JP5353141B2 - Program, camera, image processing apparatus, and method of calculating degree of focus of image - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a means for accurately obtaining focusing degree of a picked-up image by processing that is hardly influenced by noise and does not require parameter adjustment. <P>SOLUTION: A program makes a computer execute image reading processing for acquiring the picked-up image, localized area setting processing, structure information arithmetic operation processing, and focusing degree calculation processing. In the localized area setting processing, the computer successively designates two or more pixels under consideration from pixels included in the picked-up image, and also sets a localized area of predetermined size in the picked-up image with the position of each pixel under consideration as reference. In the structure information arithmetic operation processing, the computer obtains an image structure vector showing image structure in the position of each pixel under consideration using gradient information of a pixel value obtained from a plurality of pixels included in the localized area. In the focusing degree calculation processing, the computer obtains the focusing degree in the predetermined position of the picked-up image using information on the image structure vector. <P>COPYRIGHT: (C)2010,JPO&amp;INPIT

Description

The present invention, program, a camera, an image processing apparatus, and a focus degree calculation method of the image.

Conventionally, regarding a digital captured image acquired by an electronic camera or the like, a technique for evaluating the degree of focus of a captured image using an edge amount or a high-frequency component included in a region of interest of the image is known (for example, Patent Literature 1).
JP 2003-274258 A

  However, when obtaining the degree of focus of a captured image using the above-described conventional technique, if the amount of noise included in the image increases, an erroneous detection of the edge amount is likely to occur, and particularly for an image captured with high imaging sensitivity. The evaluation accuracy of the degree of focus can be greatly reduced. Therefore, in order to suppress the influence of noise in the above-described conventional technology, for example, it is complicated to set parameters for noise countermeasures in consideration of imaging sensitivity or to perform noise removal processing according to imaging sensitivity. There is room for improvement in that it requires a special treatment.

  Accordingly, an object of the present invention is to provide means for accurately obtaining the degree of focus of a captured image by processing that is not easily affected by noise and does not require parameter adjustment.

The program according to one aspect specifies an acquisition process for acquiring a captured image, specifies a target pixel from among pixels included in the captured image, and has a predetermined size in the captured image with reference to the position of the target pixel. Using a local area setting process for setting a local area and gradient information of pixel values obtained from a plurality of pixels included in the local area, principal component analysis using the sum of the gradient information in the local area as a variable To solve the eigenvalue problem, a structure information calculation procedure for obtaining an image structure vector indicating an image structure at the position of the target pixel, and information indicating the intensity of the image structure vector obtained from at least two of the target pixels. By performing the comparison, when obtaining a plurality of the captured images in the degree-of-focus calculation process for obtaining the degree of focus at a predetermined position of the captured image, and the image reading process, A determination area setting process for setting a determination area for obtaining the degree of focus in each of the captured images is compared with the degree of focus in the determination area in each of the captured images, and based on the comparison result And causing the computer to execute image selection processing for selecting the captured image.

  In the present invention, the degree of focus of a captured image can be obtained with high accuracy using information of an image structure vector indicating an image structure at a plurality of target pixel positions.

<Description of One Embodiment>
FIG. 1 is a block diagram illustrating a configuration example of an image processing apparatus according to an embodiment. The image processing apparatus according to one embodiment is a personal computer in which an image processing program is installed. The computer 11 constituting the image processing apparatus can evaluate the degree of focus on the input captured image by executing the image processing program.

  The computer 11 includes a data reading unit 12, a storage device 13, a CPU 14, a memory 15, an input / output I / F 16, and a bus 17. The data reading unit 12, the storage device 13, the CPU 14, the memory 15, and the input / output I / F 16 are connected to each other via a bus 17. Further, an input device 18 (keyboard, pointing device, etc.) and a monitor 19 are connected to the computer 11 via an input / output I / F 16. The input / output I / F 16 receives various inputs from the input device 18 and outputs display data to the monitor 19.

  The data reading unit 12 is used when reading captured image data or an image processing program from the outside. For example, the data reading unit 12 communicates with a reading device (such as an optical disk, a magnetic disk, or a magneto-optical disk reading device) that acquires data from a removable storage medium, or an external device in accordance with a known communication standard. It consists of communication devices (USB interface, LAN module, wireless LAN module, etc.) to be performed.

