. 68, the AF data of the R sensor 94 and the L sensor 96 before correction are obtained.
When there is no contrast difference between the AF data of No. 1 and the AF data of No. 3, the same result is shown in both the conventional AF data correction and the new AF data correction. The degree of agreement of the signal amounts of is improved. In FIG. 69, the subject is actually arranged at a distance from the closest distance to infinity, and the set distance (vertical axis) of the taking lens set by autofocus is set to the distance (horizontal axis) and the AF data is corrected. Is not performed (without correction), the AF data is corrected by the new method, the AF data is corrected by the conventional method, and the design value is used. As is clear from this figure, there is a deviation from the design value without correction, but in the case of the conventional method and the new method, the set distance of the taking lens is almost the same as the design value. I understand. From the above, when there is no contrast difference between the R sensor 94 and the L sensor 96, the A method of either the conventional method or the new method is used.
Appropriate results can be obtained even in the F data correction process.

However, the R sensor 94 and the L sensor 9
When one of 6 sensors is dark (when the sensor on one side is hidden by a finger, etc. → when there is a signal amount difference and contrast difference), the new method is more advantageous than the conventional method. Is obtained. Next, the correction result in this case will be illustrated. 70 (A) and 70 (B) show the distribution of AF data before correction (without correction) and the distribution of AF data after correction by the conventional method in the sensors (center area in the figure) adopted by the R sensor 94 and the L sensor 96. And the correction is performed on the AF data of the R sensor 94.

On the other hand, FIGS. 71A and 71B show the distribution of AF data before correction (without correction) and the distribution of AF data after correction by the new method, which are the same as those in FIG.
This is performed on the AF data of the L sensor 96.

FIG. 72 is a correlation value distribution when the correlation value f (n) is calculated based on the AF data before correction in FIGS. 70 and 71 and the AF data after correction by the new method and the conventional method. Is shown.

As can be seen from the correlation value distribution in FIG. 72, the minimum minimum value is smaller in the AF data correction by the new method than in the conventional method, and the AF data of the R sensor 94 and L
The degree of agreement of the signal amount of the AF data of the sensor 96 is further improved. In FIG. 73, the subject is actually placed at a distance from the closest distance to infinity, and the distance (horizontal axis) is set to the setting distance (vertical axis) of the photographing lens set by AF, and the AF data is corrected. If not performed (without correction), if AF data is corrected by the new method, AF is performed by the conventional method.
It shows the case where the data is corrected and the case of the design value. As is clear from this figure, the setting distance of the taking lens is deviated from the design value in the case of no correction and in the conventional method, but in the case of the new method, the setting distance of the taking lens is designed. It can be seen that the values almost match. From the above, when there is a contrast difference between the R sensor 94 and the L sensor 96, the AF data correction process by the new method can obtain a more appropriate result than the conventional method. Therefore, the new method, which can obtain an appropriate result regardless of the contrast difference, is more suitable than the conventional method.

The above-mentioned contrast correction amount DLVCOM
R1MAX and R1MIN, L1MAX and L when calculating PA and offset correction amount DLVCOMPB
Although 1 MIN is the maximum value and the minimum value of the AF data of the sensors adopted by the R sensor 94 and the L sensor 96, respectively, it is not limited to this, and the AF of the R sensor 94 and the L sensor 96 is not limited to this.
It may be the maximum value and the minimum value of the AF data in the range for correcting the data. In addition, R1MAX, R1MI
R2MAX, R instead of N, L1MAX, L1MIN
2MIN, L2MAX, L2MIN may be used. In addition, R2MIN in the above formulas (32), (35), (38), and (41),
L2MIN is the minimum value of the AF data in the R window 94B and the L window 96B where the highest correlation is obtained, but A2 instead of R2MIN and L2MIN
You may use the minimum value of AF data in the range which corrects F data. {Minimum value determination process} Next, the minimum value determination process will be described. The correlation value calculation processing in step S16 of FIG. 7 described above,
7. The L and R channel difference correction processing in step S20 in FIG. 7 includes processing for detecting the minimum value of the correlation value f (n) from the correlation value distribution. At that time, the processing for the minimum value determination described here is performed. Determines whether or not there is a minimum value. Basically, the correlation value determined to be the minimum value is smaller than any correlation value in the shift amounts adjacent to both sides of the shift amount, and the smallest minimum value is the minimum minimum value. .

By the way, when the subject is present at a shorter distance than the closest distance at which the distance can be measured, the minimum value of the correlation value originally does not exist. FIG. 74 is a diagram showing an example of a correlation value distribution in the case where it is assumed that the correlation value f (n) has been calculated up to a shift amount on a closer distance side than the maximum value 38 of the shift amount n in this case. is there. In such a correlation value distribution, there is no minimum value in the range of the shift amount n = −2 to 38, and therefore it is determined that distance measurement cannot be performed by this adopted sensor. This judgment is appropriate.

However, even when the subject is present at a short distance rather than the closest distance in this way, there may be a local minimum value as shown in FIGS. 75 and 76. 75 shows the case of high contrast, and FIG. 76 shows the case of low contrast.

On the other hand, as the basic determination content of the minimum value determination, when the minimum value is larger than the predetermined value, it is determined that the minimum value is not the minimum value. In the case of 75, there is no minimum value, and it is appropriately determined that distance measurement is impossible.

On the other hand, in the case of FIG. 76, the minimum value is 100.
Since there is a value smaller than 0, there is a problem that it is determined that the minimum value exists in the above determination content.

