JP2007243556A - Imaging apparatus, image processing method, and image processing program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an imaging apparatus, an image processing method, and an image processing program capable of obtaining a more proper correction image by discriminating a photographed scene of an image acquired, by photographing with high accuracy and applying correction processing to the image, depending on the photographed scene. <P>SOLUTION: The imaging apparatus is provided with a first image acquisition means for acquiring a first image by photographing; a first luminance information acquisition means for acquiring first luminance information in a prescribed first region from a photometric value of a photographing region calculated at the photographing; a second luminance information acquisition means for acquiring second luminance information in a second region around the first region from a photometric value of a photographing region calculated at the photographing; a scene discrimination processing means for discriminating photographing scene, on the basis of the first luminance information, the second luminance information and the first image which are acquired; and a gradation processing condition setting means for setting a gradation processing condition to the first image, on the basis of a discrimination result by the scene discrimination processing means. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to an imaging apparatus, an image processing method, and an image processing program that perform image processing of a captured image.

  In recent years, digital still cameras (including those incorporated in devices such as mobile phones and laptop computers, hereinafter abbreviated as DSC) have become widespread, and, as with conventional color photographic film systems, output as hard copy images. In addition, systems that display on a medium such as a CRT or record on a recording medium such as a CD-R (CD-Recordable) are widely used.

  However, when an image taken with a DSC or the like is viewed as an image through various media as described above, an image suitable for viewing is generally obtained as it is due to inadequate exposure adjustment at the time of shooting. There are many cases where this is not possible. That is, in order to obtain an appropriate appreciation image, it is desirable that an appropriate image gradation correction process is performed in order to compensate for overexposure or underexposure during shooting.

  In addition, if there is a large luminance deviation in the image due to the influence of the light source state during shooting, such as shooting in a backlight state or close-up shooting using a flash, the image can be viewed as it is. It cannot be said that the image is suitable for the purpose, and it is desirable to perform some correction processing.

  In order to solve such problems, correction processing such as gradation conversion processing has been performed conventionally. For example, in addition to conversion processing that corrects the average luminance for under and over exposure, if a large area with a large luminance deviation occurs in the image, a correction value is calculated by discriminant analysis or multiple regression analysis. For example, a conversion process is performed.

  However, in this discriminant regression analysis method, for example, correction values calculated by flash close-up shooting and shooting in a backlight scene are similar, for example, correction processing after appropriately determining the shooting scene is performed. Sometimes it was difficult to do.

  For this reason, a method for obtaining an appropriate correction value using a distribution of luminance values in an image has been proposed as an alternative to the above correction method (see, for example, Patent Document 1). Further, a method has been proposed in which face area candidates in an image are extracted and a scene is discriminated from the magnitude of the average luminance bias (see, for example, Patent Document 2).

  In Patent Document 1, a high-luminance region and a low-luminance region are deleted from a histogram indicating the cumulative number of pixels (frequency number) of luminance in an image, the frequency number is further limited, a luminance average is calculated, and reference luminance and The correction value is obtained from the difference value.

In Patent Document 2, a candidate for a face region is extracted by a hue saturation histogram, pattern matching, or the like, and a bias with respect to the entire image is calculated. If the bias is large, a one-dimensional density histogram is obtained. Based on this, a backlit scene and proximity flash photography are discriminated.
JP 2002-247393 A JP 2000-148980 A

  However, in the technique described in Patent Document 1, the influence of a region with a large luminance deviation in a backlight scene or close-up flash photography is reduced. However, for example, in a photographing scene having a person as a main subject, the luminance of the face region is high. There is a problem that it cannot be corrected to a sufficiently appropriate value.

  The technique described in Patent Document 2 can achieve the effect of compensating for the identification of a face area in a typical backlight scene or close-up flash photography, but the compensation effect cannot be obtained unless a typical composition is applied. There's a problem.

  An object of the present invention is to determine an imaging scene of an image acquired by imaging with high accuracy, and to perform a correction process according to the imaging scene, thereby obtaining an appropriate correction image, image A processing method and an image processing program are provided.

In order to solve the above-mentioned problem, the invention described in claim 1
First image acquisition means for acquiring a first image by photographing;
First luminance information acquisition means for acquiring first luminance information in a predetermined first area from a photometric value of the imaging area calculated at the time of shooting;
Second luminance information acquisition means for acquiring second luminance information in a second area around the first area from the calculated photometric value of the imaging area;
Scene discrimination processing means for discriminating a shooting scene based on the acquired first luminance information, second luminance information and the first image;
Gradation processing condition setting means for setting gradation processing conditions for the first image based on a determination result by the scene determination processing means;
It is characterized by having.

Furthermore, the invention according to claim 2 is the invention according to claim 1,
The scene discrimination processing means includes
Color information is acquired from the image data of the first image, and the image data is classified into classes composed of combinations of predetermined brightness and hue based on the acquired color information, and for each of the classified classes, First occupancy ratio calculating means for calculating a first occupancy ratio indicating a ratio of the entire image data;
Based on the acquired color information, the image data is classified into a class composed of a combination of the distance from the outer edge of the screen and the brightness, and a second ratio indicating the ratio of the entire image data to each classified class. Second occupancy rate calculating means for calculating the occupancy rate of
First index calculating means for calculating index 1 by multiplying the first occupancy by a preset first coefficient;
A second index calculating means for calculating index 2 by multiplying the first occupancy by a preset second coefficient;
A third index calculating means for calculating index 3 by multiplying the second occupancy by a preset third coefficient;
A fourth index calculating means for calculating index 4 by multiplying an average brightness of the skin color at least in the center of the screen of the image data by a preset fourth coefficient;
Scene discriminating means for discriminating a shooting scene of the image data based on the index 1, the index 2, the index 3, the index 4, the first luminance information and the second luminance information;
It is characterized by having.

Furthermore, the invention according to claim 3 is the invention according to claim 1 or 2,
Second image acquisition means for acquiring a second image obtained by reducing the image size from the first image acquired by the first image acquisition means;
The scene discrimination processing means discriminates a shooting scene based on the second image acquired by the second image acquisition means.

Furthermore, the invention according to claim 4 is the invention according to any one of claims 1 to 3,
The gradation processing condition setting means includes:
Gradation adjustment parameter calculation means for calculating a gradation adjustment parameter based on an index calculated based on the first image, the first luminance information, and the second luminance information;
A gradation processing condition for the first image is set based on a determination result by the scene determination processing unit and the gradation adjustment parameter calculated by the gradation adjustment parameter calculation unit.

Furthermore, the invention according to claim 5 is the invention according to any one of claims 1 to 4,
The image processing apparatus is characterized by further comprising gradation conversion processing means for performing gradation conversion processing on the first image based on the gradation processing conditions set by the gradation processing condition setting means.

Furthermore, the invention according to claim 6 is the invention according to any one of claims 1 to 5,
Focusing is performed with respect to a specific object to be photographed in the photographing region, and focusing means for detecting the focal position is provided.
The first luminance information acquisition unit is characterized in that the first region is specified based on a focus position detected by the focusing unit.

In order to solve the above problem, the invention according to claim 7 provides:
A first image acquisition step of acquiring a first image by photographing;
A first luminance information acquisition step of acquiring first luminance information in a predetermined first area from a photometric value of the imaging area calculated at the time of shooting;
A second luminance information acquisition step of acquiring second luminance information in a second region around the first region from the photometric value of the calculated imaging region;
A scene determination processing step of determining a photographic scene based on the acquired first luminance information, second luminance information, and second image;
A gradation processing condition setting step for setting a gradation processing condition for the first image based on a determination result by the scene determination processing step;
It is characterized by including.

Further, the invention according to claim 8 is the invention according to claim 7,
The scene discrimination processing step includes
Color information is acquired from the image data of the first image, and the image data is classified into classes composed of combinations of predetermined brightness and hue based on the acquired color information, and for each of the classified classes, A first occupancy ratio calculating step of calculating a first occupancy ratio indicating a ratio of the entire image data;
Based on the acquired color information, the image data is classified into a class composed of a combination of the distance from the outer edge of the screen and the brightness, and a second ratio indicating the ratio of the entire image data to each classified class. A second occupancy rate calculating step for calculating the occupancy rate of
A first index calculation step of calculating index 1 by multiplying the first occupancy by a preset first coefficient;
A second index calculating step of calculating index 2 by multiplying the first occupancy by a preset second coefficient;
A third index calculating step of calculating index 3 by multiplying the second occupancy by a preset third coefficient;
A fourth index calculating step of calculating index 4 by multiplying an average brightness of the skin color at least in the center of the screen of the image data by a preset fourth coefficient;
A scene determination step of determining a shooting scene of the image data based on the index 1, the index 2, the index 3, the index 4, the first luminance information, and the second luminance information;
It is characterized by including.

