JP2006333205A - Imaging apparatus, image processing method and image processing program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To obtain desirable photographed image data on the basis of a calculated index by calculating the index representing a photographing scene from divided photometric data with high accuracy. <P>SOLUTION: A processor 31 of this imaging apparatus 1 is provided with a whole image acquisition part 101 for acquiring the whole image obtained by preliminary photographing as a divided image composed of a plurality of divided areas; a color information acquisition part 102 for acquiring color information about each divided area of the whole image; an occupancy ratio calculating part 103 for dividing each divided area into prescribed classes constituted of a combination of lightness and hue on the basis of the acquired color information and calculating a first occupancy ratio showing a ratio at which a divided area belonging to each divided class occupies the whole image for the divided class; and an index calculating part 104 for calculating a first index and a second index for specifying a photographic scene by multiplying the first occupancy ratio by two types of different coefficients preset in accordance with a photographing condition. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to an imaging apparatus, an image processing method, and an image processing program.

  In recent years, photographed image data obtained by photographing with a digital camera (including those incorporated in devices such as mobile phones and laptop computers) is directly transmitted to an inkjet printer or the like without using a personal computer or the like. A standard (CIPA DC-001) called PictBridge that performs output has been proposed. However, when the captured image data obtained by photographing with a general digital camera is unfavorable image data such as a backlight image or an under image, a favorable print cannot be obtained even if the print output is performed as it is. Therefore, it is desired to perform appropriate exposure control and gradation correction in the digital camera. For this reason, there is a method in which the situation of the shooting scene is determined using the divided photometric data in the digital camera, and the exposure level is adjusted and the gradation conversion characteristics are changed based on the determination result to obtain appropriate image data. Proposed.

For example, in the method described in Patent Document 1, a plurality of average luminance information obtained by averaging the luminance information for each divided region obtained by the photometric means in at least one of the row direction and the column direction is obtained, Backlight discrimination is performed by calculating the brightness change tendency, and the exposure correction amount is calculated from the slope of the average luminance value within the shooting range. Further, in the method described in Patent Document 2, subject information such as in-screen contrast strength and luminance distribution state is obtained from the divided photometry results, and tone conversion characteristics of image data are optimized from the subject information. .
JP 2002-296635 A JP 2001-54014 A

  However, in the method described in Patent Document 1, it is possible to correctly determine backlight in the case of typical backlight shooting, but since only luminance information is used, the shooting scene is correctly corrected unless the typical composition is applied. There was a problem that could not be determined. In Patent Document 1, the exposure correction amount is calculated from the slope of the average luminance value, but it does not necessarily take into account the brightness of the main subject, and does not quantitatively represent the shooting scene. There was a problem. Further, in the method described in Patent Document 2, the tone conversion characteristics are changed depending on the contrast strength. However, since the shooting scene cannot be determined with high accuracy, an appropriate tone cannot be selected according to the shooting scene. There was a problem.

  An object of the present invention is to calculate an index representing a shooting scene with high accuracy from divided photometric data, and to obtain preferable captured image data based on the calculated index.

In order to solve the above-described problem, the invention according to claim 1 is an acquisition unit that acquires an entire image obtained by preliminary shooting as a divided image composed of a plurality of divided regions;
Color information acquisition means for acquiring color information for each divided region of the entire image;
Based on the color information acquired by the color information acquisition means, each of the divided areas is classified into a predetermined class composed of a combination of lightness and hue, and for each classified class, the divided areas belonging to the class are An occupancy ratio calculating means for calculating a first occupancy ratio indicating a ratio of the entire image;
A first index (index 1) and a second index (index) for specifying a shooting scene are obtained by multiplying the first occupation ratio by two different coefficients set in advance according to shooting conditions. And an index calculating means for calculating 2).

The invention according to claim 2 is an acquisition means for acquiring the whole image obtained by the preliminary photographing as a divided image composed of a plurality of divided regions;
Color information acquisition means for acquiring color information for each divided region of the entire image;
Based on the color information acquired by the color information acquisition means, each of the divided areas is classified into a predetermined class composed of a combination of lightness and hue, and for each classified class, the divided areas belonging to the class are A first occupancy ratio indicating a ratio of the entire image is calculated, and each of the divided regions is classified into a predetermined class composed of a combination of a distance from the outer edge of the screen of the entire image and brightness, and the classified class An occupancy ratio calculating means for calculating a second occupancy ratio indicating the ratio of the divided area belonging to the class to the entire image for each time;
The first occupancy is multiplied by a coefficient set in advance according to shooting conditions to calculate a first index (index 1, index 2) for specifying a shooting scene, and the second And an index calculation means for calculating a second index (index 3) for specifying the shooting scene by multiplying the occupation rate of the image by a coefficient set in advance according to the shooting conditions. Yes.

  A third aspect of the present invention is the imaging apparatus according to the first or second aspect, wherein the difference between the average luminance value of the skin color at the center of the screen of the whole image and the maximum luminance value and the average luminance value of the whole image. It is characterized by comprising third index calculating means for calculating a third index (index 4) for specifying a shooting scene by multiplying each value by a coefficient set in advance according to the shooting conditions. Yes.

  According to a fourth aspect of the present invention, in the imaging apparatus according to any one of the first to third aspects, based on at least the first index and the second index among the calculated indices. It is characterized by comprising a photographing control means for adjusting the exposure level and performing actual photographing at the adjusted exposure level.

  According to a fifth aspect of the present invention, in the imaging device according to any one of the first to fourth aspects, based on at least the first index and the second index among the calculated indices. Further, the image processing apparatus is characterized by comprising gradation adjustment determining means for determining a gradation adjustment method for photographed image data obtained by actual photographing.

  According to a sixth aspect of the present invention, in the imaging apparatus according to any one of the first to fifth aspects, based on at least the first index and the second index among the calculated indices. And a discriminating means for discriminating a photographing scene of the whole image.

  According to a seventh aspect of the present invention, in the imaging apparatus according to any one of the first to sixth aspects, the predetermined class is in the highest lightness class than the lightness range in the lowest lightness class. It is characterized by a wider range of brightness.

  According to an eighth aspect of the present invention, in the imaging apparatus according to the seventh aspect, the predetermined class has at least three classes within 10% of the maximum brightness value.

The invention according to claim 9 is an acquisition step of acquiring the whole image obtained by the preliminary shooting as a divided image composed of a plurality of divided regions;
For each divided region of the entire image, a color information acquisition step for acquiring color information;
Based on the color information acquired by the color information acquisition step, the divided areas are classified into predetermined classes composed of combinations of brightness and hue, and for each classified class, the divided areas belonging to the class are An occupancy ratio calculating step of calculating a first occupancy ratio indicating the ratio of the entire image;
A first index (index 1) and a second index (index) for specifying a shooting scene are obtained by multiplying the first occupation ratio by two different coefficients set in advance according to shooting conditions. And 2) an index calculation step for calculating (2).

The invention according to claim 10 is an acquisition step of acquiring an entire image obtained by preliminary shooting as a divided image composed of a plurality of divided regions;
For each divided region of the entire image, a color information acquisition step for acquiring color information;
Based on the color information acquired by the color information acquisition step, the divided areas are classified into predetermined classes composed of combinations of brightness and hue, and for each classified class, the divided areas belonging to the class are A first occupancy ratio indicating a ratio of the entire image is calculated, and each of the divided regions is classified into a predetermined class composed of a combination of a distance from the outer edge of the screen of the entire image and brightness, and the classified class An occupancy ratio calculating step for calculating a second occupancy ratio indicating the ratio of the divided area belonging to the class to the entire image for each time;
The first occupancy is multiplied by a coefficient set in advance according to shooting conditions to calculate a first index (index 1, index 2) for specifying a shooting scene, and the second And an index calculation step of calculating a second index (index 3) for specifying the shooting scene by multiplying the occupation rate of the image by a coefficient set in advance according to the shooting conditions. Yes.