Therefore, in the determination of the minimum value, the following determination is made to eliminate the above-mentioned problem. When the subject is within the range in which the distance can be measured, the minimum minimum value of the correlation value f (n) is usually also the minimum value. On the other hand, when the minimum value is detected on the side closer to the shift amount of the minimum minimum value, it can be predicted that the subject is located on the side closer than the closest point. Therefore, when there is a correlation value smaller than the minimum minimum value on the close side (the closer the shift amount is, the closer the side) to the shift amount of the minimum minimum value, the short distance warning or the distance measurement is disabled.

On the other hand, if there is a minimum value on the far distance side with respect to the shift amount of the minimum minimum value, some abnormality (shift amount n
Since it becomes infinity at = 0, it cannot be determined that it is infinity farther than infinity. Therefore, distance measurement is impossible. {Details of Interpolation Value Calculation Process (Step S22 in FIG. 7)} Next, the interpolation value calculation process in step S22 of FIG. 7 will be described. The interpolation value calculation process is a process of detecting the shift amount of the highest correlation with higher accuracy from the peripheral correlation value f (n) with respect to the shift amount nmin for which the highest correlation (highest correlation value fmin) is obtained in each divided area. Is. In the following description, the shift amount of the highest correlation detected by the interpolation value calculation process is called the true highest correlation shift amount, and the value is indicated by x.

The CPU 60 performs the following processing in this interpolation value calculation processing. As shown in FIG. 77, the highest correlation (highest correlation value fmin (f (nmi
n)) for the obtained shift amount nmin, the correlation value f (nmin-1) of the shift amount nmin-1 of -1 and +1
And the correlation value f (nmin + 1) of the shift amount nmin + 1 of

[0322]

It is assumed that the relationship of f (nmin−1)> f (nmin + 1) (44) is satisfied. In this case, the CPU 60 controls the correlation value f (n of the shift amount nmin and the shift amount nmin−1.
min) and f (nmin−1), and a correlation value f of the shift amount nmin + 1 and the shift amount nmin + 2.
A straight line L passing through (nmin + 1) and f (nmin + 2)
Find the intersection with 2. Then, the intersection is set as the shift amount x of the true highest correlation.

On the other hand, as shown in FIG. 78, the shift amount nmin at which the highest correlation is obtained is -1.
−1 correlation value f (nmin−1) and +1 shift amount nm
and the correlation value f (nmin + 1) of in + 1 is

[0324]

It is assumed that the relationship of f (nmin−1) ≦ f (nmin + 1) (45) is satisfied. In this case, the CPU 60 causes the correlation value f between the shift amount nmin-1 and the shift amount nmin-2.
A straight line L passing through (nmin-1) and f (nmin-2)
1, and a straight line L passing through the correlation values f (nmin) and f (nmin + 1) of the shift amount nmin and the shift amount nmin + 1
Find the intersection with 2. Then, the intersection is set as the shift amount x of the true highest correlation.

However, as shown in FIG. 79, the minimum value of the shift amount n (shift amount n = -2) is the minimum value of the correlation value f (n),
Alternatively, as shown in FIG. 80, when the maximum value of the shift amount n (shift amount n = 38) is the minimum value of the correlation value f (n), these minimum values do not become the minimum value, and therefore the shift amount. n minimum value (shift amount n = -2) or maximum value (shift amount n =
There is no case where the interpolation value calculation is performed with 38) as the shift amount nmin of the highest correlation. In this case, distance measurement is impossible.

Further, as shown in FIGS. 81A and 81B, +1 is added to the minimum value of the shift amount n (shift amount n = -2).
When the shift amount (shift amount n = −1) is the shift amount nmin having the highest correlation, when the relationship of the above equation (44) holds as in FIG. 81 (A) (in the case of FIG. 77), ,
Interpolation value calculation can be performed. However, FIG. 81 (B)
When the relation of the above equation (45) is established (case of FIG. 78) as described above, the straight line L1 is not determined and the distance measurement is impossible without performing the interpolation value calculation.

In addition, as shown in FIGS. 82A and 82B, when the maximum value of the shift amount n-1 (shift amount n = 37) is the shift amount nmin of the highest correlation,
When the relationship of the above equation (45) is established as in (B) (Fig. 78).
In the case of), interpolation value calculation can be performed. However, when the relationship of the above equation (44) is established as in FIG. 82 (A) (the case of FIG. 77), the straight line L2 is not determined, and the distance measurement is impossible without performing the interpolation value calculation.

The above processing is a basic processing, and in the following case, the shift amount x of the true highest correlation is obtained by another processing. For example, with respect to the shift amount nmin for which the highest correlation is obtained, the shift amounts nmin-2 and nmin in the range of ± 2
When the correlation values f (n) of −1, nmin + 1, and nmin + 2 are compared, it is assumed that the correlation values f (n) are close to each other only by the shift amount n at three consecutive points including the shift amount nmin. In this case, it is considered that the correlation values at the center points of the three points are shifted.

Therefore, in this case, the shift amount x of the true highest correlation is detected by the interpolation value calculation process described below instead of the above-mentioned interpolation value calculation process. The interpolation value calculation process described above is called an interpolation value normal calculation process, and the interpolation value calculation process described below is called an interpolation value-based calculation process. Further, a specific determination as to whether the correlation value f (n) is a close value will be described later.