Furthermore, the invention according to claim 9 is the invention according to claim 7 or 8,
Including a second image acquisition step of acquiring a second image obtained by reducing the image size from the first image acquired by the first image acquisition step;
The scene discrimination processing step is characterized in that a photographic scene is discriminated based on the second image acquired by the second image acquisition means.

Furthermore, the invention according to claim 10 is the invention according to any one of claims 7 to 9,
The gradation processing condition setting step includes
A gradation adjustment parameter calculating step of calculating a gradation adjustment parameter based on an index calculated based on the first image, the first luminance information, and the second luminance information;
A gradation processing condition for the first image is set based on a determination result obtained by the scene determination processing step and the gradation adjustment parameter calculated by the gradation adjustment parameter calculation step.

Furthermore, the invention according to claim 11 is the invention according to any one of claims 7 to 10,
The image processing apparatus includes a gradation conversion processing step for performing gradation conversion processing on the first image based on the gradation processing conditions set by the gradation processing condition setting step.

Furthermore, the invention according to claim 12 is the invention according to any one of claims 7 to 11,
Focusing on a specific object to be photographed in the photographing region, and including a focusing step of detecting the focal point position;
The first luminance information acquisition step is characterized in that the first region is specified based on the focal position detected by the focusing step.

In order to solve the above problems, the invention according to claim 13 is
In the computer for executing image processing,
A first image acquisition function for acquiring a first image by photographing;
A first luminance information acquisition function for acquiring first luminance information in a predetermined first area from a photometric value of the imaging area calculated at the time of shooting;
A second luminance information acquisition function for acquiring second luminance information in a second region around the first region from the photometric value of the calculated imaging region;
A scene discrimination processing function for discriminating a shooting scene based on the acquired first luminance information, second luminance information, and second image;
A gradation processing condition setting function for setting gradation processing conditions for the first image based on a determination result by the scene determination processing function;
Is realized.

Furthermore, the invention of claim 14 is the invention of claim 13,
The scene discrimination processing function is
Color information is acquired from the image data of the first image, and the image data is classified into classes composed of combinations of predetermined brightness and hue based on the acquired color information, and for each of the classified classes, A first occupancy ratio calculating function for calculating a first occupancy ratio indicating a ratio of the entire image data;
Based on the acquired color information, the image data is classified into a class composed of a combination of the distance from the outer edge of the screen and the brightness, and a second ratio indicating the ratio of the entire image data to each classified class. A second occupancy ratio calculating function for calculating the occupancy ratio of
A first index calculation function for calculating index 1 by multiplying the first occupancy by a preset first coefficient;
A second index calculation function for calculating index 2 by multiplying the first occupancy by a preset second coefficient;
A third index calculation function for calculating index 3 by multiplying the second occupancy by a preset third coefficient;
A fourth index calculation function for calculating index 4 by multiplying an average brightness of the skin color at least in the center of the screen of the image data by a preset fourth coefficient;
A scene discrimination function for discriminating a shooting scene of the image data based on the index 1, the index 2, the index 3, the index 4, the first luminance information, and the second luminance information;
It is characterized by having.

Furthermore, the invention of claim 15 is the invention of claim 13 or 14,
In the computer,
Realizing a second image acquisition function for acquiring a second image obtained by reducing the image size from the first image acquired by the first image acquisition function;
The scene discrimination processing function discriminates a photographic scene based on the second image acquired by the second image acquisition function.

Furthermore, the invention described in claim 16 is the invention described in any one of claims 13-15,
The gradation processing condition setting function is
A gradation adjustment parameter calculation function for calculating a gradation adjustment parameter based on an index calculated based on the first image, the first luminance information, and the second luminance information;
A gradation processing condition for the first image is set based on a determination result by the scene determination processing function and the gradation adjustment parameter calculated by the gradation adjustment parameter calculation function.

Furthermore, the invention according to claim 17 is the invention according to any one of claims 13 to 16,
In the computer,
A gradation conversion processing function for performing gradation conversion processing on the first image is realized based on the gradation processing conditions set by the gradation processing condition setting function.

Furthermore, the invention according to claim 18 is the invention according to any one of claims 13 to 17,
In the computer,
Focusing on a specific object to be photographed in the photographing region, realizing a focusing function for detecting the focal position,
The first luminance information acquisition function is characterized in that the first area is specified based on a focus position detected by the focusing means.

  According to the first, seventh, and thirteenth aspects of the present invention, the photographic scene is determined based on the first luminance information and the second luminance information in the photographic region, and the gradation processing condition corresponding to the determined photographic scene is set. Set. This makes it possible to discriminate shooting scenes from image data with high accuracy, and to perform gradation processing according to the discrimination results of shooting scenes such as overexposure, underexposure, forward light, and backlight scene of the main subject. Therefore, a more appropriate corrected image can be obtained.

  According to the inventions described in claims 2, 8, and 14, since the shooting scene is determined based on the index calculated from the first occupancy rate and the second occupancy rate, the shooting scene is accurately detected from the image data. Since it is possible to perform the gradation processing according to the discrimination result of the shooting scene such as the overshoot of the main subject, underexposure, forward light, backlight scene, etc., it is possible to obtain a more appropriate corrected image Can do.

  According to the third, ninth, and fifteenth aspects of the present invention, since the shooting scene is determined based on the second image obtained by reducing the image size from the first image, the shooting scene is determined from the image data at a higher speed. be able to.

  According to the fourth, tenth, and sixteenth aspects of the present invention, since the gradation processing condition for the first image is set based on the result of determining the shooting scene and the gradation adjustment parameter, more appropriate gradation processing is performed. Therefore, a more appropriate corrected image can be obtained.

  According to the fifth, eleventh, and seventeenth aspects, the gradation conversion process is performed on the first image based on the set gradation processing condition, so that a more appropriate corrected image can be obtained.

  According to the sixth, twelfth and eighteenth aspects of the present invention, since the first area is specified based on the in-focus position, the determination result of the photographic scene such as the overshoot of the main subject, the underexposure, the forward light, the backlight scene, etc. Accordingly, it is possible to perform gradation processing correspondingly, and a more appropriate corrected image can be obtained.

  The best mode for carrying out the present invention will be described below in detail with reference to the drawings. However, the scope of the invention is not limited to the illustrated examples.

(Configuration of the imaging device 1)
First, the configuration of the imaging device 1 according to the present invention will be described.
FIG. 1A shows a front view of the imaging apparatus 1, and FIG. 1B shows a rear view of the imaging apparatus 1. The imaging device 1 is, for example, a digital camera or the like, and has a cross key 22, a photographing optical system 23, a flash 24, a finder 25, a power source, on the inside or the surface of a housing 21 made of a material such as metal or synthetic resin. A switch 26, 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 image pickup apparatus 1 includes a processor 31, a memory 32, an image pickup device 33 such as a CCD (Charge Coupled Device), a shooting optical system 23, a timing generator 41, a shutter unit 42, a diaphragm unit 43, and a focus unit 44. , A display unit 27, an operation unit 38, and an image data output unit 37. The processor 31 includes a photographing processing unit 20 that performs photographing control and processing of a photographed image, and an image processing unit 10 that performs image processing.

  The cross key 22 is made up of buttons in four directions, up, down, left and right, and is used by 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.

  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 data output unit 37 transfers and records the image data in the memory 32 to a recording medium for storage (such as an SD memory card or a multimedia card (MMC)), or transfers it to an external device. The image data output unit 37 is controlled by the processor 31.

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

  The shutter unit 42 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. Timing control is performed by the timing generator 41. The exposure amount control by the shutter unit 42 will be described later.