  The invention according to claim 11 is the image processing method according to claim 9 or 10, wherein the average luminance value of the skin color at the center of the screen of the whole image, and the maximum luminance value and the average luminance value of the whole image. A third index calculating step of calculating a third index (index 4) for specifying a shooting scene by multiplying each of the difference values by a coefficient set in advance according to the shooting conditions; It is said.

  The invention according to claim 12 is the image processing method according to any one of claims 9 to 11, based on at least the first index and the second index among the calculated indices. A shooting control step of adjusting the exposure level and performing actual shooting at the adjusted exposure level.

  The invention according to claim 13 is the image processing method according to any one of claims 9 to 12, based on at least the first index and the second index among the calculated indices. And a gradation adjustment determining step for determining a gradation adjustment method for the captured image data obtained by the actual photographing.

  The invention according to claim 14 is the image processing method according to any one of claims 9 to 13, based on at least the first index and the second index among the calculated indices. And a discriminating step for discriminating a photographing scene of the whole image.

  The invention according to claim 15 is the image processing method according to any one of claims 9 to 14, wherein the predetermined class is a class having the highest brightness than a range of brightness in the class having the lowest brightness. It is characterized by a wider range of brightness.

  According to a sixteenth aspect of the present invention, in the image processing method according to the fifteenth aspect, the predetermined class has at least three classes within 10% of the maximum brightness value.

The invention according to claim 17 is a computer for executing image processing.
An acquisition function for acquiring an entire image obtained by preliminary shooting as a divided image composed of a plurality of divided areas;
For each divided area of the entire image, a color information acquisition function for acquiring color information;
Based on the color information acquired by the color information acquisition function, each of the divided areas is classified into a predetermined class consisting of a combination of lightness and hue, and for each classified class, the divided areas belonging to the class are An occupancy ratio calculation function for calculating a first occupancy ratio indicating the ratio of the entire image;
A first index (index 1) and a second index (index) for specifying a shooting scene are obtained by multiplying the first occupation ratio by two different coefficients set in advance according to shooting conditions. 2 is an image processing program for realizing an index calculation function for calculating 2).

The invention according to claim 18 is a computer for executing image processing.
An acquisition function for acquiring an entire image obtained by preliminary shooting as a divided image composed of a plurality of divided areas;
For each divided area of the entire image, a color information acquisition function for acquiring color information;
Based on the color information acquired by the color information acquisition function, each of the divided areas is classified into a predetermined class consisting of a combination of lightness and hue, and for each classified class, the divided areas belonging to the class are A first occupancy ratio indicating a ratio of the entire image is calculated, and each of the divided regions is classified into a predetermined class composed of a combination of a distance from the outer edge of the screen of the entire image and brightness, and the classified class An occupancy ratio calculation function for calculating a second occupancy ratio indicating the ratio of the divided area belonging to the class to the entire image for each time;
The first occupancy is multiplied by a coefficient set in advance according to shooting conditions to calculate a first index (index 1, index 2) for specifying a shooting scene, and the second An image for realizing an index calculation function for calculating a second index (index 3) for specifying a shooting scene by multiplying the occupation rate of the image by a coefficient set in advance according to shooting conditions It is a processing program.

  The invention according to claim 19 is the image processing program according to claim 17 or 18, wherein an average luminance value of a skin color in a central portion of the screen of the whole image, a maximum luminance value and an average luminance value of the whole image are obtained. It has a third index calculation function for calculating a third index (index 4) for specifying a shooting scene by multiplying each difference value by a coefficient set in advance according to shooting conditions. It is said.

  The invention according to claim 20 is the image processing program according to any one of claims 17 to 19, based on at least the first index and the second index among the calculated indices. It is characterized by having a shooting control function for adjusting the exposure level and performing actual shooting at the adjusted exposure level.

  The invention according to claim 21 is the image processing program according to any one of claims 17 to 20, based on at least the first index and the second index among the calculated indices. Thus, it has a gradation adjustment determination function for determining a gradation adjustment method for photographed image data obtained by actual photographing.

  According to a twenty-second aspect of the present invention, in the image processing program according to any one of the seventeenth to twenty-first aspects, based on at least the first index and the second index among the calculated indices. And having a discrimination function for discriminating the shooting scene of the whole image.

  The invention according to claim 23 is the image processing program according to any one of claims 17 to 22, wherein the predetermined class is a class having the highest brightness than the range of brightness in the class having the lowest brightness. It is characterized by a wider range of brightness.

  According to a twenty-fourth aspect of the present invention, in the image processing program according to the twenty-third aspect, the predetermined class has at least three classes within 10% of the maximum brightness value.

  According to the invention described in claims 1 to 3, 9 to 11, and 17 to 19, it is possible to calculate an index that represents a shooting scene with high accuracy from an entire image obtained by preliminary shooting.

  According to the fourth, twelfth, and twentieth aspects of the present invention, since the index that represents the shooting scene with high accuracy is used, the exposure for the main shooting can be adjusted accurately.

  According to the inventions of the fifth, thirteenth and twenty-first aspects, since the index representing the shooting scene with high accuracy is used, the gradation adjustment method for the shot image data obtained by the main shooting can be accurately determined. it can.

  According to the invention described in claims 6, 14, and 22, it is possible to discriminate the shooting scene with high accuracy from the whole image obtained by the preliminary shooting.

  According to the seventh, eighth, fifteenth, sixteenth, twenty-third, and twenty-fourth aspects of the present invention, even in the case of linear image data, the separation of the lower lightness class is improved, and the photographic scene can be determined with high accuracy.

Hereinafter, embodiments of the present invention will be described with reference to the drawings.
First, the configuration in the present embodiment will be described.

  FIG. 1A shows a front view of the imaging apparatus 1 according to the embodiment of the present invention, and FIG. 1B shows a rear view of the imaging apparatus 1. The imaging device 1 is, for example, a digital camera, and has a cross key 22, a photographing optical system 23, a flash 24, a viewfinder 25, and a power switch 26 on or inside a housing 21 made of a material such as metal or synthetic resin. A display unit 27 and a release button 28 are provided.

  FIG. 2 shows an internal configuration of the imaging apparatus 1. As shown in FIG. 2, the imaging apparatus 1 includes a processor 31, a memory 32, an imaging element 33 such as a CCD (Charge Coupled Device), a shutter unit 34, an aperture unit 35, and a display unit 27.

  The cross key 22 is made up of buttons in four directions, up, down, left, and right, and is for the user to select or set various modes.

  The photographing optical system 23 includes a plurality of lenses, a lens barrel, and the like, and has a zoom function. The photographing optical system 23 causes the light received by the lens to form an image on the image sensor 33. The flash 24 emits auxiliary light by a control signal from the processor 31 when the subject brightness is low.

  The viewfinder 25 is used for the user to check the shooting target and shooting area by eye contact. The power switch 26 is a switch for operating ON / OFF of the operation in the imaging apparatus 1.

  The display unit 27 includes a liquid crystal panel, and displays an image currently captured on the image sensor 33, an image captured in the past, a menu screen, a setting screen, and the like according to a display control signal input from the processor 31.

  The release button 28 is a two-stage push-in switch that is provided on the upper surface of the housing 21 and can detect a half-pressed state (preliminary shooting) and a fully-pressed state (main shooting) by the user.

  FIG. 3 shows the internal configuration of the processor 31. The processor 31 controls the operation of each unit of the imaging apparatus 1, and as shown in FIG. 3, the whole image acquisition unit 101, the color information acquisition unit 102, the occupation rate calculation unit 103, the index calculation unit 104, the shooting scene The determination unit 105, the imaging control unit 106, and the gradation adjustment determination unit 107 are configured.