As described above, when the correlation value f (n) shows a close value only in the continuous shift amount n of three points, the correlation value of the central point in the shift amount n of the three points is originally the highest correlation. It is considered that it should have been detected as the value fmin. Therefore, the CPU 60 sets the minimum shift amount ns among the shift amounts n of the three points and −1 for the shift amount ns.
Correlation value f (ns) and f (ns-) with the shift amount ns-1 of
A straight line L1 passing through 1) and a straight line passing the correlation values f (nl) and f (nl + 1) of the maximum shift amount nl among the three shift amounts n and the shift amount nl + 1 of +1 with respect to the shift amount nl. Find the intersection with L2. Then, the intersection is set as the shift amount x of the true highest correlation.

For example, as shown in FIG. 83, the maximum correlation shift amount nmin is detected as 0, and the maximum correlation value f (0) and the shift amount nmin are shifted by +1 and +2.
It is assumed that the correlation values f (1) and f (2) in 2 are close to each other. In this case, a straight line L1 passing the correlation values of the shift amounts n = −1 and 0 and a straight line L2 passing the correlation values of the shift amounts n = 2 and 3.
The intersection point with is obtained, and the intersection point is set as the shift amount x. As in this example, the shift amount nmin of the highest correlation is +1
Processing when the correlation value in the shift amounts of + and +2 becomes a value close to the maximum correlation value is called processing type 1.

As shown in FIG. 84, the maximum correlation shift amount nmin is detected at 0, and the maximum correlation value f (0) and the shift amount nmin are -1 and +1 shift amount -1,
It is assumed that the correlation values f (-1) and f (1) in 1 are close to each other. In this case, an intersection of a straight line L1 passing the correlation values of the shift amounts n = -2 and -1, and a straight line L2 passing the correlation values of the shift amounts n = 1 and 2 is determined, and the intersection is defined as the shift amount x.
Incidentally, the processing when the correlation value at the shift amounts of −1 and +1 becomes a value close to the maximum correlation value with respect to the shift amount nmin of the maximum correlation as in this example is referred to as processing type 2.

As shown in FIG. 85, the maximum correlation shift amount nmin is detected at 0, and the maximum correlation value f (0) and the shift amount nmin are -2 and -1 shift amounts -2,
It is assumed that the correlation values f (-2) and f (-1) at -1 are close to each other. In this case, an intersection of a straight line L1 passing the correlation values of the shift amounts n = -3 and -2 and a straight line L2 passing the correlation values of the shift amounts n = 0 and 1 is defined as the shift amount x. Incidentally, the processing when the correlation value becomes a value close to the maximum correlation value in the shift amounts of −2 and −1 with respect to the shift amount nmin of the maximum correlation as in this example is referred to as processing type 3.

FIG. 86 is a flow chart showing a procedure for discriminating processing types 1 to 3 of the interpolation value normal calculation and the interpolation value-based calculation in the interpolation value calculation processing. First, CP
U60 is the correlation value difference f (nmin) between the highest correlation value f (nmin) and the correlation value f (nmin + 1) at the shift amount nmin + 1 of +1 with respect to the shift amount nmin of the highest correlation.
+1) -f (nmin) is the following formula with respect to the reference value R7:

[0335]

It is determined whether or not f (nmin + 1) -f (nmin) <R7 is satisfied (step S400). still,
The reference value R7 is an upper limit value with which it can be determined that the two correlation values are close to each other. If NO is determined, next, the highest correlation value f (nmin) and the correlation value f (n at the shift amount nmin−1 of −1 with respect to the shift amount nmin are calculated.
min-1) correlation value difference f (nmin-1) -f (nmi
n) is based on the reference value R7,

[0336]

It is determined whether or not f (nmin-1) -f (nmin) <R7 is satisfied (step S402). If NO is also determined in this determination process,
Normal interpolation value calculation processing is performed (step S432), the shift amount x of the true highest correlation is detected, and this interpolation value calculation processing is terminated.

On the other hand, if YES in step S402, then the correlation value f (n at the shift amount nmin-3 of -3 with respect to the shift amount nmin having the highest correlation is obtained.
min-3) is present (step S
404). If NO is determined, a normal interpolation value calculation process is performed (step S432). On the other hand, if YES is determined, the correlation value f at the shift amount nmin-1
(nmin-1) and the correlation value difference f (nmin-2) -f in the shift amount nmin-2 f (nmin-2) -f
(nmin-1) is the following formula with respect to the reference value R7:

[0338]

It is determined whether or not f (nmin-2) -f (nmin-1) <R7 is satisfied (step S406). If it is determined NO in this determination process, the interpolation value normal calculation process is performed (step S432). on the other hand,
If YES is determined, a correlation value difference f (nmi between the correlation value f (nmin-2) at the shift amount nmin-2 and the correlation value f (nmin-3) at the shift amount nmin-3.
n−3) −f (nmin−2) is the following formula with respect to the reference value R7:

[0339]

[Mathematical formula-see original document] It is determined whether or not f (nmin-3) -f (nmin-2) <R7 is satisfied (step S408). If YES is determined in this determination process,
Interpolation value normal calculation processing is performed (step S432). On the other hand, if NO is determined, the correlation value f (nmin + 1) at the shift amount nmin + 1 and the shift amount nmin-2
Correlation value f (nmin-2) with the correlation value f (nm
in + 1) -f (nmin-2) is relative to the reference value R7,
The following equation,

[0340]

[Equation 51] It is determined whether or not f (nmin + 1) -f (nmin-2) <R7 is satisfied (step S410). If NO is determined in this determination processing, the calculation processing for each interpolation value of processing type 3 is performed (step S41).
2). That is, as shown in FIG. 85, the correlation value f (nmin
Assuming that a local minimum value (true highest correlation value) exists near −1), correlation values f (nmin-3), f (nmin-2), f
The shift amount x is calculated based on (nmin) and f (nmin + 1).