  Adjustment of the amount of light received by the image sensor 33 is performed by the aperture unit 43 and / or the shutter unit 42. The focus unit 44 performs a control operation for driving the photographing optical system 23 to focus on the photographing subject. Focus control by the focus unit 44 will be described later.

(Internal configuration of the imaging processing unit 20)
FIG. 3 shows an internal configuration of the imaging processing unit 20. The shooting processing unit 20 performs control related to shooting conditions during shooting and processing of shot images. Hereinafter, the internal configuration of the imaging processing unit 20 will be described with reference to FIG.

  As shown in FIG. 3, the imaging processing unit 20 includes an AE control unit 51, an AF control unit 52, and a pixel interpolation unit 53, an AWB control unit 54, and a gamma that perform image processing on a captured image. It is comprised by the correction | amendment part 55 grade | etc.,.

  The AE control unit 51 automatically controls the exposure amount at the time of image shooting. Normally, the exposure amount control during shooting standby is performed by controlling the shutter speed with the aperture opened, and the exposure amount during shooting is controlled by the aperture and shutter speed.

  For example, the exposure amount control during shooting standby in the AE control unit 51 is performed as follows (see the flowchart in FIG. 4A).

  First, the diaphragm unit 43 sets the diaphragm to an open fixed diaphragm (step S111). The AE control unit 51 reads data of a predetermined photometric area from the image data obtained by the image sensor 33 (step S112), and acquires information corresponding to the luminance value (step S113). Information corresponding to the luminance value is used as information for AE control, and the G value of RGB three-color components is often used simply (hereinafter referred to as luminance information G). The charge accumulation time in the next frame of the image sensor 33 is set according to the luminance information G (step S114), and the charge accumulation time in the next frame is controlled by the timing generator 41 so that the predetermined luminance level is obtained. (Step S117). This is control of the shutter speed, and FIG. 5 shows how charges are accumulated. That is, when the acquired luminance level is large (bright), the charge accumulation time is shortened, and when the acquired luminance level is small (dark), the charge accumulation time is lengthened, thereby stabilizing the exposure amount.

  By performing exposure amount control during shooting standby in this way, a photographer can observe a live view image whose exposure amount is controlled on the display unit 27 such as a liquid crystal display.

  In the exposure control at the time of actual photographing in the AE control unit 51, in addition to the shutter speed control described above, aperture control is also performed (see the flowchart in FIG. 4B). Similarly to the above (steps S112 and S113), the aperture unit 43 is controlled according to the luminance information G of the photometric area, and an aperture value is set (step S116). That is, the exposure value is stabilized by decreasing the aperture value when the acquired brightness level is large (bright) and increasing the aperture value when the brightness level is low (dark). The adjustment level in combination with the shutter speed is controlled based on data of a predetermined program diagram, for example, the charge accumulation time of the image sensor 33 is adjusted according to the aperture value (step S115, S117).

  As described above, the exposure amount control is performed at the time of photographing, so that the photographer can automatically perform the exposure amount setting for the photographed image with an arbitrary or predetermined combination of the aperture value and the shutter speed.

  The AF control unit 52 performs automatic control for focusing on a specific shooting target in the shooting area when shooting an image. This in-focus control is performed by, for example, driving the photographing optical system as described below to detect the in-focus position and stopping it according to the position (see the flowchart in FIG. 6). That is, the AF control unit 52 functions as a focusing unit.

  When driving of the photographic optical system 23 is started (step S121), the AF control unit 52 sequentially reads data of a predetermined distance measuring area from the image data obtained by the image sensor 33 (step S122). ), Contrast information is acquired according to this data (step S123). This is for detecting whether or not the in-focus position has been reached, and is determined as follows. That is, the contrast information is set and calculated so as to depend on the sharpness of the edge portion by taking the difference between adjacent pixels in the distance measurement area data. The state that has reached the maximum is determined to be the focal point (steps S124 and S125). If it is determined that the focus position is not reached, the movement of the photographing optical system is continued (step S126).

  FIG. 7 shows a change in contrast information accompanying the movement of the photographic optical system 23 and how the focal point position is detected. In the above operation, a distance measurement calculation is performed in which contrast information is sequentially acquired while driving the optical system to obtain a focal point position, and the photographing optical system 23 is stopped in accordance with the focal length ( Step S127). That is, steps S124 to 127 function as a focusing process.

  With such AF control, it is possible to obtain a captured image that is always in focus automatically during shooting.

  The pixel interpolation unit 53 interpolates pixels for each color component with respect to the CCD array in which the RGB color components are dispersedly arranged in the image sensor 33, and processes the image data so that each color component value is obtained at the same pixel position. (Refer to the flowchart of FIG. 8).

  The pixel interpolation unit 53 masks the RGB image data (step S131) obtained by the image sensor 33 with each of the RGB pixel filter patterns (steps S132, S134, S136), and then performs average interpolation (also referred to as pixel interpolation). (Steps S133, S135, S137). Among these, the G pixel filter pattern having pixels up to a high band is a median filter that performs average interpolation by substituting the average value of the intermediate binary values of the surrounding four pixels, and the R and B pixel filters The pattern performs average interpolation with respect to the same color from 9 neighboring pixels.

  The AWB control unit 54 automatically adjusts the white balance in the captured image. Assuming that the photographed image has a subject area in which RGB color balance is achieved (white when summed up), each component value of RGB of the image is achieved so as to achieve white balance in that area. Adjust the level for. This white balance processing is performed, for example, as follows (see the flowchart of FIG. 9).

  The AWB control unit 54 estimates an area that is supposed to be white from the luminance and saturation data of the image data obtained by the image sensor 33 (step S141). For that region, the average intensity, G / R ratio, and G / B ratio of each RGB component value are obtained, and the R value and B value correction gains for the G value are calculated (steps S143 and S144). Based on this, gain correction for each color component in the entire image is performed (step S145).

  By such AWB control, it is possible to automatically correct the collapse of the color balance of the entire screen that occurs during shooting, and an image with a stable color tone can be obtained regardless of the actual illumination state of the subject.

  The gamma correction unit 55 performs processing for converting the gradation of the captured image so as to be suitable for the characteristics of the output device.

  The gamma characteristic is a gradation characteristic, and indicates how an output gradation is set with respect to an input gradation by a correction value or a correction curve. FIG. 10 shows an example of a correction curve indicating an output value corrected for the input value. The gamma correction is a conversion process for converting an input value into an output value according to the correction value or the correction curve. Since this gradation characteristic varies depending on the output device, it is necessary to correct this gamma characteristic in order to obtain a gradation suitable for the output device. As a result, the captured linear image is converted into a non-linear image.

  A monitor is generally set as the output device, and gamma correction of the captured image is performed so as to match the gamma characteristic of a general monitor.

(Internal configuration of the image processing unit 10)
FIG. 11 shows an internal configuration of the image processing unit 10. The image processing unit 10 controls a gradation correction operation based on scene discrimination for a captured image in the imaging apparatus 1, and after the processing in the imaging processing unit 20 or independently of the processing, A series of processes such as image acquisition, scene discrimination, and gradation processing condition setting are executed. Hereinafter, the internal configuration of the image processing unit 10 will be described with reference to FIG.

  As shown in FIG. 11, the image processing unit 10 includes a first image acquisition unit 101, a second image acquisition unit 102, an occupation rate calculation unit 103, an index calculation unit 104, a scene determination unit 105, and a gradation processing condition setting unit 106. , And a gradation conversion processing unit 107.

  The first image acquisition unit 101 acquires the image data of the latest image captured on the image sensor 33 as the first image when the release button 28 is fully pressed. That is, the first image acquisition unit 101 functions as a first image acquisition unit. In addition, the first image acquisition unit 101 divides the imaging area into a plurality of photometric areas when acquiring the first image, and acquires photometric values (luminance information) individually for each photometric area.