  The storage device 13 stores the image processing program and various data necessary for executing the program. The storage device 13 can also record captured image data acquired from the data reading unit 12. Note that the storage device 13 in one embodiment is configured by a hard disk, a nonvolatile semiconductor memory, or the like.

  The CPU 14 is a processor that comprehensively controls the operation of each part of the computer 11. Further, the CPU 14 obtains an image structure vector indicating an image structure at a predetermined position of the captured image by executing the image processing program. And CPU14 calculates | requires the focus degree of a captured image using the information of this image structure vector (In addition, the content of said arithmetic processing is mentioned later). The memory 15 temporarily stores the calculation result of the image processing program. The memory 15 is composed of, for example, a volatile SDRAM.

  Next, the evaluation of the degree of focus of a captured image by the image processing program of one embodiment will be described.

  In general, noise in a captured image exists regardless of the structure of the image and the direction of the edge, so that the amount of edge due to the noise of the image has no directivity. On the other hand, in a normal captured image, it is known that a strong correlation occurs between pixel values in the structure direction in the local region due to the structure of the image. In the local region, the difference in pixel values in the direction with strong correlation (direction in which the image structure is similar) shows a small value, and the difference in pixel values in the vertical direction with respect to the direction with strong correlation shows a large value. Show.

  For this reason, the image processing program of one embodiment uses the above-described properties to determine the degree of focus of a captured image based on information on an image structure vector indicating an image structure in a local region, which is obtained using a principal component analysis technique. Evaluating.

(Operation example 1 of focus evaluation processing)
Hereinafter, referring to the flowchart of FIG. 2, as an example of the focus degree evaluation process by the image processing program according to the embodiment, an operation example when searching for a portion with a high focus degree in one captured image will be described. To do. 2 is started in response to a program execution instruction from the user.

  Step S <b> 101: The CPU 14 acquires data of a captured image to be evaluated from the outside via the data reading unit 12. The captured image data acquired in S101 is recorded in the storage device 13 or the memory 15 under the control of the CPU 14. Note that the CPU 14 may omit the processing of S101 when captured image data is stored in the storage device 13 in advance.

  Step S102: The CPU 14 designates the position of the pixel of interest X for obtaining the image structure vector from among a plurality of pixels included in the captured image.

  Here, as an example, the CPU 14 in S102 is described as sequentially specifying all pixels of the captured image as the target pixel X. However, the following processing is performed in a small region including predetermined pixels in the captured image. Also good. Note that when changing the position of the pixel of interest X in S102, the CPU 14 sequentially designates the pixel of interest X from left to right one line at a time starting from the upper left corner of the image.

  Step S103: The CPU 14 sets a predetermined local region in the captured image with reference to the position of the target pixel X (see FIG. 3). Although the size and shape of the local area can be set arbitrarily, as an example, the CPU 14 in S103 sets a rectangular area (for example, a 9 × 9 pixel area) centered on the target pixel in the captured image as the local area. To do.

  Step S104: The CPU 14 obtains an image structure vector at the position of the target pixel X using the gradient information of the pixel value of each pixel included in the local region. Here, as an example, the CPU 14 in S104 performs calculation by paying attention to the luminance of the captured image when obtaining the gradient of the pixel value. If the input captured image data is in the YCbCr format, the CPU 14 only needs to obtain the gradient of the pixel value of the Y component. However, if the captured image data is in the RGB format, the CPU 14 determines any pixel value of RGB. The gradient of the pixel value of the Y component may be obtained after color space conversion from RGB to YCbCr.

Next, the CPU 14 in S104 performs calculation processing for obtaining an image structure vector in the following manner. For each pixel x _i in the local region (S103), the gradient of the pixel value is

Can be obtained by solving the eigenvalue problem. However, “C” in the above equation (2) indicates a matrix defined by the following equation (3) using the pixel value f (x) at each pixel x _i in the local region.

Note that “Σ” in Equation (3) above represents the sum of all the pixels included in the local region.

  Further, since the matrix C is a 2 × 2 matrix, the above equation (2) has two eigenvalues and two different unit eigenvectors.

  Step S105: The CPU 14 determines whether or not the current pixel of interest X is at the last position (pixel at the lower right corner of the image). If the above requirement is satisfied (YES side), the process proceeds to S106. On the other hand, if the above requirement is not satisfied (NO side), the CPU 14 returns to S102 and repeats the above operation. Note that the image structure vector information obtained at each position of the captured image is stored in the memory 15 by the NO-side loop in S105.