On the other hand, if it is determined to be YES in step S410, the calculation processing for each interpolation value of processing type 2 is performed (step S420). That is, as shown in FIG. 84, a minimum value (true highest correlation value) near the correlation value f (nmin)
Of the correlation values f (nmin-2), f (n
The shift amount x is obtained based on (min-1), f (nmin + 1), f (nmin + 2).

If YES in step S400, the CPU 60 determines the highest correlation value f (nmi
n) and the correlation value difference f (nmin-1) at the shift amount nmin-1 of -1 with respect to the shift amount nmin of the highest correlation
The correlation value difference f (nmin−1) −f (nmin) with respect to the reference value R7 is

[0343]

(52) It is determined whether or not f (nmin-1) -f (nmin) <R7 is satisfied (step S414). YE
When it is determined to be S, the correlation value difference f (nmi) between the correlation value f (nmin-1) at the shift amount nmin-1 and the correlation value f (nmin-2) at the shift amount nmin-2 is next.
n-2) -f (nmin-1) is the following formula with respect to the reference value R7:

[0344]

[Equation 53] It is determined whether or not f (nmin-2) -f (nmin-1) <R7 is satisfied (step S416). If YES is determined in this determination process,
Interpolation value normal calculation processing is performed (step S432). On the other hand, if NO is determined, then the shift amount nmin
Correlation value f (nmin + 1) at +1 and shift amount nm
The correlation value difference f (nmin + 2) -f (nmin + 1) with the correlation value f (nmin + 2) at in + 2 is expressed by the following equation with respect to the reference value R7:

[0345]

It is determined whether or not f (nmin + 2) -f (nmin + 1) <R7 is satisfied (step S418). If YES is determined in this determination process,
Interpolation value normal calculation processing is performed (step S432). On the other hand, when it is determined to be NO, the calculation process for each interpolation value of process type 2 is performed (step S420).

If NO in step S414, the CPU 60 determines the maximum correlation shift amount nmin.
With respect to the shift value nmin-3 of -3 with respect to f
It is determined whether (nmin-3) exists (step S422). If NO is determined, a normal interpolation value calculation process is performed (step S432). On the other hand, when the determination is YES, the correlation value f at the shift amount nmin + 1
Correlation value difference f (nmin + 2) -f between the correlation value f (nmin + 2) at the shift amount nmin + 2
(nmin + 1) is the following equation with respect to the reference value R7:

[0347]

It is determined whether or not f (nmin + 2) -f (nmin + 1) <R7 is satisfied (step S424). NO
If it is determined that the interpolation value normal calculation processing is performed (step S432). On the other hand, if YES is determined, the correlation value f (nmin + 2) at the shift amount nmin + 2
And the correlation value f (nmin at shift amount nmin + 3
+ (3) correlation value difference f (nmin + 3) -f (nmin +
2) is based on the reference value R7,

[0348]

[Equation 56] It is determined whether or not f (nmin + 3) -f (nmin + 2) <R7 is satisfied (step S426). If YES is determined, the interpolation value normal calculation process is performed (step S432). On the other hand, if NO is determined, then the correlation value f at the shift amount nmin-1
Correlation value difference f (nmin-1) -f between the correlation value f (nmin + 2) at the shift amount nmin + 2
(nmin + 2) is the following formula with respect to the reference value R7:

[0349]

[Equation 57] It is determined whether or not f (nmin-1) -f (nmin + 2) <R7 is satisfied (step S428). If NO is determined, the calculation process for each interpolation value of process type 2 is performed (step S420). On the other hand, if it is determined to be YES, the calculation processing for each interpolation value of processing type 1 is performed (step S430). That is, as shown in FIG. 83, assuming that a minimum value (true highest correlation value) exists near the correlation value f (nmin + 1), the correlation values f (nmin−1), f
The shift amount x is calculated based on (nmin), f (nmin + 2), and f (nmin + 3). {Details of AF Error Processing (Step S24 in FIG. 7)} Next, the AF error processing in step S24 in FIG. 7 will be described. In the AF error processing, when it is determined that the distance measurement is impossible in all the divided areas of the distance measurement areas set in the three areas or the five areas in the distance measurement area setting processing (see step S10 in FIG. 7), the preset object distance is set. This is a process of setting the taking lens to a fixed focus so as to focus on. In addition, C which sets the taking lens to a fixed focus
The processing of the PU 60 is called fixed focus processing, and this fixed focus processing will be described below.

When it is determined that the distance measurement is impossible in all the divided areas of the distance measurement area, the CPU 60 determines in advance as shown in the flow charts of FIGS. 87 and 88 according to the cause of the determination that the distance measurement is impossible and the film sensitivity. Set the taking lens to a fixed focus.

First, when it is determined that distance measurement is impossible in all the divided areas of the distance measurement area, the CPU 60 determines whether or not AF pre-emission has been performed (step S45).
0). If NO is determined, it is determined whether the sensor sensitivity is set to high sensitivity or low sensitivity (step S452). When it is determined that the sensitivity is set to low, the photographing lens is set to a fixed focus of 6 m (step S
454) On the other hand, if it is determined in step S452 that the sensor sensitivity has been set to high sensitivity, then the flow shifts to the flowchart in FIG. 88 and the film sensitivity is less than ISO 400 or IS.
It is determined whether it is O400 or more (step S464). IS
If it is determined to be less than O400, the taking lens is set to a fixed focus of 3 m (step S466). On the other hand, ISO
If it is determined to be 400 or more, the photographing lens is set to a fixed focus of 6 m (step S468).

If YES in step S450, the CPU 60 next determines whether the distance measuring area is set to 5 areas or 3 areas (step S45).
6). When it is determined that the area is set to 5 areas, it is determined whether or not the reason why it is determined that distance measurement is impossible in all of the divided areas is insufficient signal amount (the subject is dark) (step S458). If YES is determined, the taking lens is set to the infinity position (step S46).
0). On the other hand, if NO is determined, the process proceeds to the process of the flowchart of FIG. 88, and the taking lens is set to a fixed focus according to the film sensitivity (details omitted).

When it is determined in step S456 that the three areas are set, it is determined whether or not the reason why it is determined that the distance measurement is impossible in all the divided areas is the signal amount shortage, as in the case of the five areas setting (step). S46
2). If YES is determined, the taking lens is set to the infinity position (step S460). On the other hand, if NO is determined, the process proceeds to the process of the flowchart of FIG. 88, and the taking lens is set to a fixed focus according to the film sensitivity (details omitted). {Details of Area Selection Process (Step S28 in FIG. 7)} Next, the area selection process in step S28 in FIG. 7 will be described. The area selection processing is processing for selecting which divided area of the object distances calculated for each divided area of the distance measuring area is to be used for focusing of the photographing lens. In principle, the closest one of the subject distances calculated in the divided areas other than the divided areas determined to be unable to measure the distance is used. The subject distance in each divided area is calculated by the distance calculation process in step S26 of FIG. 7 based on the shift amount x of the true highest correlation calculated by the interpolation value calculation process in step S22 of FIG.

On the other hand, as an exception, when only the subject distance of either the left area or the right area becomes extremely short in comparison with other divided areas, the subject distance is not adopted and other The closest subject distance in the divided area is adopted.

To be more specific, reference values 1 and 2 for dividing the subject distance into three sections, that is, a super close range, a short range, and a medium range and beyond are set in advance. The reference value 1 is, for example, 50
The reference value 2 is set to, for example, cm (distance at which a short-distance warning is generated) and 4 m. Now, when the distance measurement area is set to 5 areas, it is assumed that the subject distance is calculated in each of the central area, the middle left area, the left area, the middle right area, and the right area. Then, the subject distance of only one of the left area and the right area becomes the super close distance closer than the reference value 1, and the other divided areas (the divided area of the left area and the right area where the subject distance is not the super close distance) It is assumed that the subject distance (including also) is more than the middle distance, which is farther than the reference value 2. In this case, the subject distance in the left area or the right area, which is the closest distance, is not adopted, and the closest one among the subject distances in the other divided areas is adopted. If any one of the divided areas other than the left area or the right area where the distance is super close, the super close distance, or
If there is a close object distance, as a general rule,
The closest subject distance among the subject distances of all the divided areas is adopted.

As a concrete example, as shown in FIG. 89 (A), the object distance of each divided area is a super close distance in which only the object distance of the left area is closer than the reference value 1, and in other divided areas. It is assumed that the distance is greater than the reference value 2 and is equal to or greater than the middle distance. In this case, of the subject distances obtained in the divided areas other than the left area, the closest subject distance in the central area is used.

On the other hand, as shown in FIG. 89 (B), the subject distance in the left area is a super close distance closer than the reference value 1, and the subject distance in the central area is farther than the reference value 1 and closer than the reference value 2. , It is assumed that the subject distances of the other divided areas are more than the middle distance, which is farther than the reference value 2. In this case, as a general rule, the subject distance in the left area that is the closest is adopted. As shown in FIG. 89C, the subject distance in the left area is farther than the reference value 1 and closer than the reference value 2 Then, it is assumed that the subject distances in the other divided areas are more than the middle distance, which is farther than the reference value 2. In this case also, as a general rule, the object distance in the left area that is the closest is adopted.

The same applies to the right area, as shown in FIG.
As shown in FIG. 9 (D), it is assumed that only the subject distance in the right area is a super close distance closer to the reference value 1, and the other divided areas are farther than the reference value 2 than the middle distance. In this case, of the subject distances obtained in the divided areas other than the right area, the closest subject distance in the left area is adopted.

On the other hand, as shown in FIG. 89 (E), the subject distance in the right area is a super close distance closer than the reference value 1, and the subject distance in the left area is farther than the reference value 1 and closer than the reference value 2. , It is assumed that the subject distances of the other divided areas are more than the middle distance, which is farther than the reference value 2. In this case, as a general rule, of the subject distances of all the divided areas, the closest subject distance of the right area is adopted.

Further, as shown in FIG. 89 (F), the subject distance in the right area is farther than the reference value 1 and closer to the reference value 2, and the subject distances in the other divided areas are smaller than the reference value 2. It is assumed that the distance is farther than the middle distance. In this case as well, as a general rule, the object distance of the closest right area is adopted among the object distances of all the divided areas.

The above exceptional processing can be similarly applied to the case where the distance measuring areas are set to three areas. That is, in the case of setting three areas, the subject distance becomes a super close distance in only one of the center right area, the center left area, and the center left area of the left middle area which configure the distance measuring area.
When the subject distance becomes longer than the middle distance in the other divided areas, the closest subject distance among the subject distances other than the super close distance may be adopted.