  Specifically, among the plurality of acquired luminance information, the first luminance information is acquired from the first area in the shooting area, and the second luminance information is acquired from the second area corresponding to the peripheral area of the first area. To do. That is, the first image acquisition unit 101 functions as a first luminance information acquisition unit and a second luminance information acquisition unit. The first luminance information and the second luminance information acquired in the present embodiment are luminance values calculated from a plurality of photometric values (Brightness Value, hereinafter, the first luminance information is referred to as BV1 and second luminance information BV2). Means. Here, the calculation method of the first luminance information BV1 and the second luminance information BV2 is not particularly limited. For example, the average value of the plurality of luminance information in the first region is set to the first luminance information BV1, the second luminance information BV2, and the second luminance information BV2. An average value of a plurality of luminance information in the area may be used as the second luminance information BV2. The acquired image data of the first image, the first luminance information BV1 and the second luminance information BV2 are stored in the memory 32.

  FIG. 13 shows an example in which the photometric area in the photographing area is divided into two, a photometric area (first area) A1 at the center and a second area A2 around the first area. Here, the first area A1 is specified based on the in-focus position detected by the focus unit 44. For example, there is a method in which the photometry area including the in-focus position is the first area, and there is another method in which the photometry area including the in-focus position and the photometry area adjacent thereto are the first area. That is, the first luminance information BV1 is acquired from the first area A1 corresponding to the main subject that is the focus target in the shooting area, and the second area A2 that is the background around the first area (main subject) is acquired. The second luminance information BV2 is acquired.

  The second image acquisition unit 102 divides the acquired first image into M × N rectangular regions (regions divided into M pieces in the vertical direction and N pieces in the horizontal direction). FIG. 12A shows an example of the first image, and FIG. 12B shows an example in which the first image is divided into M × N (14 × 22) areas. The number of divided areas is not particularly limited. In the present embodiment, each divided area is regarded as a “pixel” of image data, and the divided image is handled as an image with a substantially reduced size. This reduced image is the second image, and the second image is acquired by the above operation. Therefore, the second image acquisition unit 102 functions as a second image acquisition unit.

  The occupation ratio calculation unit 103 acquires color information for the image data of the second image, that is, for each pixel constituting the image. Based on the acquired color information, each pixel of the image is classified into a predetermined class composed of a combination of lightness and hue (see FIG. 17), and for each classified class, the pixels belonging to the class are included in the entire image. A first occupation ratio indicating the occupation ratio is calculated. That is, the occupation ratio calculation unit 103 functions as a first occupation ratio calculation unit.

  Further, the occupancy rate calculation unit 103 classifies each pixel of the second image into a predetermined class composed of a combination of the distance from the outer edge of the screen of the second image and the brightness (see FIG. 18). For each class, a second occupancy ratio indicating the ratio of pixels belonging to the class to the entire image is calculated. That is, the occupation rate calculation unit 103 also functions as a second occupation rate calculation unit.

  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 rate calculation unit 103 by a coefficient set in advance according to the shooting conditions, thereby specifying the index 1 for specifying the shooting scene, and the index 2 is calculated. That is, the index calculation unit 104 functions as a first index calculation unit and a second index calculation unit.

  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 condition, thereby obtaining an index 3 for specifying the shooting scene. calculate. That is, the index calculation unit 104 functions as a third index calculation unit and a second index calculation unit.

  Further, the index calculation unit 104 multiplies each of the average luminance value in the central portion of the screen of the second 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 condition. Thus, the index 4 for specifying the shooting scene is calculated. That is, the index calculation unit 104 functions as a fourth index calculation unit.

  In addition, the index calculation unit 104 has an average luminance value (referred to as index 7) of the skin color area in the center of the screen of the second image, index 1 and index 3, and the first luminance information BV1 and the first luminance at the time of shooting described above. A new index 5 is calculated by multiplying the two luminance information BV2 by a coefficient set in advance according to the photographing condition and taking the sum.

  In addition, the index calculation unit 104 includes the average luminance value of the skin color area in the center of the screen of the second image, the index 2 and the index 3, and the first luminance information BV1 and the second luminance information BV2 at the time of shooting described above. Then, a new index 6 is calculated by multiplying a coefficient set in advance according to the photographing condition 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 scene determination unit 105 determines the shooting scene of the first image based on each index calculated by the index calculation unit 104, the first luminance information BV1, and the second luminance information BV2. That is, the scene determination unit 105 functions as a scene determination unit. Here, the shooting scene indicates a light source condition when shooting a subject such as a front light, a backlight, a proximity flash, etc., and is a main subject (mainly a person, but is not limited to this). This includes exposure conditions such as over and under. The method for determining the shooting scene will be described later in detail.

  As described above, the occupation rate calculation unit 103, the index calculation unit 104, and the scene determination unit 105 function as a scene determination processing unit.

  The gradation processing condition setting unit 106 functions as a gradation processing condition setting unit, and sets gradation processing conditions (see FIG. 26) for the first image based on the shooting scene determined by the scene determination unit 105. . That is, the gradation processing condition setting unit 106 functions as a gradation processing condition setting unit.

  Further, the gradation processing condition setting unit 106 calculates a gradation adjustment parameter for gradation adjustment for the first image based on each index calculated by the index calculation unit 104. Therefore, the gradation processing condition setting unit 106 functions as a gradation adjustment parameter calculation unit. The setting of the gradation processing conditions will be described in detail later with reference to FIG.

  The gradation conversion processing unit 107 functions as a gradation conversion processing unit, and executes gradation conversion processing for the first image in accordance with the gradation processing conditions set in the gradation processing condition setting unit 106. That is, the gradation conversion processing unit 107 functions as a gradation conversion processing unit.

  In addition to the processing performed in the image processing unit 10, the processor 31 performs processing in the photographing processing unit 20 such as automatic white balance processing and gamma conversion processing, and other image processing, image format conversion, It has a function of controlling processing operations such as recording of image data.

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

(Operation Flow of Imaging Device 1)
Next, the operation of the imaging device 1 in the present embodiment will be described. Hereinafter, the object to be photographed 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 starts an operation for photographing by directing the imaging device 1 toward the main subject so that the main subject enters the field of the imaging device 1. The release button 28 is pressed to take a picture (step S2). The image formed on the image sensor 33 is captured as an electrical signal, and interpolation processing based on the CCD array is performed (step S4). In step S <b> 5, the first image is acquired as a captured image and held in the memory 32. The first image is a linear image and is called a RAW image. That is, steps S2, 4, and 5 function as a first image acquisition process.

  On the other hand, when shooting is performed, in step S3 which is the first luminance information acquisition step and the second luminance information acquisition step, the first luminance information BV1 and the second luminance from the first region A1 and the second region A2 of the shooting region, respectively. Information BV2 is acquired. The acquired first luminance information BV1 and second luminance information BV2 are held in the memory 32.

  The first image acquired by shooting is subjected to AWB (automatic white balance) processing (step S6). This may be processed separately for the first image and the second image after the second image described below is acquired.

  After the AWB process, the image data of the first image is acquired as a divided image composed of a plurality of divided regions, that is, a second image (step S7). Each divided region of the divided image is a pixel of the second image, and the second image is an image obtained by reducing the size of the first image. FIG. 12A shows an example of the first image, and FIG. 12B shows an example in which the first image is divided into M × N (14 × 22) cells. Each cell corresponds to one pixel of the second image. As an actual image data size reduction method, a known technique such as a simple average, a bilinear method, or a bicubic method can be used. Step S7 functions as a second image acquisition process.

  Next, in step S8, which is a scene determination processing step, a scene determination process for determining a shooting scene is performed based on the acquired first luminance information BV1, second luminance information BV2, and image data of the second image. The shooting scene determination process in step S8 will be described later with reference to FIG.

  Next, in step S9 which is a gradation processing condition setting step, it is necessary for the gradation conversion processing of the first image based on each index obtained in the scene determination processing in step S8 and the determination result of the shooting scene. Processing for setting conditions is performed. The gradation processing condition setting process in step S9 will be described later with reference to FIG.

  On the other hand, the first image after the AWB process is subjected to a gamma conversion process and converted to a non-linear image (step S10). However, the gamma conversion process is a gradation conversion process, and may be performed together with the gradation conversion process in step S11 described below.

  In step S11, which is a gradation conversion processing step, gradation conversion processing is performed on the image data of the first image, which is a captured image, based on the gradation processing conditions set based on the second image. The gamma conversion is converted into a non-linear gradation in accordance with the visual sense. However, the gradation conversion in step S11 corrects the influence on the gradation due to the light source condition of the shooting scene, and the step is determined based on the determination result in step S8. The gradation conversion processing is performed based on the processing conditions set in S9.