  Step S106: The CPU 14 uses the information on the image structure vector to obtain the focus evaluation value E at each position of the captured image by either of the following methods (A) or (B) (or a combination of both). Ask.

(A) The CPU 14 obtains a focus evaluation value at each position of the captured image from the eigenvalue λ _s (obtained at S104) indicating the intensity of the image structure vector at the position of each target pixel.

Here, since the eigenvalue λ _s is an amount obtained by squaring the directivity of the image structure, the double root of the eigenvalue λ _s is preferably used as the focus evaluation value. Further, since the eigenvalue λ _s is a value proportional to the number of pixels in the local area, it is preferable to average with the number of pixels in the local area. Therefore, the CPU 14 calculates a focus evaluation value E for each target pixel X by the following equation (4).

Note that “N” in Expression (4) indicates the number of pixels in the local region. It also indicates that the degree of focus of the image increases as the intensity of the image structure vector increases. Therefore, the higher the focus degree of the image at the position of the target pixel is, the higher the focus evaluation value E is.

  (B) The CPU 14 obtains a focus evaluation value E at each position of the captured image based on the correlation of the direction of the image structure vector between adjacent target pixels.

  For a subject that is in focus in the image, since the correlation of the structure in the image is high, the image structure vectors of the pixel of interest and its surrounding pixels are easily oriented in the same direction. On the other hand, for an out-of-focus subject in the image, the image is blurred and the directivity of the structure is lost, and the orientation of the image structure vector is non-uniform compared to the focused state. Therefore, it can be seen that the degree of focus at each position of the image can be evaluated by looking at the correlation of the direction of the image structure vector between adjacent target pixels.

  Step S107: The CPU 14 displays the focus evaluation value distribution obtained in S106 on the monitor 19. Thereby, the user can easily confirm the focused state of the image from the display on the monitor 19.

  As an example, FIG. 4 shows an example of a captured image to be evaluated, and FIG. 5 schematically shows a display screen of a focus evaluation value distribution state. For the sake of simplicity, the subject is represented by a thicker line as the focus evaluation value is higher on the display screen of FIG. FIG. 4 shows an image in which the person in the center is in focus but the background tree is blurred. In this case, in the focus evaluation value display screen shown in FIG. 5, the focus evaluation value of the person is shown as a high value, while the focus evaluation value of the background tree is shown as a low value. Above, description of the flowchart of FIG. 2 is complete | finished.

(Operation example 2 of focus evaluation processing)
Next, referring to the flowchart of FIG. 6, as another example of the focus degree evaluation process of the captured image by the image processing program of the one embodiment, the in-focus state between each image is targeted for a plurality of captured images. An operation example for comparison will be described. Note that the processing in the flowchart of FIG. 6 is also started in response to a program execution instruction from the user.

  Step S201: The CPU 14 acquires data of a plurality of captured images to be evaluated from the outside via the data reading unit 12. Here, as an example, a case is considered in which the CPU 14 sets a captured image group obtained by continuously shooting the same subject as an evaluation target in S201. Note that the content of the processing in S201 substantially corresponds to S101 in FIG.

  Step S202: The CPU 14 designates an image on which the focus evaluation value is calculated among the plurality of captured images. Here, the CPU 14 in S202 sequentially designates all of the plurality of captured images acquired in S201 as calculation targets.

  Step S203: The CPU 14 designates the position of the target pixel X for obtaining the image structure vector from the pixels of the captured image designated in S202.

  Here, as an example, consider a case where the CPU 14 sets a determination region in a part of the captured image based on the position of the focus detection area when the captured image is captured in S203. Then, the target pixel X is sequentially designated from the pixels in the determination area.

  In order to set the determination area, the CPU 14 in S203 acquires position information of a focus detection area at the time of shooting from supplementary information (for example, header information according to the Exif standard) of captured image data. In the example of the process in FIG. 6, the CPU 14 sets a rectangular small area corresponding to the focus detection area in the image as a determination area (see FIG. 7). In addition, it is assumed that the position of the determination region is common between the captured images.

  Step S204: The CPU 14 sets a local area of a predetermined size in the captured image with reference to the position of the target pixel X in the determination area. Note that the content of the processing in S204 corresponds to S103 in FIG.