As described above, the AF sensor 74 is used in the above embodiment.
Although the sensor data is output by the CPU 60 and converted into AF data by the CPU 60 to perform the correlation value calculation process, the present invention is not limited to this. After the AF sensor 74 converts the sensor data into AF data, the AF data is converted into AF data. And output
A mode in which the correlation value calculation processing is executed by the CPU 60, and
The AF sensor 74 may convert the sensor data into AF data, perform the correlation value calculation process, and then output the distance signal to the CPU 60.

Further, although the above-mentioned embodiment is an example of an external light passive type distance measuring device, the present invention is not limited to this.
It can also be applied to the passive phase difference method of L or the like.

Further, the distance measuring device for the camera according to the above-mentioned embodiment is not limited to the camera, and can be applied to the distance measuring device used for other purposes.

[0365]

As described above, according to the distance measuring apparatus of the present invention, the correlation value is calculated for each shift amount when the pair of window ranges are shifted at a predetermined interval, so the correlation value calculation is performed. Can be reduced, while
Within the predetermined range before and after the shift amount of the window range when the highest correlation value is obtained among the correlation values obtained by this, in order to calculate the correlation value for each shift amount of the minimum interval, Distance measurement accuracy does not deteriorate.

[Brief description of drawings]

FIG. 1 is a front perspective view of a camera to which the present invention is applied.

FIG. 2 is a rear perspective view of a camera to which the present invention is applied.

FIG. 3 is a block diagram showing a control unit of a camera to which the present invention is applied.

FIG. 4 is a diagram showing a configuration of a passive AF sensor.

FIG. 5 is a diagram exemplifying a sensor image (AF data) when the distance from the AF sensor to the subject is short.

FIG. 6 is a diagram exemplifying a sensor image (AF data) when a distance from an AF sensor to a subject is long.

FIG. 7 is a flowchart showing an outline of a processing procedure of AF distance measurement in the CPU.

FIG. 8 is a diagram showing divided areas in a sensor area of an R sensor and an L sensor.

FIG. 9 is a flowchart showing a procedure of distance measuring area setting processing.

FIG. 10 is a diagram showing distance measurement areas of 3 area setting and 5 area setting.

FIG. 11 is an explanatory diagram used for explaining an effect when the distance measuring areas are divided and the integration processing is individually performed.

FIG. 12 is an explanatory diagram used for explaining a correlation value calculation.

FIG. 13 is a diagram showing an aspect of a peak selection area set in the AF data acquisition processing.

FIG. 14 is a flowchart showing a procedure of AF data acquisition processing.

FIG. 15 is a flowchart showing a processing procedure of 3-division gain high integration.

FIG. 16 is a diagram showing a signal line between a CPU and an AF sensor.

FIG. 17 is an operation timing chart showing operation timing regarding signal transmission / reception between the CPU and the AF sensor.

FIG. 18 is an explanatory diagram used for explaining peak selection region setting data.

FIG. 19 is an explanatory diagram used for explaining peak selection region setting data.

FIG. 20 is an explanatory diagram used for explaining the peak selection region number data.

FIG. 21 is an explanatory diagram used to describe a procedure for generating peak selection region setting data.

FIG. 22 is an explanatory diagram used to describe a procedure for generating peak selection region setting data.

FIG. 23 is an explanatory diagram used to describe a procedure for generating peak selection region setting data.

FIG. 24 is an explanatory diagram showing peak selection region setting data and peak selection region number data.

FIG. 25 is a diagram showing an output form when the / AFEND signal is not normally output.

FIG. 26 is a diagram exemplifying states of / AFEND signal and MDATA signal when a subject is bright and when it is dark.

FIG. 27 is an explanatory diagram used to describe AF data read processing.

FIG. 28 is an explanatory diagram used for explaining the conventional method and the new method for 2-pixel difference data.

FIG. 29 is a diagram exemplifying 2-pixel difference data (AF data) obtained by the conventional method and the new method.

FIG. 30 is a flowchart showing a processing procedure of a correlation value calculation when AF data is generated during (during) execution of the correlation value calculation.

FIG. 31 is a flowchart showing a processing procedure of correlation value calculation in a case where AF data is generated in advance and stored in a RAM before execution of the correlation value calculation.

FIG. 32 is a diagram showing a data flow when AF data is generated during execution (during execution) of a correlation value calculation.

FIG. 33 is a diagram showing a data flow when AF data is generated in advance and stored in a RAM before execution of a correlation value calculation.

FIG. 34 is a flowchart showing a process of reading sensor data in the conventional method.

FIG. 35 is a timing chart showing an AFCLK signal and an AFDATAP signal when reading sensor data in the conventional method.

FIG. 36 is a flowchart showing a process of reading sensor data in the new method (present invention).

FIG. 37 is an AFCLK signal and AFDATAP at the time of reading sensor data in the new method (present invention).
6 is a timing chart showing signals.

FIG. 38 is a diagram showing a comparison of distance measuring times of the new method (present invention) and the conventional method.

FIG. 39 is an explanatory diagram used for explaining a local minimum value determination process.

FIG. 40 is an explanatory diagram used for explaining a local minimum value determination process.

FIG. 41 is a diagram showing cell positions i of adopted cells in the R window 94B and the L window 96B in every third i operation.

FIG. 42 is a diagram showing an example of a correlation value distribution calculated by a normal calculation.

FIG. 43 is a diagram showing an example of a correlation value distribution calculated by every third i calculation.

FIG. 44 is a diagram showing a recalculation range in every third i calculation.

FIG. 45 is a diagram showing an example of a correlation value distribution when the provisional minimum minimum value detected by every third i calculation is within the short-range warning range.