  In the present embodiment, gradation processing conditions are set and converted in steps S9 and S11. However, in addition to image processing for the first image that has been shot, for example, an optimal image for the shooting scene is selected. Processing such as calculating exposure conditions for acquisition in real time and reflecting them in the shooting operation may be performed. At that time, the image data of the latest image captured on the image sensor 33 at the timing when the release button 28 is half-pressed or at a predetermined timing even when the release button 28 is not pressed is used as the first image. It is good also as an aspect which acquires attitude | position information at the time of acquisition of this image.

  Next, the image format is converted for image recording (step S12). Generally, it is converted into an image in JPEG format. Thereafter, the image data in the JPEG format is recorded on a storage medium for storage (such as an SD memory card or a multimedia card (MMC)) (step S13). When the next shooting is started or the power switch 26 is turned off, the operation of the image pickup apparatus 1 ends.

(Scene discrimination process flow)
Next, with reference to the flowchart of FIG. 15 and FIGS. 16 to 24, the scene determination process (step S8 of FIG. 14) in the imaging apparatus 1 will be described.

  As shown in FIG. 15, the 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 scene determination (step S23). The Hereinafter, each process illustrated in FIG. 15 will be described in detail with reference to FIGS. 16 to 24.

First, in step S20 of FIG. 15, a color space conversion process is performed.
In this process, information indicating the RGB value, the luminance value, and the white balance of each pixel of the second image obtained from the photographed first image is acquired. As the luminance value, a value calculated by substituting RGB values into a known conversion formula may be used. Next, the acquired RGB values are converted into the HSV color system, and the color information of the image is acquired. The HSV color system represents image data with three elements of hue (Hue), saturation (Saturation), and lightness (Value or Brightness), and was devised based on the color system proposed by Munsell. It has been done. The conversion to the HSV color system is performed using an HSV conversion program or the like. Usually, the calculated hue value H is defined as 0 to 360 for the input R, G, B, The unit of saturation value S and brightness value V is defined as 0-255.

  In the present embodiment, “brightness” means “brightness” which is 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 step S20, the values of H, S, and V obtained as described above are acquired as color information.

<Occupancy rate calculation process>
Next, in step S21, an occupation ratio calculation process is performed. The occupation rate calculation process will be described with reference to the flowchart of FIG.

  First, based on the HSV value calculated by the color space conversion process, each pixel of the second image is classified into a predetermined class composed of a combination of hue and brightness, and the cumulative number of pixels is calculated for each classified class. As a result, a two-dimensional histogram is created (step S30).

  FIG. 17 shows a class composed of a combination of brightness and hue. In step S30, the lightness (V) is 0-5 (v1), 6-12 (v2), 13-24 (v3), 25-76 (v4), 77-109 (v5), 110-110. It is divided into seven classes of 149 (v6) and 150 to 255 (v7). As shown in FIG. 17, the brightness range in the highest brightness class is wider than the brightness range in the lowest brightness class.

  Hue (H) is a flesh color hue region (H1 and H2) having a hue value of 0 to 39 and 330 to 359, a green hue region (H3) having a hue value of 40 to 160, and a blue hue region having 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 known that the contribution to the determination of the shooting scene is small. The skin color hue region is further divided into a skin color region (H1) and another region (H2). Hereinafter, among the flesh-colored hue regions (H = 0 to 39, 330 to 359), the hue ′ (H) that satisfies the following formula (1) is defined as the flesh-colored region (H1), and the region that does not satisfy the formula (1) is ( 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) = R × 0.30 + G × 0.59 + B × 0.11 (A)
As
Hue '(H) / Luminance (Y) <3.0 × (Saturation (S) / 255) +0.7 (1)
Therefore, the number of classes in the second image is 4 × 7 = 28. Moreover, 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 lightness (V) in Formula (A) and Formula (1).

  After step S30, each pixel of the second 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 the two-dimensional histogram is calculated by calculating the cumulative number of pixels for each classified class. Is created (step S31).

  FIG. 18A shows three regions n1 to n3 divided in accordance with the distance from the outer edge of the second image in step S31. 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 second image. Here, n1 to n3 are preferably divided so as to have substantially the same number of pixels. In the present embodiment, three divisions are used, but the present invention is not limited to this. In step S31, the brightness is divided into seven areas v1 to v7 as described above. FIG. 18B shows a class composed of combinations of three regions n1 to n3 and brightness. As shown in FIG. 18B, the number of classes when the second 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 number of pixels calculated for each predetermined class composed of a combination of brightness and hue to the total number of pixels (M × N) Is calculated (step S32). That is, step S30 and step S32 function as a first occupancy rate calculation step.

  Assuming that the first occupancy calculated in the class composed of the combination of the lightness area vi and the hue area Hj is Rij, the first occupancy in each class is expressed as shown in Table 1.

  When the two-dimensional histogram is created in step S31, the second occupancy ratio indicating the ratio of the cumulative number of pixels calculated for each predetermined class composed of a combination of the distance from the outer edge of the screen and the brightness to the total number of pixels is obtained. Calculation is performed (step S33), and the occupancy rate calculation process ends. That is, step S31 and step S33 function as a second occupancy rate calculating step.

  When 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 pixel into a class consisting of a distance from the outer edge of the screen, brightness, and hue, and calculating the cumulative number of pixels for each class. Hereinafter, a method using a two-dimensional histogram is adopted.
<Indicator calculation process>
Next, the index calculation process (step S22 in FIG. 15) will be described with reference to the flowchart in FIG.

  First, in step S40, which is a first index calculation step, the first occupancy calculated for each class in the occupancy ratio calculation process is multiplied by a coefficient (first coefficient) set in advance according to the shooting conditions. As a result, the index 1 for specifying the shooting scene is calculated. The index 1 is an index that compositely represents characteristics of close-up flash photography such as low peripheral brightness and high brightness of the face color and when the main subject is over, and should be determined as “proximity flash” and “main subject over” This is to separate only the image from other shooting scenes.

  Next, in step S41, which is the second index calculation step, a coefficient (second coefficient) different from the first coefficient preset in accordance with the shooting conditions is added to the first occupancy ratio calculated for each class. ) To obtain the sum, the index 2 for specifying the shooting scene is calculated. 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 region distributed in the skin color hue region (H1) of high brightness (v6), and the other hue is blue. A negative (−) coefficient is used for the first occupancy calculated from the hue region. FIG. 20 shows a first coefficient in the skin color area (H1) and a first coefficient in the other area (green hue area (H3)) as a curve (coefficient curve) that continuously changes over the entire brightness. It is shown. According to Table 3 and FIG. 20, 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 both are different.

  If 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 region sum = R11 × 0 + R21 × 0 + (omitted)... + R71 × (−8) (2-1)
Sum of H2 regions = R12 × (−2) + R22 × (−1) + (omitted)... + R72 × (−10)
(2-2)
Sum of H3 regions = R13 × 5 + R23 × (−2) + (omitted)... + R73 × (−12)
(2-3)
Sum of H4 region = R14 × 0 + R24 × (−1) + (omitted)... + R74 × (−12)
(2-4)
The index 1 is defined as in Expression (3) using the sum of the H1 to H4 regions shown in Expressions (2-1) to (2-4).

Index 1 = sum of H1 region + sum of H2 region + sum of H3 region + sum of H4 region + 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 occupancy rate 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-color hue area (H1), and the flesh-color hue range (H1) is low. A coefficient 0 is used for the occupation ratio calculated from the brightness (shadow) region (v2, v3). FIG. 21 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. 21, 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 in the coefficients in both regions.

  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).

  Accordingly, the sum of the H1 to H4 regions is expressed by the following formulas (4-1) to (4-4).

Sum of H1 regions = R11 × 0 + R21 × 0 + (omitted)... + R71 × 2 (4-1)
Sum of H2 region = R12 × (−2) + R22 × (−1) + (omitted)... + R72 × 2
(4-2)
Sum of H3 regions = R13 × 2 + R23 × 1 + (omitted)... + R73 × 3 (4-3)
Sum of H4 region = R14 × 0 + R24 × (−1) + (omitted)... + R74 × 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 regions + sum of H2 regions + sum of H3 regions + sum of H4 regions + 1.7 (5)
Since the index 1 and the index 2 are calculated based on the brightness and hue distribution amount of the second image, they are effective in determining a shooting scene when the image is a color image.