  Step S205: The CPU 14 obtains an image structure vector at the position of the target pixel X using the gradient information of the pixel value of each pixel included in the local region. Note that the content of the processing in S205 corresponds to S104 in FIG.

  Step S206: The CPU 14 determines whether or not the current target pixel X is the last position in the determination area. If the above requirement is satisfied (YES side), the process proceeds to S207. On the other hand, if the above requirement is not satisfied (NO side), the CPU 14 returns to S203 and repeats the above operation. Note that the image structure vector information obtained at each pixel position in the determination region is stored in the memory 15 by the NO-side loop in S206.

Step S207: The CPU 14 obtains a focus evaluation value E at each pixel position in the determination region of the captured image using information on the image structure vector in the determination region. The CPU 14 in S207 obtains the focus evaluation value E from the intensity (eigenvalue λ _s ) of the image structure vector as in the process in S106 of FIG. 2, or the eigenunit vector between adjacent target pixels. The focus evaluation value E may be obtained from the inner product. For this reason, redundant description of the calculation of the focus evaluation value is omitted.

  Step S208: The CPU 14 determines whether or not all captured images have been processed. If the above requirement is satisfied (YES side), the process proceeds to S209. On the other hand, if the above requirement is not satisfied (NO side), the CPU 14 returns to S202 and repeats the above operation with another unprocessed captured image as a calculation target.

  Step S209: The CPU 14 compares the in-focus evaluation values E in the determination areas of the respective captured images, and selects an image with the highest degree of focus from among all the captured images. For example, the CPU 14 selects an image in which the focus evaluation value E has the maximum value from the group of captured images to be evaluated.

Here, when the focus evaluation value E is obtained from the intensity of the image structure vector, the eigenvalue λ _s is influenced by the luminance value of the image. Therefore, when comparing the focus evaluation value E based on the eigenvalue λ _s between a plurality of captured images having different luminances, the CPU 14 needs to normalize the focus evaluation value E. As an example, CPU 14, as well as obtaining the maximum value lambda _max of the eigenvalues lambda _s of the image structure vectors in any of the captured image, the eigenvalues lambda _s of the image structure vector are divided by the maximum value lambda _max of the all of the captured image Normalization. When the focus evaluation value E is obtained from the inner product of the unique unit vectors between the target pixels, the focus evaluation value E is not affected by the luminance value of the image, and thus it is not necessary to perform the normalization as described above. .

  Step S210: The CPU 14 displays the image selection result in S209 on the monitor 19. For example, the CPU 14 displays the reproduction screen of the captured image selected in S209, information on the file name, and the like on the monitor 19 (the display screen in this case is not shown). Thus, the user can easily pick up a good image that is most in focus on the subject corresponding to the focus detection area from among the plurality of captured images. Above, description of the flowchart of FIG. 6 is complete | finished.

  Hereinafter, the operational effects of the embodiment will be described. In one embodiment, the CPU 14 obtains an image structure vector in a local region of the captured image, and evaluates the degree of focus of the captured image based on the correlation between the strength of the image structure vector and the direction of the image structure vector. Since the above image structure vector is obtained from the gradient of the pixel value in the local region using the principal component analysis method, the influence of noise from the gradient component due to non-directional noise on the above image structure vector is very small. It will be a thing. Therefore, in one embodiment, it is possible to obtain the degree of focus of an image with higher accuracy than the method of obtaining the degree of focus from the edge amount of the image and the high frequency component of the image.

  In one embodiment, it is not necessary to adjust parameters according to the imaging sensitivity of the captured image, and the convenience of the user when the computer 11 evaluates the degree of focus of the captured image is greatly improved.

<Description of other embodiments>
FIG. 8 is a block diagram illustrating a configuration example of an electronic camera according to another embodiment. The electronic camera 21 includes a focusing lens 22, a lens driving unit 23, an image sensor 24, a control unit 25, a ROM 26, a buffer memory 27, a monitor 28, a recording I / F 29, and a release button 30. doing. Here, the lens driving unit 23, the image sensor 24, the ROM 26, the buffer memory 27, the monitor 28, the recording I / F 29, and the release button 30 are connected to the control unit 25, respectively.

  The focusing lens 22 is a lens for performing focus adjustment. The lens position of the focusing lens 22 is adjusted in the optical axis direction by the lens driving unit 23.