FIG. 46 is a diagram showing an example of a correlation value distribution when a plurality of local minimum values are detected by normal calculation.

47 is a diagram showing a correlation value distribution obtained when an operation is performed every three i's based on the same AF data as in FIG. 46.

48 is a diagram showing a result of recalculation of the correlation value distribution of FIG. 47.

FIG. 49 is a flowchart showing a processing procedure of a shortage recalculation processing.

50 (A) and 50 (B) exemplify AF data used in the calculation of every third i among the AF data of the R sensor and the L sensor obtained by the 2-pixel difference calculation. FIG.

FIG. 51 is a diagram showing a result of calculating a correlation value f (n) by performing an operation every third i in the example of the AF data of FIGS. 50 (A) and (B).

52 is a diagram showing a result of calculating a correlation value f (n) by performing a normal calculation in the example of the AF data of FIGS. 50 (A) and 50 (B).

FIG. 53 is a diagram showing a correlation value f (n) obtained by computing every third i when the sensor data aspect as shown in FIG. 50 is obtained by actual measurement.

FIG. 54 is an explanatory diagram showing an example of the adopted shift amount n in every nth third calculation.

[FIG. 55] FIG. 55 is an explanatory diagram used to explain how to obtain an adopted shift amount n in every nth third calculation.

[Fig. 56] Fig. 56 is an explanatory diagram used for explaining how to adopt the adopted shift amount n in every n3th calculation.

[FIG. 57] FIG. 57 is an explanatory diagram used for explaining how to take an adopted shift amount n in every nth third calculation.

FIG. 58 is a diagram showing an example of a recalculation range in every n3th calculation shown in FIG. 56;

FIG. 59 is a flowchart showing an overall procedure of a series of contrast detection processing by contrast detection processing 1 and contrast detection processing 2.

FIG. 60 is a diagram showing an example of AF data and correlation value distribution when it is determined by the contrast detection process that distance measurement is impossible.

FIG. 61 is a diagram showing an example of AF data and a correlation value distribution when it is determined by the contrast detection process that distance measurement is impossible.

FIG. 62 is a flowchart showing a procedure of L and R channel difference correction processing in the CPU.

FIG. 63 is a view showing correction of AF data by A of the R sensor.
6 is a flowchart showing a processing procedure when correcting a signal amount difference between F data and AF data of an L sensor.

FIG. 64 is an explanatory diagram used for explaining an effect of the L and R channel difference correction processing.

FIG. 65 is a flowchart showing a processing procedure of AF data correction processing for performing AF data correction in L and R channel difference correction processing by correcting a signal amount difference and a contrast ratio.

66 is an explanatory diagram used for explaining the effect of the AF data correction processing in FIG. 65.

67 is an explanatory diagram used for explaining the effect of the AF data correction processing in FIG. 65.

68 is an explanatory diagram used for explaining the effect of the AF data correction processing in FIG. 65.

69 is an explanatory diagram used for explaining the effect of the AF data correction processing in FIG. 65.

70 is an explanatory diagram used for explaining the effect of the AF data correction processing in FIG. 65.

71 is an explanatory diagram used for explaining the effect of the AF data correction processing in FIG. 65.

72 is an explanatory diagram used for explaining the effect of the AF data correction processing in FIG. 65.

73 is an explanatory diagram used for explaining the effect of the AF data correction processing in FIG. 65.

[Fig. 74] Fig. 74 is an explanatory diagram used for explaining the processing of the minimum value determination.

[Fig. 75] Fig. 75 is an explanatory diagram used for explaining the processing of the minimum value determination.

[FIG. 76] FIG. 76 is an explanatory diagram used for explaining the processing of the minimum value determination.

[Fig. 77] Fig. 77 is an explanatory diagram used for explaining an interpolation value calculation process.

[Fig. 78] Fig. 78 is an explanatory diagram used for explaining the interpolation value calculation process.

[Fig. 79] Fig. 79 is an explanatory diagram used for explaining the interpolation value calculation process.

[Fig. 80] Fig. 80 is an explanatory diagram used for explaining the interpolation value calculation process.

[FIG. 81] FIG. 81 is an explanatory diagram used for describing an interpolation value calculation process.

[FIG. 82] FIG. 82 is an explanatory diagram used to describe an interpolation value calculation process.

[Fig. 83] Fig. 83 is an explanatory diagram used for explaining the calculation processing for each interpolation value.

FIG. 84 is an explanatory diagram used for describing the interpolated-value-based arithmetic processing.

[FIG. 85] FIG. 85 is an explanatory diagram used for explaining the calculation processing for each interpolation value.

FIG. 86 is a flowchart showing a procedure for determining processing types 1 to 3 of the interpolation value normal calculation and the interpolation value-based calculation in the interpolation value calculation processing.

FIG. 87 is a flowchart showing a procedure of fixed focus processing.

FIG. 88 is a flowchart showing a procedure of fixed focus processing.

FIG. 89 is an explanatory diagram used for describing the area selection processing.

[Explanation of symbols]

10 ... Camera, 34 ... Shutter button, 60 ... CPU,
72 ... Strobe device, 74 ... AF sensor, 94 ... R sensor, 96 ... L sensor, 99 ... Processing circuit

   ─────────────────────────────────────────────────── ─── Continued front page    F-term (reference) 2F112 AC03 BA05 CA02 DA28 FA03                       FA05 FA07 FA29 FA36 FA38                       FA41 FA45                 2H011 AA01 BA05 BB02 BB04                 2H051 AA01 BB07 CB20 CE18 CE20                       CE24 DA03 DA07 DA22 DA26

Claims (9)

[Claims] 1. A pair of line sensors consisting of a plurality of light receiving elements forms an image of light from an object to be measured, and a pair of AF data for calculating a correlation value is generated based on signals obtained from the respective light receiving elements. AF data generating means, an AF data acquiring means for acquiring a pair of AF data from a pair of adopted sensor ranges used for distance measurement of the pair of line sensors, and a correlation value within the pair of adopted sensor ranges. A pair of window ranges for obtaining a pair of AF data used for calculation is determined, and correlation values are sequentially calculated while shifting the pair of window ranges to obtain the highest correlation within the pair of adopted sensor ranges. In the correlation value calculating means of No. 1, the shift amount interval of the pair of window ranges in the case of shifting the pair of window ranges by one pixel is defined as the minimum interval. First correlation value calculation means for calculating a correlation value using AF data within the pair of window ranges for each shift amount of the pair of window ranges when the pair of window ranges are shifted at predetermined intervals. And the pair of windows within a predetermined range before and after the shift amount of the window range when the highest correlation value among the correlation values obtained by the first correlation value calculating means is obtained. A second correlation value calculating means for sequentially calculating a correlation value while shifting the range at the minimum interval; and a maximum correlation value among the correlation values obtained by the second correlation value calculating means. A distance measuring object distance calculating means for calculating a distance to a distance measuring object based on a shift amount of a window range. 2. The first correlation value calculating means calculates a correlation value for each shift amount of the minimum interval within a predetermined range in the vicinity of the minimum value and the maximum value of the shift amount of the pair of window ranges. The distance measuring device according to claim 1, wherein 3. The first correlation value calculating means, when there are a plurality of extreme values showing a high correlation by the correlation value calculation in the adopted sensor range, the extreme value having the highest correlation is determined as the temporary first extreme value. Then, the extreme value having the next highest correlation is obtained as the temporary second extreme value, and the second correlation value calculating means determines that the difference between the temporary first extreme value and the temporary second extreme value is within a predetermined reference value. In this case, within the predetermined range before and after the shift amount of the window range when the temporary first extreme value is obtained, and in the window range when the temporary second extreme value is obtained. 3. The distance measuring device according to claim 1, wherein the correlation value calculation is performed within a predetermined range before and after the shift amount is a reference. 4. The second correlation value calculating means has a shift value within the range for performing the correlation value calculation by the second correlation value calculating means, and the correlation value is already calculated by the first correlation value calculating means. Regarding the obtained shift amount, the correlation value obtained by the first correlation value computing means is set as the correlation value obtained by the second correlation value computing means without performing the correlation value computation. The distance measuring device according to claim 1 or 3, which is characterized in that. 5. A shift amount of the window range when the maximum correlation value is obtained by the first correlation value calculating means,
A means for obtaining a difference from the shift amount of the window range when the maximum correlation value is obtained by the second correlation value calculating means, and distance measurement is impossible when the obtained difference is equal to or more than a predetermined shift amount. 3. The distance measuring device according to claim 1, further comprising a determining unit. 6. A shift amount of the window range when the maximum correlation value is obtained by the first correlation value calculating means,
The second correlation value calculating means has a means for obtaining a difference from the shift amount of the window range when the maximum correlation value is obtained, and the second correlation value calculating means has the shift amount of the obtained difference. The distance measuring device according to claim 1 or 2, wherein an additional correlation value calculation is performed by exceeding the predetermined range by the amount. 7. The distance measuring object distance calculating means is the second distance measuring means.
The highest correlation value among the correlation values obtained by the correlation value calculation means, and the shift amount at which the true highest correlation value is obtained by the interpolation value calculation based on the correlation values before and after the correlation value, The distance measuring device according to any one of claims 1 to 5, wherein the distance to the distance measuring object is calculated based on the shift amount. 8. A contrast determination means for determining whether the contrast of a pair of AF data acquired by the AF data acquisition means is higher or lower than a predetermined reference, and a correlation value calculation within the pair of adopted sensor ranges. A pair of window ranges for acquiring a pair of AF data used for the above, and sequentially calculating correlation values while shifting the pair of window ranges to obtain the highest correlation within the pair of adopted sensor ranges. Correlation value calculating means for calculating a correlation value using AF data at predetermined intervals of the AF data within the pair of window ranges.
Within the predetermined range before and after the shift amount of the window range when the highest correlation value among the correlation values obtained by the third correlation value calculation means is obtained. A fourth correlation value calculating means for sequentially calculating the correlation value while shifting the pair of window ranges, the fourth correlation value calculating means using all the AF data within the pair of window ranges.
And the contrast determination means determines that the contrast of the pair of AF data is high, the correlation value computation by the third correlation value computation means and the fourth correlation value computation means is performed. If the contrast determination means determines that the contrast of the pair of AF data is low, the first correlation value calculation means and the second correlation value calculation means
Correlation value calculation means for selectively executing correlation value calculation by the correlation value calculation means, wherein the distance measurement object distance calculation means is the second correlation value calculation means selected and executed by the correlation value calculation selection means. Alternatively, the distance to the object for distance measurement is calculated based on the shift amount of the window range when the highest correlation value is obtained from the correlation values obtained by the fourth correlation value calculation means. 1 or 2 distance measuring device. 9. The pair of adopted sensor ranges is a sensor of the entire distance measuring area of the pair of line sensors, or a sensor of each divided area obtained by dividing the total distance measuring area of the pair of line sensors into a plurality of divided areas. The distance measuring device according to any one of claims 1 to 8.