  The entire image acquisition unit 101 acquires image data of the latest entire image (entire image obtained by preliminary shooting) captured on the image sensor 33 at the timing when the release button 28 is half-pressed. Then, the entire image is divided into N × M rectangular regions (regions equally divided into M pieces in the vertical direction and N pieces in the horizontal direction). FIG. 4A shows an example of the entire image, and FIG. 4B shows an example in which the entire image is divided into 11 × 7 areas. The number of divided areas is not particularly limited. In the present embodiment, each region obtained by the division is referred to as a “cell”.

  The color information acquisition unit 102 acquires color information of each cell. A method of acquiring color information by the color information acquisition unit 102 will be described in detail later with reference to FIGS.

  Based on the color information acquired by the color information acquisition unit 102, the occupancy rate calculation unit 103 classifies each cell of the entire image into a predetermined class consisting of a combination of brightness and hue (see FIG. 10) and is classified. For each class, a first occupation ratio indicating a ratio of cells belonging to the class to the entire image is calculated. Further, the occupancy rate calculation unit 103 classifies each cell into a predetermined class composed of a combination of the distance from the outer edge of the screen of the entire image and the brightness (see FIG. 11), and assigns each cell to the class. A second occupancy ratio indicating the ratio of the cell to which the cell belongs to the entire image is calculated. The occupation rate calculation process executed in the occupation rate calculation unit 103 will be described in detail later with reference to FIG.

  The index calculation unit 104 multiplies the first occupancy calculated by the occupancy calculation unit 103 by a coefficient set in advance according to the shooting conditions, thereby specifying a first index ( Index 1 and index 2) are calculated. In addition, the index calculation unit 104 multiplies the second occupancy calculated by the occupancy rate calculation unit 103 by a coefficient set in advance according to the shooting conditions, thereby specifying a second photographic scene. An index (index 3) is calculated. Further, the index calculation unit 104 multiplies the average luminance value in the central portion of the entire image and the difference value between the maximum luminance value and the average luminance value by a coefficient set in advance according to the shooting conditions. Then, a third index (index 4) for specifying the shooting scene is calculated.

  In addition, the index calculation unit 104 multiplies the average luminance value (index 4 ′) of the skin color area in the center of the entire image screen by the coefficients set in advance according to the shooting conditions. Then, a new index 5 is calculated by calculating the sum. Further, the index calculation unit 104 calculates a new index 6 by multiplying the average luminance value, the index 2 and the index 3 by a coefficient set in advance according to the shooting conditions, and taking the sum. . The index calculation process executed in the index calculation unit 104 will be described in detail later with reference to FIG.

  The shooting scene determination unit 105 determines the shooting scene of the entire image obtained by the preliminary shooting based on each index calculated by the index calculation unit 104. Here, the shooting scene indicates a light source condition when shooting a subject such as a follow light, a backlight, a proximity flash, and the like, and is a main subject (mainly a person, but is not limited thereto). This includes the over and under degrees. The method for determining the shooting scene will be described later in detail.

  The shooting control unit 106 adjusts the exposure level necessary for the actual shooting based on each index (indexes 4 to 6) calculated by the index calculation unit 104 and the determination result in the shooting scene determination unit 105 ( FIG. 18).

  The gradation adjustment determination unit 107 determines a gradation adjustment method (see FIG. 20) for the captured image data obtained by the actual shooting based on the shooting scene determined by the shooting scene determination unit 105. In addition, the gradation adjustment determination unit 107 determines a gradation adjustment amount for gradation adjustment with respect to the captured image data obtained by the actual photographing based on each index calculated by the index calculation unit 104. A method for determining the gradation adjustment amount will be described in detail later.

  The processing of each unit in the processor 31 is basically performed by hardware processing, but a part thereof is performed by software processing such as executing a program stored (saved) in the memory 32.

  Returning to FIG. 2, the memory 32 stores (saves) image data obtained by photographing. In addition, the memory 32 stores various processing programs executed in the imaging apparatus 1, data used in the processing programs, and the like.

  The image sensor 33 converts the imaged light into electric charges. Thereby, for example, image data as shown in FIG. 4A is obtained. This image includes an object in the imaging range (imaging range), that is, an imaging object (imaging target) and other objects (background). Hereinafter, such an image of the entire photographing range is referred to as an “entire image”. The RGB value of each pixel of the entire image is represented by, for example, 256 gradations.

  The shutter unit 34 controls the timing of resetting the image sensor 33 and the timing of charge conversion based on the state (half-pressed state or fully-pressed state) detected by the release button 28. Adjustment of the amount of light received by the image sensor 33 is performed by the aperture unit 35 and / or the shutter unit 34.

Next, the operation in this embodiment will be described.
Hereinafter, the photographing object is referred to as “main subject”.
First, the overall flow of processing executed by the imaging apparatus 1 will be described with reference to the flowchart of FIG.

  First, when the power switch 26 is turned on (when the power is turned on), preprocessing such as resetting of the memory 32 is performed (step S1). The user directs the imaging device 1 toward the main subject so that the main subject enters the field of the imaging device 1, and starts an operation for photographing. When the release button 28 is pressed halfway (step S2; YES), preliminary shooting is performed, and image data of the entire image obtained by the preliminary shooting is acquired as a divided image composed of a plurality of divided regions (step S3). ).

  Next, information about the lens is acquired (step S4), and switch information such as mode and switch setting is acquired (step S5). Next, based on the data (information) acquired in steps S3 to S5, a shooting scene determination process for determining the shooting scene of the entire image is performed (step S6). The shooting scene determination process in step S6 will be described later with reference to FIG.

  Next, an exposure level adjustment process for adjusting an exposure level necessary for the actual photographing is performed based on each index obtained in the photographing scene discrimination process of step S6 and the discrimination result of the photographing scene (step S7). The exposure level adjustment process in step S7 will be described later with reference to FIG.

  In parallel with the processes in steps S4 to S7, the entire image acquired in step S3 is displayed on the display unit 27 (step S8). When other conditions for main shooting are met and standby is completed (S9; YES), and the release button 28 is fully pressed (step S10; YES), operation processing for main shooting is performed (step S11). . In step S11, image data (captured image data) of the entire image when the release button 28 is fully pressed is acquired and recorded on a storage recording medium (such as an SD memory card or a multimedia card (MMC)). Is done. Also, the captured image data obtained by the actual photographing is displayed on the display unit 27.

  Next, gradation conversion processing is performed on the captured image data (step S12). While the power switch 26 is ON, the process returns to step S1, and when the release button 28 is pressed halfway again by the user, the processes of steps S3 to S12 are repeated. On the other hand, when the power switch 26 is turned off (step S13; YES), the operation in the imaging device 1 is finished.

  Next, with reference to the flowchart of FIG. 6 and FIGS. 7 to 17, the photographing scene determination process (step S6 of FIG. 5) will be described.

  As shown in FIG. 6, the shooting scene determination process includes a color space conversion process (step S20), an occupation ratio calculation process (step S21), an index calculation process (step S22), and a shooting scene determination (step S23). Composed. Hereinafter, each process illustrated in FIG. 6 will be described in detail with reference to FIGS.

  First, the color space conversion process (step S20 in FIG. 6) will be described with reference to the flowchart in FIG.

  First, information indicating the RGB value, luminance value, and white balance of each cell of the entire image obtained by preliminary shooting is acquired (step S25). These values are average values such as the RGB value and the luminance value of each pixel included in the cell, and can be easily obtained by a known hardware process. As the luminance value, a value calculated by substituting RGB values into a known conversion formula may be used.

  Next, the RGB values acquired in step S25 are converted into the HSV color system, and color information of the entire image is acquired (step S26). The HSV color system represents the three elements of image data: Hue, Saturation, and Lightness (Value or Brightness), and was devised based on the color system proposed by Munsell. It has been done.

  FIG. 8 shows an example of a conversion program (HSV conversion program) that obtains hue, saturation, and lightness by converting from RGB to the HSV color system in program code (c language). In the HSV conversion program shown in FIG. 8, the values of digital image data as input image data are defined as InR, InG, and InB, the calculated hue value is defined as OutH, the scale is defined as 0 to 360, and the saturation The value is OutS, the brightness value is OutV, and the unit is defined as 0 to 255.

  In this embodiment, “brightness” means “brightness” generally used unless otherwise noted. In the following description, V (0 to 255) of the HSV color system is used as “brightness”, but a unit system representing the brightness of any other color system may be used. At that time, it goes without saying that numerical values such as various coefficients described in the present embodiment are recalculated.

  In the present embodiment, “hue” means “color” that is generally used unless otherwise noted. In the following description, H (0 to 360) of the HSV color system is used as “hue”, but for example, a color represented by a red difference value (Cr) or a blue difference value (Cb) may be used. At that time, it goes without saying that numerical values such as various coefficients described in the present embodiment are recalculated. In the color information acquisition unit 102, the values of H, S, and V obtained as described above are acquired as color information.

  Next, the occupation rate calculation process (step S21 in FIG. 6) will be described with reference to the flowchart in FIG.

  First, based on the HSV value calculated in the color space conversion process, each cell of the entire image is classified into a predetermined class composed of a combination of hue and brightness, and the cumulative number of cells is calculated for each classified class. Thus, a two-dimensional histogram is created (step S30).

  FIG. 10 shows a class composed of a combination of brightness and hue. In step S30, the lightness (V) has lightness values of 0 to 5 (v1), 6 to 12 (v2), 13 to 24 (v3), 25 to 76 (v4), 77 to 109 (v5), 110 to It is divided into seven areas 149 (v6) and 150 to 255 (v7). As shown in FIG. 10, the brightness range in the highest brightness class is wider than the brightness range in the lowest brightness class.

Hue (H) is a skin hue hue area (H1 and H2) with a hue value of 0 to 39, 330 to 359, a green hue area (H3) with a hue value of 40 to 160, and a blue hue area with a hue value of 161 to 250 It is divided into four areas (H4) and a red hue area (H5). Note that the red hue region (H5) is not used in the following calculation because it is found that the contribution to the discrimination of the shooting scene is small. The flesh-color hue area is further divided into a flesh-color area (H1) and other areas (H2). Hereinafter, among the flesh-colored hue areas (H = 0 to 39, 330 to 359), the hue '(H) that satisfies the following formula (1) is defined as the flesh-colored area (H1), H2).
10 <Saturation (S) <175;
Hue '(H) = Hue (H) + 60 (when 0 ≤ Hue (H) <300);
Hue '(H) = Hue (H)-300 (when 300 ≤ Hue (H) <360).
Luminance (Y) = InR x 0.30 + InG x 0.59 + InB x 0.11 (A)
As
Hue '(H) / Luminance (Y) <3.0 × (Saturation (S) / 255) +0.7 (1)

  Therefore, the number of classes in the entire image is 4 × 7 = 28. Further, it has at least three classes (v1, v2, v3) within 10% of the maximum brightness value (255). In addition, it is also possible to use the brightness (V) in Formula (A) and Formula (1).

  After step S30, each cell of the entire image is classified into a predetermined class composed of a combination of the distance from the outer edge of the screen and the brightness, and a two-dimensional histogram is created by calculating the cumulative number of cells for each classified class. (Step S31).

  FIG. 11A shows three regions n1 to n3 divided in step S31 according to the distance from the outer edge of the screen of the entire image. The region n1 is an outer frame, the region n2 is a region inside the outer frame, and the region n3 is a central region of the entire image. In step S31, the brightness is divided into seven regions v1 to v7 as described above. FIG. 11B shows a class composed of combinations of three regions n1 to n3 and brightness. As shown in FIG. 11B, the number of classes when the entire image is classified into classes composed of combinations of the distance from the outer edge of the screen and the brightness is 3 × 7 = 21.

When a two-dimensional histogram is created in step S30, a first occupancy ratio indicating a ratio of the cumulative cell number calculated for each predetermined class composed of a combination of brightness and hue to the total cell number (N × M cells) Is calculated (step S32). If the first occupancy calculated in the class composed of the combination of the brightness area vi and the hue area Hj is Rij, the first occupancy in each class is expressed as shown in Table 1.

なお、各セルを画面の外縁からの距離、明度及び色相からなる階級に分類し、分類された階級毎に累積セル数を算出することによって３次元ヒストグラムを作成してもよい。以下では、２次元ヒストグラムを用いる方式を採用するものとする。 When the two-dimensional histogram is created in step S31, the second occupancy ratio indicating the ratio of the cumulative cell number calculated for each predetermined class composed of the combination of the distance from the outer edge of the screen and the brightness to the total cell number is calculated. (Step S33), the occupancy rate calculation process ends. If the second occupancy calculated in each class composed of the combination of the brightness area vi and the screen area nj is Qij, the second occupancy in each class is expressed as shown in Table 2.

Note that a three-dimensional histogram may be created by classifying each cell into a class composed of the distance from the outer edge of the screen, brightness, and hue, and calculating the cumulative number of cells for each class. Hereinafter, a method using a two-dimensional histogram is adopted.

  Next, the index calculation process (step S22 in FIG. 6) will be described with reference to the flowchart in FIG.

  First, the first occupancy ratio calculated for each class in the occupancy ratio calculation process is multiplied by two different coefficients (first coefficient and second coefficient) set in advance according to the shooting conditions. By taking the above, index 1 and index 2 for specifying the shooting scene are calculated (step S40). The index 1 is an index representing the degree of overshoot of the main subject, and is for separating only the image that should be determined as “the main subject is over” from other shooting scenes. The index 2 is an index that compositely represents the characteristics at the time of backlight shooting such as sky blue high brightness and low face color brightness, and only images that should be determined as “backlight” and “main subject is under” are taken from other shooting scenes. It is for separation.

Hereinafter, the calculation method of the index 1 and the index 2 will be described in detail.
Table 3 shows the first coefficient necessary for calculating the index 1 by class. The coefficient of each class shown in Table 3 is a weighting coefficient by which the first occupation ratio Rij of each class shown in Table 1 is multiplied, and is set in advance according to the shooting conditions.

  According to Table 3, a positive (+) coefficient is used for the first occupancy calculated from the area distributed in the skin color hue area (H1) of high brightness (v6), and the other hue is blue. A negative (−) coefficient is used for the first occupation ratio calculated from the hue region. FIG. 13 shows the first coefficient in the skin color area (H1) and the first coefficient in the other area (green hue area (H3)) as a curve (coefficient curve) that changes continuously over the entire brightness. It is shown. According to Table 3 and FIG. 13, in the region of high brightness (V = 77 to 150), the sign of the first coefficient in the skin color region (H1) is positive (+), and other regions (for example, the green hue region) The sign of the first coefficient in (H3)) is negative (-), and it can be seen that the signs of the two are different.

従って、H1〜H4領域の和は、下記の式(2-1)〜(2-4)のように表される。
H1領域の和＝R11×0＋R21×0＋（中略）...＋R71×(-8) (2-1)
H2領域の和＝R12×(-2)＋R22×(-1)＋（中略）... ＋R72×(-10) (2-2)
H3領域の和＝R13×5＋R23×(-2)＋（中略）...＋R73×(-12) (2-3)
H4領域の和＝R14×0＋R24×(-1)＋（中略）...＋R74×(-12) (2-4) When the first coefficient in the lightness region vi and the hue region Hj is Cij, the sum of the Hk regions for calculating the index 1 is defined as in Expression (2).

Accordingly, the sum of the H1 to H4 regions is expressed by the following formulas (2-1) to (2-4).
H1 area sum = R11 x 0 + R21 x 0 + (omitted) ... + R71 x (-8) (2-1)
Sum of H2 area = R12 x (-2) + R22 x (-1) + (omitted) ... + R72 x (-10) (2-2)
Sum of H3 area = R13 x 5 + R23 x (-2) + (omitted) ... + R73 x (-12) (2-3)
Sum of H4 area = R14 x 0 + R24 x (-1) + (omitted) ... + R74 x (-12) (2-4)

The index 1 is defined as Expression (3) using the sum of the H1 to H4 regions shown in Expressions (2-1) to (2-4).
Index 1 = sum of H1 area + sum of H2 area + sum of H3 area + sum of H4 area + 1.5 (3)

Table 4 shows the second coefficient necessary for calculating the index 2 by class. The coefficient of each class shown in Table 4 is a weighting coefficient by which the first occupation ratio Rij of each class shown in Table 1 is multiplied, and is set in advance according to the shooting conditions.

  According to Table 4, a negative (-) coefficient is used for the occupancy calculated from the areas (v4, v5) distributed in the intermediate brightness of the flesh hue area (H1), and the low brightness of the flesh hue area (H1). A coefficient of 0 is used for the occupation ratio calculated from the (shadow) region (v2, v3). FIG. 14 shows the second coefficient in the skin color region (H1) as a curve (coefficient curve) that continuously changes over the entire brightness. According to Table 4 and FIG. 14, the sign of the second coefficient of the intermediate lightness region having a lightness value of 25 to 150 in the flesh color hue region is negative (−), and the low lightness (shadow) region having a lightness value of 6 to 24 The second coefficient is 0, and it can be seen that there is a large difference between the coefficients in both regions.

従って、H1〜H4領域の和は、下記の式(4-1)〜(4-4)のように表される。
H1領域の和＝R11×0＋R21×0＋（中略）...＋R71×2 (4-1)
H2領域の和＝R12×(-2)＋R22×(-1)＋（中略）... ＋R72×2 (4-2)
H3領域の和＝R13×2＋R23×1＋（中略）...＋R73×3 (4-3)
H4領域の和＝R14×0＋R24×(-1)＋（中略）...＋R74×3 (4-4) When the second coefficient in the lightness area vi and the hue area Hj is Dij, the sum of the Hk areas for calculating the index 2 is defined as in Expression (4).

Therefore, the sum of the H1 to H4 regions is expressed by the following equations (4-1) to (4-4).
H1 area sum = R11 x 0 + R21 x 0 + (omitted) ... + R71 x 2 (4-1)
Sum of H2 area = R12 x (-2) + R22 x (-1) + (omitted) ... + R72 x 2 (4-2)
Sum of H3 area = R13 x 2 + R23 x 1 + (omitted) ... + R73 x 3 (4-3)
H4 area sum = R14 x 0 + R24 x (-1) + (omitted) ... + R74 x 3 (4-4)

The index 2 is defined as in Expression (5) using the sum of the H1 to H4 regions shown in Expressions (4-1) to (4-4).
Index 2 = sum of H1 area + sum of H2 area + sum of H3 area + sum of H4 area + 1.7 (5)
Since the index 1 and the index 2 are calculated based on the brightness of the entire image and the distribution amount of the hue, they are effective for determining a shooting scene when the entire image is a color image.

  When the index 1 and the index 2 are calculated, the third factor (first factor, second factor) set in advance according to the shooting condition is added to the second occupancy rate calculated for each class in the occupancy rate calculation process. The index 3 for specifying the photographic scene is calculated by multiplying the sum by multiplying by a coefficient different from the coefficient (step S41). The index 3 indicates a difference in contrast between the center and the outside of the screen of the image data between the backlight with the main subject under and the image with the main subject over.

図１５は、画面領域ｎ１〜ｎ３における第３の係数を、明度全体に渡って連続的に変化する曲線（係数曲線）として示したものである。 Hereinafter, a method for calculating the index 3 will be described.
Table 5 shows the third coefficient necessary for calculating the index 3 by class. The coefficient of each class shown in Table 5 is a weighting coefficient by which the second occupation ratio Qij of each class shown in Table 2 is multiplied, and is set in advance according to the shooting conditions.

FIG. 15 shows the third coefficient in the screen areas n1 to n3 as a curve (coefficient curve) that continuously changes over the entire brightness.

従って、n1〜n3領域の和は、下記の式(6-1)〜(6-3)のように表される。
n1領域の和＝Q11×12＋Q21×10＋（中略）...＋Q71×0 (6-1)
n2領域の和＝Q12×5＋Q22×3＋（中略）...＋Q72×0 (6-2)
n3領域の和＝Q13×(-1)＋Q23×(-4)＋（中略）...＋Q73×(-8) (6-3) If the third coefficient in the brightness area vi and the screen area nj is Eij, the sum of the nk area (screen area nk) for calculating the index 3 is defined as in Expression (6).

Accordingly, the sum of the n1 to n3 regions is expressed by the following formulas (6-1) to (6-3).
n1 area sum = Q11 x 12 + Q21 x 10 + (omitted) ... + Q71 x 0 (6-1)
n2 area sum = Q12 x 5 + Q22 x 3 + (omitted) ... + Q72 x 0 (6-2)
n3 area sum = Q13 x (-1) + Q23 x (-4) + (omitted) ... + Q73 x (-8) (6-3)

The index 3 is defined as in Expression (7) using the sum of the n1 to n3 regions shown in Expressions (6-1) to (6-3).
Index 3 = sum of n1 area + sum of n2 area + sum of n3 area + 0.7 (7)
The index 3 is calculated on the basis of the compositional characteristic (distance from the outer edge of the screen of the entire image) based on the distribution position of the brightness of the entire image, so that it can be used to discriminate not only a color image but also a monochrome image shooting scene. Is also effective.

  Further, for example, according to the focus detection area detected by a known method, the weight of the third coefficient multiplied by the second occupancy calculated from the distance from the outer edge of the screen and the predetermined class of brightness is set. By changing, it is possible to calculate an index for discriminating a scene with higher accuracy.

  When the indices 1 to 3 are calculated, the imaging condition is determined for each of the average luminance value of the skin color in the central portion of the screen of the entire image obtained by preliminary shooting and the difference value between the maximum luminance value and the average luminance value of the entire image. The index 4 for specifying the shooting scene is calculated by multiplying a coefficient set in advance according to (step S42).

  Hereinafter, the calculation process of the index 4 will be described in detail with reference to the flowchart of FIG.

  First, the luminance Y is calculated from the RGB (Red, Green, Blue) values of the image data of the entire image using the equation (A). Next, the average luminance value x1 of the skin color area at the center of the screen of the entire image is calculated (step S50). Here, the center of the screen is an area constituted by, for example, the area n3 shown in FIG. Next, the difference value x2 between the maximum luminance value and the average luminance value of the entire image is calculated (step S51).

Next, the standard deviation x3 of the luminance of the entire image is calculated (step S52), and the average luminance value x4 at the center of the screen is calculated (step S53). Next, a comparison value x5 between the difference value between the maximum luminance value Yskin_max and the minimum luminance value Yskin_min of the skin color area in the whole image and the average luminance value Yskin_ave of the skin color area is calculated (step S54). This comparison value x5 is expressed as the following equation (8-1).
x5 ＝ (Yskin_max−Yskin_min) / 2 −Yskin_ave （8-1）

Next, the index 4 is calculated by multiplying each of the values x1 to x5 calculated in steps S50 to S54 by a fourth coefficient set in advance according to the shooting conditions to obtain a sum (step 4). S55), the index 4 calculation process ends. The index 4 is defined as the following formula (8-2).
Index 4 = 0.05 × x1 + 1.41 × x2 + (− 0.01) × x3 + (− 0.01) × x4 + 0.01 × x5−5.34 (8-2)
This index 4 has not only the compositional characteristics of the screen of the whole image obtained by the preliminary shooting but also the luminance histogram distribution information. In particular, this index 4 is used for discriminating a shooting scene from which the main subject is over and an under shooting scene. It is valid.

  When the index 4 is calculated, the average luminance value of the skin color area in the center of the screen of the indices 1 to 3 and the entire image is multiplied by a weighting factor set in advance according to the shooting conditions, thereby the indices 5 and 6 Is calculated (step S43), and the index calculation process is terminated.

Hereinafter, the calculation method of the index 5 and the index 6 will be described in detail.
The average luminance value of the skin color area at the center of the screen of the entire image obtained by the preliminary shooting is defined as an index 4 ′. Here, the central portion of the screen is, for example, a region composed of the region n2 and the region n3 in FIG. At this time, the index 5 is defined as shown in the formula (9) using the index 1, the index 3, and the index 4 ′, and the index 6 is expressed by the formula (10) using the index 2, the index 3, and the index 4 ′. Is defined as
Index 5 = 0.54 × Index 1 + 0.50 × Index 3 + 0.01 × Index 4′−0.65 (9)
Indicator 6 = 0.83 x Indicator 2 + 0.23 x Indicator 3 + 0.01 x Indicator 4'-1.17 (10)

  Note that, as a method of calculating the average luminance value (for example, the overall average luminance value) in FIG. 16, a simple addition average value of individual luminance data obtained from each light receiving unit of the imaging device 1 may be obtained, or imaging may be performed. Similar to the center-weighted average metering that is often used as the metering method of the apparatus 1, the luminance data obtained from the light receiving unit near the center of the screen is highly weighted, and the luminance data obtained from the light receiving unit near the periphery of the screen is weighted. A method of obtaining the average value by lowering may be used. In addition, the luminance data obtained from the vicinity of the light receiving unit corresponding to the focus detection area is increased in weight, and the luminance data obtained from the light receiving unit distant from the focus detection position is reduced in weight to obtain an average value, etc. May be used.

図１７は、表６に示した判別内容を、指標４〜６の座標系を用いて表した判別マップである。 When the indices 4 to 6 are calculated, the shooting scene is determined based on the values of these indices (step S23). Table 6 shows the details of the shooting scene discrimination based on the values of index 4, index 5, and index 6.

FIG. 17 is a discrimination map representing the discrimination contents shown in Table 6 using the coordinate system of the indices 4-6.

  Next, the exposure level adjustment process (step S7 in FIG. 5) for adjusting the exposure level in the main shooting based on the indices 4 to 6 and the determined shooting scene will be described with reference to the flowchart of FIG.

First, based on the indices 4 to 6 and the determined shooting scene, an exposure adjustment value is calculated so that proper exposure is obtained in the main shooting (step S60). The exposure adjustment value is defined as in Expression (11).
Exposure adjustment value = adjustment value × {(index 4/6) × weight of index 4+ (index 5/6) × weight of index 5+ (index 6/6) × weight of index 6} (11)
Table 7 shows the adjustment value, the weight of the index 4, the weight of the index 5, and the weight of the index 6 in Expression (11). As shown in Table 7, the adjustment value and the weight of each index are set according to the determined shooting scene. Note that the method of calculating the exposure correction value is not particularly limited to Expression (11), and may be calculated based on, for example, the average luminance value and the index value of the cell determined to be skin color.

  Next, based on the exposure adjustment value calculated in step S60, the aperture unit 35 (or shutter unit 34) is controlled (step S61), and the main exposure level adjustment process ends. In parallel with the exposure level adjustment process of FIG. 18, the photographing control unit 106 may adjust the focus. For example, a focus area may be detected using a known method, and control (AF) of the imaging optical system 23 shown in FIG. 1 may be performed so that the found area becomes the in-focus area. Further, the presence or absence of flash emission may be determined according to the determined shooting scene. For example, when the scene is determined to be backlit, it is possible to make the main subject have an appropriate brightness by performing flash emission.

  Next, with reference to the flowchart of FIG. 19, the gradation conversion process (step S12 of FIG. 5) for the captured image data obtained by the actual photographing will be described.

  First, the gradation adjustment method and gradation adjustment amount for the captured image data obtained in the actual photographing are determined according to the determined photographing scene (step S70). In the present embodiment, a case where both the gradation adjustment method and the gradation adjustment amount are determined in step S70 is shown, but either one may be used.

  When determining the gradation adjustment method, as shown in FIG. 20, the gradation adjustment method A (FIG. 20 (a)) is selected when the shooting scene is a continuous light, and the gradation adjustment method is selected when the photographing scene is a backlight. When B (FIG. 20B) is selected and the main subject is over, the tone adjustment method C (FIG. 20C) is selected, and when it is under, the tone adjustment method B (FIG. 20) is selected. (B)) is selected.

  When the gradation adjustment method is determined, parameters necessary for gradation adjustment are calculated based on each index calculated in the index calculation process. Hereinafter, a method for calculating the gradation adjustment parameter will be described. In the following description, it is assumed that the 8-bit captured image data is converted in advance to 16 bits, and the unit of the value of the captured image data is 16 bits.

As parameters necessary for gradation adjustment (gradation adjustment parameters), the following parameters P1 to P9 are calculated.
P1: Average brightness of the entire shooting screen
P2: Block division average brightness
P3: Average brightness of skin tone area (H1)
P4: Brightness correction value 1 = P1-P2
P5: Reproduction target correction value = Brightness reproduction target value (30360)-P4
P6: Offset value 1 = P5-P1
P7: Key correction value
P7 ': Key correction value 2
P8: Brightness correction value 2
P9: Offset value 2 = P5-P8-P1

Here, a calculation method of the parameter P2 (block division average luminance) will be described with reference to FIGS.
First, a CDF (cumulative density function) is created in order to normalize captured image data. Next, the maximum value and the minimum value are determined from the obtained CDF. The maximum value and the minimum value are obtained for each RGB. Here, the maximum value and the minimum value obtained for each RGB are Rmax, Rmin, Gmax, Gmin, Bmax, and Bmin, respectively.

Next, normalized image data for any pixel (Rx, Gx, Bx) of the captured image data is calculated. When Rx normalization data in the R plane is R _point , Gx normalization data in the G plane is G _point , and Bx normalization data in the B plane is B _point , the normalization data R _point , G _point , B _point are , Respectively, are expressed as in Expression (12) to Expression (14).
R _point = {(Rx−Rmin) / (Rmax−Rmin)} × 65535 (12);
G _point = {(Gx−Gmin) / (Gmax−Gmin)} × 65535 (13);
B _point = {(Bx−Bmin) / (Bmax−Bmin)} × 65535 (14).
Next, the luminance N _point of the pixel (Rx, Gx, Bx) is calculated by Expression (15).
N _point = (B _point + G _point + R _point ) / 3 (15)

  FIG. 21A shows a frequency distribution (histogram) of luminance of RGB pixels before normalization. In FIG. 21A, the horizontal axis represents luminance, and the vertical axis represents pixel frequency. This histogram is created for each RGB. When the luminance histogram is created, normalization is performed for each plane with respect to the photographed image data by Expressions (12) to (14). FIG. 21B shows a histogram of luminance calculated by the equation (15). Since the captured image data is normalized by 65535, each pixel takes an arbitrary value between the maximum value 65535 and the minimum value 0.

  When the luminance histogram shown in FIG. 21B is divided into blocks divided by a predetermined range, a frequency distribution as shown in FIG. 21C is obtained. In FIG. 21C, the horizontal axis is the block number (luminance), and the vertical axis is the frequency.

  Next, processing for deleting highlight and shadow areas is performed from the luminance histogram shown in FIG. This is because the average brightness is very high in white walls and snow scenes, and the average brightness is very low in dark scenes, so highlights and shadow areas adversely affect average brightness control. . Therefore, by limiting the highlight area and shadow area of the luminance histogram shown in FIG. 21C, the influence of both areas is reduced. If the high luminance region (highlight region) and the low luminance region (shadow region) are deleted from the luminance histogram shown in FIG. 22A (or FIG. 21C), the result is as shown in FIG.

  Next, as shown in FIG. 22 (c), in the luminance histogram, an area whose frequency is larger than a predetermined threshold is deleted. This is because if there is a part having an extremely high frequency, the data in this part strongly affects the average luminance of the entire captured image, and thus erroneous correction is likely to occur. Therefore, as shown in FIG. 22C, the number of pixels equal to or greater than the threshold is limited in the luminance histogram. FIG. 22D is a luminance histogram after the pixel number limiting process is performed.

  Each block number of the luminance histogram (FIG. 22 (d)) obtained by deleting the high luminance region and the low luminance region from the normalized luminance histogram and further limiting the number of accumulated pixels, and the respective frequencies The parameter P2 is obtained by calculating the average luminance based on the above.

The parameter P1 is an average value of the luminance of the entire captured image data, and the parameter P3 is an average value of the luminance of the skin color region (H1) in the captured image data. The key correction value of the parameter P7, the key correction value 2 of the parameter P7 ′, and the luminance correction value 2 of the parameter P8 are respectively defined as Expression (16), Expression (17), and Expression (18).
P7 (key correction value) = {P3-((index 6/6) x 18000 + 22000)} / 24.78 (16)
P7 '(key correction value 2) = {P3-((index 4/6) x 10000 + 30000)} / 24.78 (17)
P8 (Luminance correction value 2) = (Indicator 5/6) x 17500 (18)

  When the gradation adjustment parameter is calculated, a gradation adjustment amount for the captured image data is calculated based on the calculated gradation adjustment parameter. Specifically, a gradation conversion curve corresponding to the calculated gradation adjustment parameter is selected (determined) from a plurality of gradation conversion curves set in advance corresponding to the determined gradation adjustment method. The Note that the gradation conversion curve (gradation adjustment amount) may be calculated based on the gradation adjustment parameter. When the gradation conversion curve is determined, gradation conversion processing is performed on the photographic image data according to the determined gradation conversion curve (step S71), and the gradation conversion processing ends.

Hereinafter, a method for determining a gradation conversion curve for each shooting scene (light source condition and exposure condition) will be described.
<For direct light>
When the shooting scene is front light, offset correction (parallel shift of 8-bit value) for matching the parameter P1 with P5 is performed by the following equation (19).
RGB value of output image = RGB value of input image + P6 (19)
Therefore, when the photographic scene is front light, a gradation conversion curve corresponding to Expression (19) is selected from a plurality of gradation conversion curves shown in FIG. Alternatively, the gradation conversion curve may be calculated (determined) based on Expression (19).

<Backlight>
When the shooting scene is backlit, a gradation conversion curve corresponding to the parameter P7 (key correction value) shown in Expression (16) is selected from the plurality of gradation conversion curves shown in FIG. FIG. 23 shows a specific example of the gradation conversion curve in FIG. The correspondence between the value of parameter P7 and the selected gradation conversion curve is shown below.
When -50 <P7 <+50 → L3
When +50 ≤ P7 <+150 → L4
When +150 ≤ P7 <+250 → L5
When -150 <P7 ≤ -50 → L2
When -250 <P7 ≤ -150 → L1
When the shooting scene is backlit, it is preferable to perform a dodging process together with the gradation conversion process. In this case, it is desirable to adjust the degree of dodging processing according to the index 6 indicating the backlight intensity.

<In case of under>
When the shooting scene is under, a gradation conversion curve corresponding to the parameter P7 ′ (key correction value 2) shown in Expression (17) is selected from the plurality of gradation conversion curves shown in FIG. The Specifically, the gradation conversion curve corresponding to the value of the parameter P7 ′ is selected from the gradation conversion curves shown in FIG. 23 in the same manner as the method for selecting the gradation conversion curve when the shooting scene is backlit. The When the shooting scene is under, the dodging process as shown in the case of backlight is not performed.

<When the main subject is over>
When the main subject is over, offset correction (parallel shift of 8-bit value) is performed by Expression (20).
RGB value of output image = RGB value of input image + P9 (20)
Therefore, when the main subject is over, a gradation conversion curve corresponding to Expression (20) is selected from the plurality of gradation conversion curves shown in FIG. Alternatively, the gradation conversion curve may be calculated (determined) based on Expression (20). When the value of the parameter P9 in the equation (20) exceeds a preset predetermined value α, a curve corresponding to the key correction value P9-α is selected from the curves L1 to L5 shown in FIG. Is done.

  In the present embodiment, when the gradation conversion process is actually performed on the captured image data, the above-described gradation conversion process condition is changed from 16 bits to 8 bits.

  As described above, according to the imaging apparatus 1 of the present embodiment, it is possible to calculate an index that represents a shooting scene with high accuracy from an entire image obtained by preliminary shooting. In addition, since an index representing the shooting scene with high accuracy is used, it is possible to accurately adjust the exposure for the main shooting.

  Furthermore, since an index that represents the shooting scene with high accuracy is used, it is possible to accurately determine the gradation adjustment method for the shot image data obtained by the actual shooting. In addition, in the brightness class, having at least three classes within 10% of the maximum brightness value, the separation of the low brightness side class is improved even with linear image data, and high accuracy is achieved. The shooting scene can be determined.

1 is a diagram illustrating an external configuration of an imaging apparatus according to an embodiment of the present invention. 1 is a block diagram showing an internal configuration of an imaging apparatus according to an embodiment. The block diagram which shows the internal structure of a processor. The whole image (a) obtained by preliminary photography, and the figure (b) which divided the whole image into MxN cells. 3 is a flowchart showing an overall flow of processing executed in the imaging apparatus. The flowchart which shows a photography scene discrimination | determination process. 6 is a flowchart showing color space conversion processing. The figure which shows an example of the program which converts from RGB to HSV color system. The flowchart which shows an occupation rate calculation process. The figure which shows the class which consists of brightness and hue. The figure which shows the area | region n1-n3 determined according to the distance from the outer edge of the screen of the whole image obtained by preliminary photography, and the figure which shows the class which consists of the area | region n1-n3 and the brightness (b). The flowchart which shows an index calculation process. The figure which shows the curve showing the 1st coefficient by which the 1st occupation rate for calculating the parameter | index 1 is multiplied. The figure which shows the curve showing the 2nd coefficient by which the 1st occupation rate for calculating the parameter | index 2 is multiplied. The figure which shows the curve showing the 3rd coefficient by which the 2nd occupation rate for calculating the parameter | index 3 is multiplied for every area | region (n1-n3). The flowchart which shows the parameter | index 4 calculation process. The figure which shows the relationship between a parameter | index and an imaging | photography scene. The flowchart which shows an exposure level adjustment process. The flowchart which shows a gradation conversion process. The figure which shows the gradation conversion curve corresponding to each gradation adjustment method. The figure which shows the frequency distribution (histogram) (a) of brightness | luminance, the normalized histogram (b), and the block-divided histogram (c). The figure ((a) and (b)) explaining deletion of the low-intensity area | region and the high-intensity area | region from the brightness | luminance histogram, and the figure ((c) and (d)) explaining the restriction | limiting of the frequency of a brightness | luminance. The figure which shows the gradation conversion curve showing the gradation conversion conditions in case an imaging | photography scene is backlight or under.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Image pick-up device 21 Case 22 Cross key 23 Shooting optical system 24 Flash 25 Finder 26 Power switch 27 Display part 28 Release button 31 Processor 32 Memory 33 Image sensor 34 Shutter unit 35 Aperture unit 101 Whole image acquisition part 102 Color information acquisition part 103 Occupancy rate calculation unit 104 Index calculation unit 105 Shooting scene determination unit 106 Shooting control unit 107 Tone adjustment determination unit

Claims (24)

Acquisition means for acquiring a whole image obtained by preliminary shooting as a divided image composed of a plurality of divided regions;
Color information acquisition means for acquiring color information for each divided region of the entire image;
Based on the color information acquired by the color information acquisition means, each of the divided areas is classified into a predetermined class composed of a combination of lightness and hue, and for each classified class, the divided areas belonging to the class are An occupancy ratio calculating means for calculating a first occupancy ratio indicating a ratio of the entire image;
An index calculation means for calculating a first index and a second index for specifying a shooting scene by multiplying the first occupancy by two different coefficients set in advance according to shooting conditions. When,
An imaging apparatus comprising: Acquisition means for acquiring a whole image obtained by preliminary shooting as a divided image composed of a plurality of divided regions;
Color information acquisition means for acquiring color information for each divided region of the entire image;
Based on the color information acquired by the color information acquisition means, each of the divided areas is classified into a predetermined class composed of a combination of lightness and hue, and for each classified class, the divided areas belonging to the class are A first occupancy ratio indicating a ratio of the entire image is calculated, and each of the divided regions is classified into a predetermined class composed of a combination of a distance from the outer edge of the screen of the entire image and brightness, and the classified class An occupancy ratio calculating means for calculating a second occupancy ratio indicating the ratio of the divided area belonging to the class to the entire image for each time;
The first occupancy is multiplied by a coefficient set in advance according to the shooting condition to calculate a first index for specifying the shooting scene, and the second occupancy is set to the shooting condition. Index calculating means for calculating a second index for specifying a shooting scene by multiplying a coefficient set in advance according to
An imaging apparatus comprising:   By multiplying each of the average luminance value of the skin color in the screen central portion of the whole image and the difference value between the maximum luminance value and the average luminance value of the whole image by a coefficient set in advance according to the shooting conditions, The imaging apparatus according to claim 1, further comprising a third index calculation unit that calculates a third index for specifying a shooting scene.   A photographing control unit is provided that adjusts an exposure level based on at least the first index and the second index among the calculated indices, and performs actual photographing at the adjusted exposure level. The imaging device according to any one of claims 1 to 3.   A gradation adjustment determining unit that determines a gradation adjustment method for captured image data obtained by actual imaging based on at least the first index and the second index among the calculated indices. The imaging apparatus according to claim 1, wherein the imaging apparatus is characterized.   6. The apparatus according to claim 1, further comprising: a determination unit configured to determine a shooting scene of the entire image based on at least the first index and the second index among the calculated indices. The imaging device according to claim 1.   The imaging according to any one of claims 1 to 6, wherein the predetermined class has a brightness range in the highest brightness class wider than a brightness range in the lowest brightness class. apparatus.   The image pickup apparatus according to claim 7, wherein the predetermined class has at least three classes within a value of 10% of a maximum brightness value. An acquisition step of acquiring the entire image obtained by the preliminary shooting as a divided image composed of a plurality of divided regions;
For each divided region of the entire image, a color information acquisition step for acquiring color information;
Based on the color information acquired by the color information acquisition step, the divided areas are classified into predetermined classes composed of combinations of brightness and hue, and for each classified class, the divided areas belonging to the class are An occupancy ratio calculating step of calculating a first occupancy ratio indicating the ratio of the entire image;
An index calculation step of calculating a first index and a second index for specifying a shooting scene by multiplying the first occupation ratio by two different coefficients set in advance according to shooting conditions. When,
An image processing method comprising: An acquisition step of acquiring the entire image obtained by the preliminary shooting as a divided image composed of a plurality of divided regions;
For each divided region of the entire image, a color information acquisition step for acquiring color information;
Based on the color information acquired by the color information acquisition step, the divided areas are classified into predetermined classes composed of combinations of brightness and hue, and for each classified class, the divided areas belonging to the class are A first occupancy ratio indicating a ratio of the entire image is calculated, and each of the divided regions is classified into a predetermined class composed of a combination of a distance from the outer edge of the screen of the entire image and brightness, and the classified class An occupancy ratio calculating step for calculating a second occupancy ratio indicating the ratio of the divided area belonging to the class to the entire image for each time;
The first occupancy is multiplied by a coefficient set in advance according to the shooting condition to calculate a first index for specifying the shooting scene, and the second occupancy is set to the shooting condition. An index calculation step of calculating a second index for specifying the shooting scene by multiplying a coefficient set in advance according to
An image processing method comprising:   By multiplying each of the average luminance value of the skin color in the screen central portion of the whole image and the difference value between the maximum luminance value and the average luminance value of the whole image by a coefficient set in advance according to the shooting conditions, 11. The image processing method according to claim 9, further comprising a third index calculation step of calculating a third index for specifying a shooting scene.   And a shooting control step of adjusting an exposure level based on at least the first index and the second index among the calculated indexes and performing actual shooting at the adjusted exposure level. The image processing method according to any one of claims 9 to 11.   Including a gradation adjustment determining step of determining a gradation adjustment method for captured image data obtained by actual imaging based on at least the first index and the second index among the calculated indices. The image processing method according to claim 9, wherein the image processing method is characterized in that   14. The method according to claim 9, further comprising: a determination step of determining a shooting scene of the entire image based on at least the first index and the second index among the calculated indices. An image processing method according to claim 1.   The image according to any one of claims 9 to 14, wherein the predetermined class has a brightness range in the highest brightness class wider than a brightness range in the lowest brightness class. Processing method.   16. The image processing method according to claim 15, wherein the predetermined class has at least three classes within a value of 10% of the maximum brightness value. In the computer for executing image processing,
An acquisition function for acquiring an entire image obtained by preliminary shooting as a divided image composed of a plurality of divided areas;
For each divided area of the entire image, a color information acquisition function for acquiring color information;
Based on the color information acquired by the color information acquisition function, each of the divided areas is classified into a predetermined class consisting of a combination of lightness and hue, and for each classified class, the divided areas belonging to the class are An occupancy ratio calculation function for calculating a first occupancy ratio indicating the ratio of the entire image;
An index calculation function for calculating a first index and a second index for specifying a shooting scene by multiplying the first occupation ratio by two different coefficients set in advance according to shooting conditions. When,
An image processing program for realizing In the computer for executing image processing,
An acquisition function for acquiring an entire image obtained by preliminary shooting as a divided image composed of a plurality of divided areas;
For each divided area of the entire image, a color information acquisition function for acquiring color information;
Based on the color information acquired by the color information acquisition function, each of the divided areas is classified into a predetermined class consisting of a combination of lightness and hue, and for each classified class, the divided areas belonging to the class are A first occupancy ratio indicating a ratio of the entire image is calculated, and each of the divided regions is classified into a predetermined class composed of a combination of a distance from the outer edge of the screen of the entire image and brightness, and the classified class An occupancy ratio calculation function for calculating a second occupancy ratio indicating the ratio of the divided area belonging to the class to the entire image for each time;
The first occupancy is multiplied by a coefficient set in advance according to the shooting condition to calculate a first index for specifying the shooting scene, and the second occupancy is set to the shooting condition. An index calculation function for calculating a second index for specifying a shooting scene by multiplying a coefficient set in advance according to
An image processing program for realizing   By multiplying each of the average luminance value of the skin color in the screen central portion of the whole image and the difference value between the maximum luminance value and the average luminance value of the whole image by a coefficient set in advance according to the shooting conditions, The image processing program according to claim 17 or 18, further comprising a third index calculation function for calculating a third index for specifying a shooting scene.   Of the calculated indexes, the camera has a shooting control function that adjusts an exposure level based on at least the first index and the second index, and performs actual shooting at the adjusted exposure level. The image processing program according to any one of claims 17 to 19.   A gradation adjustment determination function for determining a gradation adjustment method for captured image data obtained by actual photographing based on at least the first index and the second index among the calculated indices; The image processing program according to any one of claims 17 to 20, wherein   The discrimination function of discriminating a photographing scene of the whole image based on at least the first index and the second index among the calculated indices. The image processing program according to claim 1.   The image according to any one of claims 17 to 22, wherein the predetermined class has a range of brightness in the class of highest brightness rather than a range of brightness in the class of lowest brightness. Processing program.   The image processing program according to claim 23, wherein the predetermined class includes at least three classes within a value of 10% of a maximum brightness value.

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