  The image sensor 24 captures a subject image formed by an imaging optical system including the focusing lens 22 and generates an image signal of the captured image. The image signal output from the image sensor 24 is input to the control unit 25 via an A / D conversion circuit (not shown).

  Here, in the shooting mode of the electronic camera 21, the image sensor 24 captures a still image (main image) for recording in response to a full press operation of the release button 30. Further, the imaging element 24 in the shooting mode continuously captures images for observation (through images) at predetermined intervals even during standby for shooting. Here, the data of the through image acquired in time series is used for moving image display on the monitor 28 and various arithmetic processes by the control unit 25.

  The control unit 25 is a processor that comprehensively controls the operation of the electronic camera 21. Further, the control unit 25 functions as an image processing unit 31 and a focusing degree evaluation unit 32 by executing a program stored in the ROM 26.

  The image processing unit 31 performs various types of image processing (color interpolation processing, gradation conversion processing, contour enhancement processing, white balance adjustment, color conversion processing, etc.) on the captured image data. Further, the image processing unit 31 can continuously detect the position of the subject to be tracked from the through image input in time series by template matching. Note that the tracking target subject can be any object such as a human being, an animal, or a vehicle.

  As in the first embodiment, the focus degree evaluation unit 32 obtains an image structure vector in each local region of the captured image, and obtains a focus evaluation value using information on the image structure vector.

  The ROM 26 stores a program executed by the control unit 25. An example of the operation in the shooting mode by this program will be described later. The buffer memory 27 temporarily stores image data in a pre-process or post-process of image processing by the image processing unit 31. The buffer memory 27 is composed of SDRAM which is a volatile storage medium. The monitor 28 displays various images according to instructions from the control unit 25.

  The recording I / F 29 is formed with a connector for connecting a nonvolatile storage medium 33. The recording I / F 29 executes data writing / reading with respect to the storage medium 33 connected to the connector. The storage medium 33 includes a hard disk, a memory card incorporating a semiconductor memory, or the like. In FIG. 8, a memory card is illustrated as an example of the storage medium 33.

  The release button 30 receives from the user an instruction input for starting an autofocus (AF) operation before shooting by a half-press operation and an instruction input for starting an imaging operation by a full-press operation.

(Operation example in shooting mode of electronic camera)
Next, an operation example in the shooting mode of the electronic camera 21 of another embodiment will be described with reference to the flowchart of FIG. 9 is started in response to a half-press operation of the release button 30.

  Step S301: The control unit 25 drives the image sensor 24 to capture a through image. The through image data output from the image sensor 24 is input to the control unit 25.

  Step S302: The focus degree evaluation unit 32 designates the position of the target pixel X for obtaining the image structure vector from the determination area corresponding to the focus detection area in the through image (S301).

  Step S303: The focus degree evaluation unit 32 sets a local area of a predetermined size in the through image with the position of the target pixel X as a reference. Note that the content of the processing in S303 corresponds to S103 in FIG.

  Step S304: The focus evaluation unit 32 obtains an image structure vector at the position of the target pixel X using gradient information of pixel values of each pixel included in the local region. Note that the content of the process in S304 corresponds to S104 in FIG.

  Step S305: The focus degree evaluation unit 32 determines whether or not the current target pixel X is the last position in the determination area. If the above requirement is satisfied (YES side), the process proceeds to S306. On the other hand, when the above requirement is not satisfied (NO side), the focus evaluation unit 32 returns to S302 and repeats the above operation.

Step S306: The focus degree evaluation unit 32 obtains a focus evaluation value E in the through image determination region using the information of the image structure vector. The focus degree evaluation unit 32 in S306 obtains the focus evaluation value E from the intensity (eigenvalue λ _s ) of the image structure vector, or between adjacent target pixels, similarly to the process in S106 of FIG. The in-focus evaluation value E may be obtained from the inner product of the eigen unit vectors. For this reason, redundant description of the calculation of the focus evaluation value is omitted.

  Step S307: The focus evaluation unit 32 determines whether or not the lens position of the focusing lens 22 is in focus. Specifically, the focus degree evaluation unit 32 compares the focus evaluation value E with the through image in which the lens position of the focusing lens 22 is front and back. Then, the focusing degree evaluation unit 32 determines that the in-focus state if the focusing evaluation value E at the current lens position is a peak.