  When the index 1 and the index 2 are calculated, the second occupancy ratio calculated for each class in the occupancy ratio calculation process is set in advance according to the shooting conditions in step S42 which is the third index calculation step. By multiplying the third coefficient (coefficient different from the first coefficient and the second coefficient) and taking the sum, an index 3 for specifying the shooting scene is calculated. 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.

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 occupancy Qij of each class shown in Table 2 is multiplied, and is set in advance according to the shooting conditions.

  FIG. 22 shows the third coefficient in the screen areas n1 to n3 as a curve (coefficient curve) that continuously changes over the entire brightness.

  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 represented by the following formulas (6-1) to (6-3).

Sum of n1 region = Q11 × 12 + Q21 × 10 + (omitted)... + Q71 × 0 (6-1)
Sum of n2 regions = Q12 × 5 + Q22 × 3 + (omitted)... + Q72 × 0 (6-2)
Sum of n3 regions = Q13 × (−1) + Q23 × (−4) + (omitted)... + Q73 × (−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 region + sum of n2 region + sum of n3 region + 0.7 (7)
Since the index 3 is calculated based on the compositional feature (distance from the outer edge of the screen of the entire image) based on the lightness distribution position of the second image, the photographing scene of the monochrome image as well as the color image is discriminated. It 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, in step S43, which is a fourth index calculating step, the average luminance value of the skin color at the screen center (regions n2 and n3) of the second image and the maximum of the second image are calculated. An index 4 for specifying a shooting scene is calculated by multiplying each difference value between the brightness plant and the average brightness value by a coefficient set in advance according to the shooting conditions.

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 second image using Expression (A). Next, the average luminance value x1 of the skin color area in the screen center (areas n2 and n3) of the second image is calculated (step S50). Next, a difference value x2 between the maximum luminance value and the average luminance value of the second image is calculated (maximum luminance value−average luminance value) (step S51).

  Next, the standard deviation x3 of the luminance of the second image is calculated (step S52), and the average luminance value x4 in the screen center portion (regions n2, n3) of the second image 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 second 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 formula (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 that is 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 second image but also the luminance histogram distribution information, and is particularly effective for discriminating the shooting scene from which the main subject is over and the under shooting scene.

  When the index 4 is calculated, in step S44 (see FIG. 19), which is the fifth index calculation step, the average brightness value of the skin color area at the center of the screen of the index 1, the index 3, and the second image, the first brightness The index 5 is calculated by multiplying the information and the second luminance information by a weighting factor set in advance according to the shooting conditions.

  Further, in step S45, which is the sixth index calculation step, the index 2, index 3, and the average brightness value of the skin color area in the center of the screen of the second image, the first brightness information, and the second brightness information are set according to the shooting conditions. The index 6 is calculated by multiplying the weighting factor set in advance, and this index calculation process ends.

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 second image is taken as index 7. Here, the central portion of the screen is, for example, a region composed of the regions n2 and n3 in FIG. At this time, the index 5 is defined as Expression (9) using the index 1, the index 3, the index 7, the first luminance information BV1, and the second luminance information BV2, and the index 6 is defined as the index 2, the index 3, Using the index 7, the first luminance information BV1 and the second luminance information BV2, it is defined as in Expression (10).

Index 5 = 0.40 × Index 1 + 0.23 × Index 3 + 0.01 × Index 7 + 0.02 × BV1−0.35 × BV2 + 3.48 (9)
Index 6 = 0.68 × Index 2 + 0.03 × Index 3-0.02 × Index 7−0.31 × BV1 + 0.03 × BV2 + 1.22 (10)
Here, the coefficients to be multiplied by the respective indices in the equations (9) and (10) are set in advance according to the photographing conditions.

  Further, instead of calculating the indexes 5 and 6 based on the first luminance information BV1 and the second luminance information BV2, the first luminance information BV1 and the second luminance are used to calculate the indexes 1, 2, and 3. Information BV2 may be used. In this case, it is not necessary to use the first luminance information BV1 and the second luminance information BV2 to calculate the index 5 and the index 6.

  As a method of calculating the average luminance value (for example, the average luminance value at the center of the screen) in FIG. 23, a simple addition average value of individual luminance data obtained from each light receiving unit of the imaging device 1 may be obtained. The luminance data obtained from the light receiving unit near the center of the screen, which is similar to the center-weighted average metering that is often used as the photometric method of the imaging device 1, is high in weight, and the luminance data obtained from the light receiving unit near the periphery of the screen Alternatively, a method may be used in which the weighted value is lowered to obtain the average value. 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.

<Scene discrimination>
Returning to FIG. 15, the scene discrimination will be described.
When the indices 4 to 6 are calculated by the index calculation process in step S22, 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. The indexes 5 and 6 are calculated based on the first luminance information BV1 and the second luminance information BV2 at the time of shooting, and the first luminance information BV1 and the second luminance information BV2 indirectly contribute to the determination of the shooting scene. Yes.

  FIG. 24 is a discrimination map representing the discrimination contents shown in Table 6 using the coordinate system of the indices 4-6.

(Flow of gradation processing condition setting)
Next, the gradation processing condition setting (step S9 in FIG. 14) for the image after the gamma conversion processing of the first image will be described with reference to the flowchart in FIG.

<Tone adjustment method selection>
First, a gradation adjustment method for the first image data after the gamma conversion processing is determined in step S60 according to the determined shooting scene, and when a gradation adjustment parameter is calculated in step S61, in step S62. A gradation processing condition (gradation conversion curve) is determined. In this embodiment, the case where both the gradation adjustment method and the gradation adjustment amount are determined in steps S60 and S62 is shown, but only the gradation adjustment amount may be selected or determined.

  When the gradation adjustment method is determined in step S60, as shown in FIG. 26, the gradation adjustment method A (FIG. 26 (a)) is selected when the shooting scene is front light, and when it is back light, the floor is adjusted. When the tone adjustment method B (FIG. 26B) is selected and the main subject is over, the tone adjustment method C (FIG. 26C) is selected, and when it is under, the tone adjustment method B is selected. (FIG. 26B) is selected.

  In the present embodiment, the method for determining the gradation conversion curve to be applied to the image after the gamma conversion of the first image has been described. However, when the gradation conversion process is performed before the gamma conversion, FIG. The gradation conversion is performed on a curve obtained by performing inverse conversion of gamma conversion on the 26 gradation conversion curves.

<Calculation of gradation adjustment parameters>
When the gradation adjustment method is determined, in step S61, parameters necessary for gradation adjustment are calculated based on each index calculated in the index calculation process. That is, step S61 functions as a gradation adjustment parameter calculation step. 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 into 16 bits in advance, 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 luminance of the entire photographing screen P2: Block division average luminance P3: Average luminance of the skin color area (H1) P4: Luminance correction value 1 = P1-P2
P5: Reproduction target correction value = luminance 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, with reference to FIG. 27 and FIG. 28, a calculation method of the parameter P2 (block division average luminance) will be described.
First, in order to normalize image data, a CDF (cumulative density function) is created. 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 image data is calculated. Assuming that Rx normalization data in the R plane is Rpoint, Gx normalization data in the G plane is Gpoint, and Bx normalization data in the B plane is Bpoint, the normalization data Rpoint, Gpoint, and Bpoint are expressed by the following equation (11), respectively. ) To Expression (13).

Rp0124 = {(Rx−Rmin) / (Rmax−Rmin)} × 65535
(11);
Gpoint = {(Gx−Gmin) / (Gmax−Gmin)} × 65535
(12);
Bpoint = {(Bx−Bmin) / (Bmax−Bmin)} × 65535
(13).
Next, the luminance Npoint of the pixel (Rx, Gx, Bx) is calculated by Expression (14).

Npoint = (Bpoint + Gpoint + Rpoint) / 3 (14)
FIG. 27A shows a frequency distribution (histogram) of luminance of RGB pixels before normalization. In FIG. 27A, 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 image data by Expressions (11) to (13). FIG. 27B shows a luminance histogram calculated by the equation (14). Since the captured image data is normalized by 65535, each pixel takes an arbitrary value between the maximum value of 65535 and the minimum value of 0.

  When the luminance histogram shown in FIG. 27B is divided into blocks divided by a predetermined range, a frequency distribution as shown in FIG. 27C is obtained. In FIG. 27C, the horizontal axis represents the block number (luminance) and the vertical axis represents 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 the shadow area of the luminance histogram shown in FIG. 27C, 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. 28A (or FIG. 27C), the result is as shown in FIG.

  Next, as shown in FIG. 28 (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. 28C, the number of pixels equal to or greater than the threshold is limited in the luminance histogram. FIG. 28D is a luminance histogram after the pixel number limiting process is performed.

  Each block number of the luminance histogram (FIG. 28 (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 luminance of the entire image data, and the parameter P3 is an average value of luminance of the skin color area (H1) in the image data. The key correction value of parameter P7, the key correction value 2 of parameter P7 ′, and the luminance correction value 2 of parameter P8 are defined as shown in equations (15), (16), and (17), respectively.

P7 (key correction value) = {P3-((index 6/6) × 18000 + 22000)}
/24.78 (15)
P7 ′ (key correction value 2) = {P3-((index 4/6) × 10000 + 30000)}
/24.78 (16)
P8 (Luminance correction value 2) = (Index 5/6) × 17500 (17)
The parameters P7 and P8 are based on the index 5 and the index 6 and reflect the luminance information BV.

<Setting gradation processing conditions for each scene>
Returning to FIG. 25, when the tone adjustment parameter is calculated, in step S62, the tone conversion curve for the photographed image data, that is, the tone processing condition is set based on the calculated tone adjustment parameter. The

  That is, a gradation conversion curve corresponding to a parameter value selected according to a scene is selected (determined) from a plurality of gradation conversion curves set in advance corresponding to the already determined gradation adjustment method. Is done. Alternatively, the gradation conversion curve may be calculated based on the parameter value.

When the gradation conversion curve is determined, the gradation processing condition setting ends.
Hereinafter, a method for determining a gradation conversion curve (determination of gradation processing conditions in step S62) for each shooting scene (light source condition and exposure condition) will be described.

<For direct light>
When the photographic scene is front light, offset correction (parallel shift of 8-bit value) is performed by the following equation (18) using the parameter P6 to make P1 coincide with P5.

RGB value of output image = RGB value of input image + P6 (18)
Therefore, when the photographic scene is a continuous light, a gradation conversion curve corresponding to Expression (18) is selected from a plurality of gradation conversion curves shown in FIG. Alternatively, the gradation conversion curve may be calculated (determined) based on Expression (18).

<Backlight>
When the shooting scene is backlit, a gradation conversion curve corresponding to the parameter P7 (key correction value) is selected from a plurality of gradation conversion curves shown in FIG. FIG. 29 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
In the case of −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, the gradation conversion curve corresponding to the parameter P7 ′ (key correction value 2) is selected from the plurality of gradation conversion curves shown in FIG. Specifically, the gradation conversion curve corresponding to the value of the parameter P7 ′ is selected from the gradation conversion curves shown in FIG. 29 in the same manner as the selection method of 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 the equation (19) using the parameter P9.

RGB value of output image = RGB value of input image plus P9 (19)
Therefore, when the main subject is over, the gradation conversion curve corresponding to the parameter P9 is selected from the plurality of gradation conversion curves shown in FIG. Alternatively, the gradation conversion curve may be calculated (determined) based on Expression (19). When the value of parameter P9 in equation (19) 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 above-described embodiment, the shooting scene is determined based on the first luminance information and the second luminance information in the shooting area, and the gradation processing condition according to the determined shooting scene is set. This makes it possible to discriminate shooting scenes from image data with high accuracy, and to perform gradation processing according to the discrimination results of shooting scenes such as overexposure, underexposure, forward light, and backlight scene of the main subject. Therefore, a more appropriate corrected image can be obtained.

  The embodiment of the present invention is not limited to the above-described embodiment, and various modified forms are also included in the scope thereof as long as the gist of the present invention is met.

  In the above-described embodiment, the shooting scene is determined based on the indices 4 to 6. However, the present invention is not limited to this. For example, the shooting scene is directly compared with the values of the first luminance information BV1 and the second luminance information BV2. It is good also as a mode which discriminates. In this case, if the relationship between the first luminance information BV1 and the second luminance information BV2 is “first luminance information BV1 >> second luminance information BV2,” the shooting scene is close to the flash or the main subject is over. If it is determined that “first luminance information BV1 << second luminance information BV2”, it is preferable to determine that the shooting scene is backlight.

  In the above embodiment, the first luminance information BV1 is the luminance information corresponding to the main subject, and the second luminance information BV2 is the luminance information corresponding to the periphery of the main subject, that is, the background. The first luminance information BV1 may be the luminance information of the central portion of the shooting screen (for example, the area corresponding to n3 and n2 in FIG. 16), and the second luminance information BV2 may be the average luminance information of the entire shooting screen.

It is a figure showing an example of appearance composition of imaging device 1 concerning an embodiment of the present invention. 2 is a block diagram illustrating an internal configuration of the imaging apparatus 1. FIG. 3 is a block diagram illustrating an internal configuration of a photographing processing unit 20. FIG. It is a flowchart which shows exposure amount control in an AE control part. It is a figure which shows a mode that an electric charge accumulate | stores in an image pick-up element in control of shutter speed. It is a flowchart which shows the control which adjusts the focus of the image in AF control part. It is a figure which shows the change of the contrast information accompanying the movement of an imaging optical system, and the mode of a focal point position detection. It is a flowchart which shows the process of the image data which performs the interpolation between pixels for every RGB color component in a pixel interpolation part. It is a flowchart which shows the process which automatically adjusts the white balance in a picked-up image in an AWB control part. It is a figure which shows the example of a gamma correction curve. 2 is a block diagram showing an internal configuration of an image processing unit 10. FIG. FIG. 4A is a diagram illustrating an example of a captured first image, and FIG. 4B is a diagram illustrating an example of a second image obtained by dividing the first image into a reduced image of M × N pixels. It is the figure which showed an example of 1st area | region A1 and 2nd area | region A2 in an imaging | photography area | region. 3 is a flowchart showing an overall flow of processing executed in the imaging apparatus 1. 4 is a flowchart illustrating a scene determination process executed in the image processing unit 10. It is a flowchart which shows an occupation rate calculation process. It is a figure which shows the class which consists of brightness and hue. It is a figure which shows area | region n1-n3 determined according to the distance from the outer edge of a screen, and a figure which shows the class which consists of area | region n1-n3 and a brightness. It is a flowchart which shows an index calculation process. It is a figure which shows the curve showing the 1st coefficient by which the 1st occupation rate for calculating the parameter | index 1 is multiplied. It is a figure which shows the curve showing the 2nd coefficient by which the 1st occupation rate for calculating the parameter | index 2 is multiplied. It is a 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). It is a flowchart which shows the parameter | index 4 calculation process. It is a plot figure which shows the relationship between an imaging | photography scene (forward light, strobe, backlight, under) and the indices 4-6. It is a flowchart which shows gradation processing condition setting. It is a figure which shows the gradation conversion curve corresponding to each gradation adjustment method. It is a figure which shows the frequency distribution (histogram) (a) of a brightness | luminance, the normalized histogram (b), and the block-divided histogram (c). FIG. 2A and FIG. 2B illustrate the deletion of the low-brightness region and the high-brightness region from the luminance histogram, and FIG. 2B illustrates the limitation on the luminance frequency ((c) and (d)). is there. It is a figure which shows the gradation conversion curve showing the gradation processing conditions in case a imaging | photography scene is backlight or under.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Imaging device 10 Image processing part 20 Imaging processing part 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 Imaging element 37 Image data output part 38 Operation part 41 Timing generator 42 Shutter unit 43 Aperture unit 44 Focus unit 51 AE control unit 52 AF control unit 53 Pixel interpolation unit 54 AWB control unit 55 Gamma correction unit 101 First image acquisition unit 102 Second image acquisition unit 103 Occupancy rate calculation unit 104 Index Calculation unit 105 Scene discrimination unit 106 Gradation processing condition setting unit 107 Gradation conversion processing unit

Claims (18)

First image acquisition means for acquiring a first image by photographing;
First luminance information acquisition means for acquiring first luminance information in a predetermined first area from a photometric value of the imaging area calculated at the time of shooting;
Second luminance information acquisition means for acquiring second luminance information in a second area around the first area from the calculated photometric value of the imaging area;
Scene discrimination processing means for discriminating a shooting scene based on the acquired first luminance information, second luminance information and the first image;
Gradation processing condition setting means for setting gradation processing conditions for the first image based on a determination result by the scene determination processing means;
An imaging apparatus comprising: The scene discrimination processing means includes
Color information is acquired from the image data of the first image, and the image data is classified into classes composed of combinations of predetermined brightness and hue based on the acquired color information, and for each of the classified classes, First occupancy ratio calculating means for calculating a first occupancy ratio indicating a ratio of the entire image data;
Based on the acquired color information, the image data is classified into a class composed of a combination of the distance from the outer edge of the screen and the brightness, and a second ratio indicating the ratio of the entire image data to each classified class. Second occupancy rate calculating means for calculating the occupancy rate of
First index calculating means for calculating index 1 by multiplying the first occupancy by a preset first coefficient;
A second index calculating means for calculating index 2 by multiplying the first occupancy by a preset second coefficient;
A third index calculating means for calculating index 3 by multiplying the second occupancy by a preset third coefficient;
A fourth index calculating means for calculating index 4 by multiplying an average brightness of the skin color at least in the center of the screen of the image data by a preset fourth coefficient;
Scene discriminating means for discriminating a shooting scene of the image data based on the index 1, the index 2, the index 3, the index 4, the first luminance information and the second luminance information;
The imaging apparatus according to claim 1, further comprising: Second image acquisition means for acquiring a second image obtained by reducing the image size from the first image acquired by the first image acquisition means;
The imaging apparatus according to claim 1, wherein the scene determination processing unit determines a photographic scene based on the second image acquired by the second image acquisition unit. The gradation processing condition setting means includes:
Gradation adjustment parameter calculation means for calculating a gradation adjustment parameter based on an index calculated based on the first image, the first luminance information, and the second luminance information;
The gradation processing condition for the first image is set based on a determination result by the scene determination processing unit and the gradation adjustment parameter calculated by the gradation adjustment parameter calculation unit. The imaging device according to any one of Items 1 to 3.   5. A gradation conversion processing unit that performs gradation conversion processing on the first image based on a gradation processing condition set by the gradation processing condition setting unit. The imaging device according to any one of the above. Focusing is performed with respect to a specific object to be photographed in the photographing region, and focusing means for detecting the focal position is provided.
The imaging apparatus according to claim 1, wherein the first luminance information acquisition unit specifies the first region based on a focal position detected by the focusing unit. . A first image acquisition step of acquiring a first image by photographing;
A first luminance information acquisition step of acquiring first luminance information in a predetermined first area from a photometric value of the imaging area calculated at the time of shooting;
A second luminance information acquisition step of acquiring second luminance information in a second region around the first region from the photometric value of the calculated imaging region;
A scene determination processing step of determining a photographic scene based on the acquired first luminance information, second luminance information, and second image;
A gradation processing condition setting step for setting a gradation processing condition for the first image based on a determination result by the scene determination processing step;
An image processing method comprising: The scene discrimination processing step includes
Color information is acquired from the image data of the first image, and the image data is classified into classes composed of combinations of predetermined brightness and hue based on the acquired color information, and for each of the classified classes, A first occupancy ratio calculating step of calculating a first occupancy ratio indicating a ratio of the entire image data;
Based on the acquired color information, the image data is classified into a class composed of a combination of the distance from the outer edge of the screen and the brightness, and a second ratio indicating the ratio of the entire image data to each classified class. A second occupancy rate calculating step for calculating the occupancy rate of
A first index calculation step of calculating index 1 by multiplying the first occupancy by a preset first coefficient;
A second index calculating step of calculating index 2 by multiplying the first occupancy by a preset second coefficient;
A third index calculating step of calculating index 3 by multiplying the second occupancy by a preset third coefficient;
A fourth index calculating step of calculating index 4 by multiplying an average brightness of the skin color at least in the center of the screen of the image data by a preset fourth coefficient;
A scene determination step of determining a shooting scene of the image data based on the index 1, the index 2, the index 3, the index 4, the first luminance information, and the second luminance information;
The image processing method according to claim 7, further comprising: Including a second image acquisition step of acquiring a second image obtained by reducing the image size from the first image acquired by the first image acquisition step;
9. The image processing method according to claim 7, wherein the scene discrimination processing step discriminates a photographic scene based on the second image acquired by the second image acquisition means. The gradation processing condition setting step includes
A gradation adjustment parameter calculating step of calculating a gradation adjustment parameter based on an index calculated based on the first image, the first luminance information, and the second luminance information;
The gradation processing condition for the first image is set based on a determination result by the scene determination processing step and the gradation adjustment parameter calculated by the gradation adjustment parameter calculation step. Item 10. The image processing method according to any one of Items 7 to 9.   The gradation conversion processing step of performing gradation conversion processing on the first image based on the gradation processing condition set by the gradation processing condition setting step is included. An image processing method according to claim 1. Focusing on a specific object to be photographed in the photographing region, and including a focusing step of detecting the focal point position;
The image processing method according to claim 7, wherein the first luminance information acquisition step specifies the first region based on a focus position detected by the focusing step. In the computer for executing image processing,
A first image acquisition function for acquiring a first image by photographing;
A first luminance information acquisition function for acquiring first luminance information in a predetermined first area from a photometric value of the imaging area calculated at the time of shooting;
A second luminance information acquisition function for acquiring second luminance information in a second region around the first region from the photometric value of the calculated imaging region;
A scene discrimination processing function for discriminating a shooting scene based on the acquired first luminance information, second luminance information, and second image;
A gradation processing condition setting function for setting gradation processing conditions for the first image based on a determination result by the scene determination processing function;
An image processing program that realizes The scene discrimination processing function is
Color information is acquired from the image data of the first image, and the image data is classified into classes composed of combinations of predetermined brightness and hue based on the acquired color information, and for each of the classified classes, A first occupancy ratio calculating function for calculating a first occupancy ratio indicating a ratio of the entire image data;
Based on the acquired color information, the image data is classified into a class composed of a combination of the distance from the outer edge of the screen and the brightness, and a second ratio indicating the ratio of the entire image data to each classified class. A second occupancy ratio calculating function for calculating the occupancy ratio of
A first index calculation function for calculating index 1 by multiplying the first occupancy by a preset first coefficient;
A second index calculation function for calculating index 2 by multiplying the first occupancy by a preset second coefficient;
A third index calculation function for calculating index 3 by multiplying the second occupancy by a preset third coefficient;
A fourth index calculation function for calculating index 4 by multiplying an average brightness of the skin color at least in the center of the screen of the image data by a preset fourth coefficient;
A scene discrimination function for discriminating a shooting scene of the image data based on the index 1, the index 2, the index 3, the index 4, the first luminance information, and the second luminance information;
The image processing program according to claim 13, further comprising: In the computer,
Realizing a second image acquisition function for acquiring a second image obtained by reducing the image size from the first image acquired by the first image acquisition function;
15. The image processing program according to claim 13, wherein the scene discrimination processing function discriminates a shooting scene based on the second image acquired by the second image acquisition function. The gradation processing condition setting function is
A gradation adjustment parameter calculation function for calculating a gradation adjustment parameter based on an index calculated based on the first image, the first luminance information, and the second luminance information;
The gradation processing condition for the first image is set based on a determination result by the scene determination processing function and the gradation adjustment parameter calculated by the gradation adjustment parameter calculation function. Item 16. The image processing program according to any one of Items 13 to 15. In the computer,
The gradation conversion processing function for performing gradation conversion processing on the first image is realized based on the gradation processing conditions set by the gradation processing condition setting function. The image processing program according to any one of the above. In the computer,
Focusing on a specific object to be photographed in the photographing region, realizing a focusing function for detecting the focal position,
The image processing according to any one of claims 13 to 17, wherein the first luminance information acquisition function specifies the first region based on a focal position detected by the focusing means. program.

Images