  If the above requirement is satisfied (YES side), the process proceeds to S309. On the other hand, if the above requirement is not satisfied (NO side), the process proceeds to S308. When the focus evaluation value E is calculated for the first time, the focus degree evaluation unit 32 in S307 performs a NO determination, and the process proceeds to S308.

  Step S308: The control unit 25 moves the lens position of the focusing lens 22 in a predetermined direction by hill-climbing operation via the lens driving unit 23, and returns to S301 to repeat the above operation. Note that the control unit 25 moves the focusing lens 22 in the same direction when the focus evaluation value increases after the lens position is moved. On the other hand, when the focus evaluation value decreases after the lens position is moved, the control unit 25 moves the focusing lens 22 in the reverse direction.

  Step S309: The control unit 25 determines whether or not the release button 30 has been fully pressed. When the release button 30 is fully pressed (YES side), the process proceeds to S310. On the other hand, when the release button 30 is not fully pressed (NO side), the control unit 25 waits for the release button 30 to be fully pressed.

  Step S <b> 310: The control unit 25 drives the image sensor 24 to execute a main image imaging process. The data of the main image is recorded in the storage medium 33 via the recording I / F 29 after being subjected to predetermined processing by the image processing unit 31. Above, description of the flowchart of FIG. 9 is complete | finished.

  When performing AF control using a through image, the electronic camera 21 of another embodiment evaluates the degree of focus of the image based on the information of the image structure vector as in the case of the first embodiment. Therefore, in the electronic camera 21 according to another embodiment, it is possible to realize a highly accurate AF with less erroneous detection due to noise.

(Modifications of shooting modes in other embodiments)
In the shooting mode of the electronic camera 21 according to another embodiment, the image processing unit 31 can execute subject tracking processing for continuously detecting a tracking target subject from a through image. For example, in response to a half-press of the release button 30, the image processing unit 31 generates a subject template corresponding to the focus detection area from the through image. The image processing unit 31 executes template matching each time a new through image is acquired, and detects a tracking target subject.

  Then, when the subject tracking process is being executed, the focus degree evaluation unit 32 in S302 may set a determination region around the position of the subject to be tracked in each through image. In this case, it is possible to improve the accuracy of AF control during subject tracking.

<Supplementary items of the embodiment>
(1) The apparatus for executing the program of the present invention is not limited to the examples of the computer 11 and the electronic camera 21 of the above-described embodiment, and is a general electronic device having an image display output function (camera mobile phone with camera or image Widely applicable to viewers).

  (2) In each of the above-described embodiments, an example has been described in which various arithmetic processes for obtaining the degree of focus are realized by software using a program. However, these processes may be realized by hardware using an ASIC. It doesn't matter.

  (3) In the other embodiments described above, an example has been described in which the degree of focus of an image is obtained based on information of an image structure vector when the electronic camera 21 performs AF. However, as with the case of the first embodiment, the electronic camera 21 of the other embodiments can of course evaluate the degree of focus using the main image as an evaluation target in a post-processing step after shooting.

  (4) In the process of FIG. 6 described above, the CPU 14 may obtain information on the image structure vector for the entire captured image, as in the case of the process of FIG.

  From the above detailed description, features and advantages of the embodiments will become apparent. It is intended that the scope of the claims extend to the features and advantages of the embodiments as described above without departing from the spirit and scope of the right. Further, any person having ordinary knowledge in the technical field should be able to easily come up with any improvements and modifications, and there is no intention to limit the scope of the embodiments having the invention to those described above. It is also possible to use appropriate improvements and equivalents within the scope disclosed in.

1 is a block diagram illustrating a configuration example of an image processing apparatus according to an embodiment. The flowchart which shows an example of the focusing degree evaluation process of the captured image in one Embodiment Illustration of local region and image structure vector The figure which shows the example of the picked-up image of evaluation object The schematic diagram which shows the example of the display screen of the distribution state of the focus evaluation value corresponding to FIG. The flowchart which shows another example of the focusing degree evaluation process of the captured image in one Embodiment The figure which shows the example of setting of the judgment area The block diagram which shows the structural example of the electronic camera of other embodiment. The flowchart which shows the operation example in the imaging | photography mode of the electronic camera of other embodiment

Explanation of symbols

DESCRIPTION OF SYMBOLS 11 ... Computer, 12 ... Data reading part, 13 ... Memory | storage device, 14 ... CPU, 15 ... Memory, 16 ... Input-output I / F, 17 ... Bus, 18 ... Input device, 19 ... Monitor, 21 ... Electronic camera, 22 DESCRIPTION OF SYMBOLS ... Focusing lens, 23 ... Lens drive part, 24 ... Image pick-up element, 25 ... Control part, 26 ... ROM, 27 ... Buffer memory, 28 ... Monitor, 29 ... Recording I / F, 30 ... Release button, 31 ... Image processing part 32 ... In-focus level evaluation unit 33 ... Storage medium

Claims (8)

An acquisition process for acquiring a captured image;
A local area setting process for designating a target pixel from among pixels included in the captured image and setting a local area of a predetermined size in the captured image with reference to the position of the target pixel;
Using the gradient information of pixel values obtained from a plurality of pixels included in the local region, solving the eigenvalue problem of principal component analysis using the sum of the gradient information in the local region as a variable, the pixel of interest A structure information calculation procedure for obtaining an image structure vector indicating an image structure at the position of
A degree-of-focus calculation process for obtaining a degree of focus at a predetermined position of the captured image by comparing information indicating the intensity of the image structure vector obtained from at least two pixels of interest;
A determination area setting process for setting a determination area for obtaining the degree of focus in each captured image when a plurality of the captured images are acquired in the image reading process;
An image selection process for comparing the degree of focus in the determination region in each captured image and selecting the captured image based on the comparison result;
A program that causes a computer to execute. The program according to claim 1,
In the structure information calculation procedure, the gradient of the pixel value is calculated for the pixel x _i in the local region.
However, “C” in the equation (2) is defined by the following equation (3).
In the program according to claim 1 or 2,
Instead of the focus degree calculation process, a second focus degree calculation process for obtaining the focus degree based on the correlation of the direction of the image structure vector between the adjacent target pixels is provided. program. In the program according to any one of claims 1 to 3,
A focus position information acquisition process for acquiring position information of a focus detection area when the captured image is captured;
In the determination area setting process, the determination area is set based on a position of the focus detection area. In the program according to any one of claims 1 to 4,
A subject tracking process for detecting a subject to be tracked in each of the captured images when acquiring a plurality of the captured images in the image reading process;
In the determination area setting process, the determination area is set based on the position of the subject to be tracked.   A camera comprising a computer that executes the program according to any one of claims 1 to 5. An acquisition step of acquiring a captured image;
A local region setting step of designating a target pixel from among pixels included in the captured image and setting a local region of a predetermined size in the captured image with reference to the position of the target pixel;
By using gradient information of pixel values obtained from a plurality of pixels included in the local region, and solving an eigenvalue problem of principal component analysis using the sum of the gradient information in the local region as a variable, A structure information calculation step for obtaining an image structure vector indicating an image structure at a position;
A degree-of-focus calculation step for obtaining a degree of focus at a predetermined position of the captured image by comparing information indicating the intensity of the image structure vector obtained from at least two of the target pixels; and
A determination area setting process step for setting a determination area for obtaining the degree of focus in each captured image when acquiring a plurality of the captured images in the image reading process;
An image selection processing step of comparing the degree of focus in the determination region in each captured image and selecting the captured image based on the comparison result;
A method for calculating the degree of focus of an image, comprising: An acquisition unit for acquiring a captured image;
A local region setting unit that specifies a target pixel from among pixels included in the captured image, and sets a local region of a predetermined size in the captured image with reference to the position of the target pixel;
Using the gradient information of pixel values obtained from a plurality of pixels included in the local region, solving the eigenvalue problem of principal component analysis using the sum of the gradient information in the local region as a variable, the pixel of interest A structure information calculation unit for obtaining an image structure vector indicating an image structure at a position of
A degree-of-focus calculation unit that obtains a degree of focus at a predetermined position of the captured image by comparing information indicating the intensity of the image structure vector obtained from at least two or more pixels of interest;
A determination area setting unit that sets a determination area for obtaining the degree of focus in each captured image when a plurality of the captured images are acquired in the image reading process;
An image selection unit that compares the degree of focus in the determination region in each captured image and selects the captured image based on the comparison result;
An image processing apparatus comprising: