JP2006092133A - Image processing method, image processor, imaging device and image processing program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To improve brightness reproducibility of a photographic object by determining a gradation adjustment method on the basis of an index quantitatively expressing a photographic condition of photographic image data and a distinction map showing reliability of the index. <P>SOLUTION: An image adjustment processing part 701 divides the photographic image data into areas each comprising combination of prescribed brightness and hue, an occupation ratio showing a ratio of the divided area to the whole photographic image data is calculated in each the divided area, and a deviation amount showing deviation of a gradation distribution of the photographic image data is calculated. The index for specifying the photographic condition is calculated on the basis of the calculated occupation ratio and deviation amount, and the photographic condition of the photographic image data is distinguished on the basis of the calculated index and the distinction map previously area-divided according to a reliability degree of the photographic condition. A method for gradation adjustment to the photographic image data is determined according to the distinguished photographic condition, and gradation conversion processing is applied to the photographic image data by use of the determined gradation adjustment method. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

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

  Conventionally, the brightness correction of a film scan image or a digital camera image has been performed by correcting the average brightness of the entire image to a value desired by the user. In normal shooting, the light source conditions such as forward light, backlight, and strobe light fluctuate in various ways, resulting in a large area with a large luminance deviation in the image. Additional correction using values calculated by regression analysis was necessary. However, the discriminant regression analysis method has a problem that it is difficult to discriminate shooting conditions (shooting scenes) because the parameters calculated from the strobe scene and the backlight scene are very similar.

  Patent Document 1 discloses a method for calculating an additional correction value in place of the discriminant regression analysis method. In the method described in Patent Document 1, a luminance histogram indicating the cumulative number of pixels (frequency number) of luminance is deleted from the high luminance region and the sub luminance region, and further, the luminance average is used by using the frequency number limited. A value is calculated, and a difference between the average value and the reference luminance is obtained as a correction value.

  Patent Document 2 describes a method of determining a light source state at the time of photographing in order to compensate for the extraction accuracy of a face region. In the method described in Patent Document 2, first, a face candidate region is extracted, and the bias of the average brightness of the extracted face candidate region with respect to the entire image is calculated. When the amount of deviation is large, shooting conditions (backlight shooting or strobe proximity shooting) are calculated. And the permissible width of the determination criterion as the face area is adjusted. Japanese Patent Laid-Open No. 6-67320 discloses a method of using a two-dimensional histogram of hue and saturation, Japanese Patent Laid-Open No. 8-122944, and Japanese Patent Laid-Open No. 8-184925. And pattern matching and pattern search methods described in Japanese Patent Laid-Open No. 9-138471.

Further, in Patent Document 2, as background area removal methods other than the face, the ratio of the straight line portion, the line target property, and the outer edge of the screen described in JP-A-8-122944 and JP-A-8-184925 are described. A method of determining using a contact rate, density contrast, density change pattern and periodicity is cited. A method of using a one-dimensional histogram of density is described for determining the photographing condition. This method is based on an empirical rule that the face area is dark and the background area is bright in the case of backlighting, and the face area is bright and the background area is dark in the case of close-up flash photography.
JP 2002-247393 A JP 2000-148980 A

  However, although the technique described in Patent Document 1 reduces the influence of a region with a large luminance deviation in a backlight scene and a strobe scene, the brightness of the face region is inappropriate in a shooting scene having a person as a main subject. There was a problem that there was. In addition, the technique described in Patent Document 2 can achieve the effect of compensating for the identification of the face area in the case of typical backlighting or close-up flash photography, but if it does not apply to the typical composition, There was a problem that the effect could not be obtained.

  Also, many image data taken with a digital camera were taken with an inappropriate exposure condition, and most of them are under images due to underexposure. When discriminating shooting conditions derived from light source conditions such as backlighting or close-up flash photography, there is a problem that the under image is mistaken for close-up flash photography and the over image is mistaken for a backlight scene, leading to density correction in the exact opposite direction. It was.

  As described above, in order to realize quantitative correction based on a person's face area, improvement of the imaging condition discrimination capability is an important issue. Furthermore, countermeasures against erroneous determination of shooting conditions, such as evaluating the reliability of the determination result of shooting conditions, are desired.

  An object of the present invention is to determine a gradation adjustment method based on an index that quantitatively represents shooting conditions (light source condition and exposure condition) of captured image data and a discrimination map that evaluates the reliability of the index. It is to improve the lightness reproducibility.

In order to solve the above-mentioned problem, the invention described in claim 1 divides the photographed image data into regions composed of combinations of predetermined brightness and hue, and occupies the entire photographed image data for each of the divided regions. An occupancy ratio calculating step for calculating an occupancy ratio indicating a ratio;
A deviation amount calculating step of calculating a deviation amount indicating a deviation in gradation distribution of the photographed image data;
In order to specify the shooting condition by multiplying the occupation ratio of each region calculated in the occupation ratio calculation step and the deviation amount calculated in the deviation amount calculation step by a coefficient set in advance according to the imaging condition An index calculation process for calculating an index of
A determination step of determining a shooting condition of the captured image data based on the calculated index and a determination map divided in advance according to the accuracy of the shooting condition;
An adjustment method determining step for determining a method of gradation adjustment for the captured image data according to the determined imaging condition;
A gradation conversion step of performing gradation conversion processing on the photographed image data using the determined gradation adjustment method.

According to the second aspect of the present invention, the captured image data is divided into regions each having a predetermined combination of brightness and hue, and an occupancy ratio indicating the proportion of the entire captured image data is calculated for each of the divided regions. An occupancy calculation step to perform,
A deviation amount calculating step of calculating a deviation amount indicating a deviation in gradation distribution of the photographed image data;
In order to specify the shooting condition by multiplying the occupation ratio of each region calculated in the occupation ratio calculation step and the deviation amount calculated in the deviation amount calculation step by a coefficient set in advance according to the imaging condition An index calculation process for calculating an index of
A determination step of determining a shooting condition of the captured image data based on the calculated index and a determination map divided in advance according to the accuracy of the shooting condition;
An adjustment method determining step for determining a method of gradation adjustment for the captured image data according to the determined imaging condition;
An adjustment amount determining step for determining a gradation adjustment amount for the captured image data based on the calculated index;
A gradation conversion step of performing gradation conversion processing of the gradation adjustment amount determined in the adjustment amount determination step on the captured image data using the gradation adjustment method determined in the adjustment method determination step; It is characterized by including.

According to a third aspect of the present invention, the captured image data is divided into a predetermined area composed of a combination of the distance from the outer edge of the screen of the captured image data and the brightness, and the captured image data is divided for each of the divided areas. An occupancy ratio calculating step for calculating an occupancy ratio indicating a ratio to the whole;
A deviation amount calculating step of calculating a deviation amount indicating a deviation in gradation distribution of the photographed image data;
In order to specify the shooting condition by multiplying the occupation ratio of each region calculated in the occupation ratio calculation step and the deviation amount calculated in the deviation amount calculation step by a coefficient set in advance according to the imaging condition An index calculation process for calculating an index of
A determination step of determining a shooting condition of the captured image data based on the calculated index and a determination map divided in advance according to the accuracy of the shooting condition;
An adjustment method determining step for determining a method of gradation adjustment for the captured image data according to the determined imaging condition;
A gradation conversion step of performing gradation conversion processing on the photographed image data using the determined gradation adjustment method.

According to the fourth aspect of the present invention, the captured image data is divided into a predetermined area composed of a combination of the distance from the outer edge of the screen of the captured image data and the brightness, and the captured image data is divided for each of the divided areas. An occupancy ratio calculating step for calculating an occupancy ratio indicating a ratio to the whole;
A deviation amount calculating step of calculating a deviation amount indicating a deviation in gradation distribution of the photographed image data;
In order to specify the shooting condition by multiplying the occupation ratio of each region calculated in the occupation ratio calculation step and the deviation amount calculated in the deviation amount calculation step by a coefficient set in advance according to the imaging condition An index calculation process for calculating an index of
A determination step of determining a shooting condition of the captured image data based on the calculated index and a determination map divided in advance according to the accuracy of the shooting condition;
An adjustment method determining step for determining a method of gradation adjustment for the captured image data according to the determined imaging condition;
An adjustment amount determining step for determining a gradation adjustment amount for the captured image data based on the calculated index;
A gradation conversion step of performing gradation conversion processing of the gradation adjustment amount determined in the adjustment amount determination step on the captured image data using the gradation adjustment method determined in the adjustment method determination step; It is characterized by including.

According to the fifth aspect of the present invention, the captured image data is divided into regions each having a predetermined combination of brightness and hue, and the first occupation indicating the ratio of the divided regions to the entire captured image data. The ratio is calculated, and the photographed image data is divided into predetermined regions each composed of a combination of the distance from the outer edge of the screen of the photographed image data and the brightness, and each of the divided regions occupies the entire photographed image data. An occupancy ratio calculating step of calculating a second occupancy ratio indicating a ratio;
A deviation amount calculating step of calculating a deviation amount indicating a deviation in gradation distribution of the photographed image data;
By multiplying the first occupancy ratio and the second occupancy ratio calculated in the occupancy ratio calculation step and the deviation amount calculated in the deviation amount calculation step by a coefficient set in advance according to the shooting condition. An index calculation step for calculating an index for specifying the shooting conditions;
A determination step of determining a shooting condition of the captured image data based on the calculated index and a determination map divided in advance according to the accuracy of the shooting condition;
An adjustment method determining step for determining a method of gradation adjustment for the captured image data according to the determined imaging condition;
A gradation conversion step of performing gradation conversion processing on the photographed image data using the determined gradation adjustment method.

The invention according to claim 6 divides the photographed image data into regions composed of a combination of predetermined lightness and hue, and a first occupation indicating a ratio of the divided regions to the entire photographed image data. The ratio is calculated, and the photographed image data is divided into a predetermined region composed of a combination of the distance from the outer edge of the screen of the photographed image data and the brightness, and the divided region occupies the entire photographed image data. An occupancy ratio calculating step of calculating a second occupancy ratio indicating a ratio;
A deviation amount calculating step of calculating a deviation amount indicating a deviation in gradation distribution of the photographed image data;
By multiplying the first occupancy ratio and the second occupancy ratio calculated in the occupancy ratio calculation step and the deviation amount calculated in the deviation amount calculation step by a coefficient set in advance according to the shooting condition. An index calculation step for calculating an index for specifying the shooting conditions;
A determination step of determining a shooting condition of the captured image data based on the calculated index and a determination map divided in advance according to the accuracy of the shooting condition;
An adjustment method determining step for determining a method of gradation adjustment for the captured image data according to the determined imaging condition;
An adjustment amount determining step for determining a gradation adjustment amount for the captured image data based on the calculated index;
A gradation conversion step of performing gradation conversion processing of the gradation adjustment amount determined in the adjustment amount determination step on the captured image data using the gradation adjustment method determined in the adjustment method determination step; It is characterized by including.

The invention according to claim 7 is the image processing method according to claim 3 or 4, wherein a two-dimensional histogram is created by calculating the cumulative number of pixels for each distance and brightness from the outer edge of the screen of the captured image data. Including the steps of:
In the occupancy rate calculating step, the occupancy rate is calculated based on the created two-dimensional histogram.

The invention according to claim 8 is the image processing method according to claim 5 or 6, wherein a two-dimensional histogram is created by calculating the cumulative number of pixels for each distance and brightness from the outer edge of the screen of the captured image data. Including the steps of:
In the occupation rate calculating step, the second occupation rate is calculated based on the created two-dimensional histogram.

According to a ninth aspect of the present invention, in the image processing method according to the first or second aspect, the step of creating a two-dimensional histogram by calculating the cumulative number of pixels for each predetermined hue and brightness of the photographed image data. Including
In the occupancy rate calculating step, the occupancy rate is calculated based on the created two-dimensional histogram.

A tenth aspect of the present invention is the image processing method according to the fifth or sixth aspect, wherein a step of creating a two-dimensional histogram by calculating the cumulative number of pixels for each predetermined hue and brightness of the photographed image data. Including
In the occupation rate calculating step, the first occupation rate is calculated based on the created two-dimensional histogram.

  The invention according to claim 11 is the image processing method according to any one of claims 1, 2, 5, 6, 8 to 10, and in the index calculation step, a skin color hue region having a predetermined high brightness and The coefficient of a different sign is used for the hue area other than the high brightness skin color hue area.

  The image processing method according to any one of claims 1, 2, 5, 6, and 8 to 11, wherein, in the index calculation step, an intermediate brightness area of a flesh color area, It is characterized in that coefficients having different signs are used in lightness regions other than the intermediate lightness region.

  A thirteenth aspect of the present invention is the image processing method according to the eleventh aspect, wherein a lightness area of a hue area other than the high-brightness skin color hue area is a predetermined high-lightness area.

  According to a fourteenth aspect of the present invention, in the image processing method according to the twelfth aspect, the lightness region other than the intermediate lightness region is a lightness region within a flesh-color hue region.

  According to a fifteenth aspect of the present invention, in the image processing method according to the eleventh or thirteenth aspect, the high lightness skin color hue region includes a region having a lightness value of 170 to 224 in the HSV color system. It is characterized by that.

  According to a sixteenth aspect of the present invention, in the image processing method according to the twelfth or fourteenth aspect, the intermediate lightness region includes a region in the range of 85 to 169 as a lightness value of the HSV color system. It is said.

  The invention according to claim 17 is the image processing method according to any one of claims 11, 13, and 15, wherein a hue region other than the high brightness skin color hue region includes a blue hue region and a green hue region. It is characterized by including at least one of these.

  According to an eighteenth aspect of the present invention, in the image processing method according to any one of the twelfth, fourteenth, and sixteenth aspects, a lightness area other than the intermediate lightness area is a shadow area.

  The invention according to claim 19 is the image processing method according to claim 17, wherein a hue value of the blue hue region is in a range of 161 to 250 as a hue value of the HSV color system, and the green hue region The hue value is a hue value of the HSV color system and is in the range of 40 to 160.

  According to a twentieth aspect of the present invention, in the image processing method according to the eighteenth aspect, the lightness value of the shadow area is in the range of 26 to 84 as the lightness value of the HSV color system.

  The invention according to claim 21 is the image processing method according to any one of claims 11 to 20, wherein the hue value of the flesh color hue region is a hue value of HSV color system 0 to 39 and 330 to It is characterized by being in the range of 359.

  The invention according to claim 22 is the image processing method according to any one of claims 11 to 21, wherein the skin color hue region is divided into two regions by a predetermined conditional expression based on brightness and saturation. It is characterized by that.

  According to a twenty-third aspect of the present invention, in the image processing method according to any one of the first to twenty-second aspects, the deviation amount includes a deviation amount of brightness of captured image data, a center of a screen of the captured image data. It is characterized in that at least one of an average brightness value and a brightness difference value calculated under different conditions is included.

  Here, the brightness deviation amount of the photographed image data is, for example, the standard deviation or variance of the brightness of the photographed image data. Further, the average brightness value of the captured image data at the center of the screen is, for example, the average brightness value at the center of the screen, the average brightness value of the skin color area at the center of the screen, or the like. The brightness difference value calculated under different conditions is, for example, the difference value between the maximum luminance value and the minimum luminance value of the captured image data.

The invention according to claim 24 is the image processing method according to any one of claims 1 to 23, wherein the photographing condition indicates a light source condition and an exposure condition at the time of photographing,
The light source condition includes a flash photographing state, and the exposure condition includes an under photographing state derived from a shutter speed and an aperture value at the time of photographing.

The invention described in claim 25 divides the photographed image data into regions composed of combinations of predetermined brightness and hue, and calculates an occupancy ratio indicating the proportion of the entire photographed image data for each of the divided regions. Occupancy ratio calculating means to
A deviation amount calculating means for calculating a deviation amount indicating a deviation in gradation distribution of the photographed image data;
To specify the shooting condition by multiplying the occupation ratio of each area calculated by the occupancy ratio calculating means and the deviation amount calculated by the deviation amount calculating means by a coefficient set in advance according to the shooting conditions. Index calculating means for calculating the index of
A discriminating means for discriminating a photographing condition of the photographed image data based on the calculated index and a discriminant map previously divided according to the accuracy of the photographing condition;
An adjustment method determining means for determining a method of gradation adjustment for the captured image data according to the determined imaging condition;
Gradation conversion means for performing gradation conversion processing on the photographed image data using the determined gradation adjustment method.

The invention described in claim 26 divides the photographed image data into regions composed of a combination of predetermined brightness and hue, and calculates an occupancy ratio indicating a proportion of the entire photographed image data for each of the divided regions. Occupancy ratio calculating means to
A deviation amount calculating means for calculating a deviation amount indicating a deviation in gradation distribution of the photographed image data;
To specify the shooting condition by multiplying the occupation ratio of each area calculated by the occupancy ratio calculating means and the deviation amount calculated by the deviation amount calculating means by a coefficient set in advance according to the shooting conditions. Index calculating means for calculating the index of
A discriminating means for discriminating a photographing condition of the photographed image data based on the calculated index and a discriminant map previously divided according to the accuracy of the photographing condition;
An adjustment method determining means for determining a method of gradation adjustment for the captured image data according to the determined imaging condition;
Adjustment amount determining means for determining a gradation adjustment amount for the captured image data based on the calculated index;
Gradation conversion means for performing gradation conversion processing of the gradation adjustment amount determined by the adjustment amount determination means on the captured image data using the gradation adjustment method determined by the adjustment method determination means; It is characterized by having.

The invention described in claim 27 divides the photographed image data into predetermined regions composed of combinations of the distance from the outer edge of the screen of the photographed image data and the brightness, and the photographed image data for each of the divided regions. An occupancy ratio calculating means for calculating an occupancy ratio indicating a ratio of the whole;
A deviation amount calculating means for calculating a deviation amount indicating a deviation in gradation distribution of the photographed image data;
To specify the shooting condition by multiplying the occupation ratio of each area calculated by the occupancy ratio calculating means and the deviation amount calculated by the deviation amount calculating means by a coefficient set in advance according to the shooting conditions. Index calculating means for calculating the index of
A discriminating means for discriminating a photographing condition of the photographed image data based on the calculated index and a discriminant map previously divided according to the accuracy of the photographing condition;
An adjustment method determining means for determining a method of gradation adjustment for the captured image data according to the determined imaging condition;
Gradation conversion means for performing gradation conversion processing on the photographed image data using the determined gradation adjustment method.

The invention described in claim 28 divides the photographed image data into predetermined regions comprising a combination of the distance from the outer edge of the screen of the photographed image data and the brightness, and the photographed image data for each of the divided regions. An occupancy ratio calculating means for calculating an occupancy ratio indicating a ratio of the whole;
A deviation amount calculating means for calculating a deviation amount indicating a deviation in gradation distribution of the photographed image data;
To specify the shooting condition by multiplying the occupation ratio of each area calculated by the occupancy ratio calculating means and the deviation amount calculated by the deviation amount calculating means by a coefficient set in advance according to the shooting conditions. Index calculating means for calculating the index of
A discriminating means for discriminating a photographing condition of the photographed image data based on the calculated index and a discriminant map previously divided according to the accuracy of the photographing condition;
An adjustment method determining means for determining a method of gradation adjustment for the captured image data according to the determined imaging condition;
Adjustment amount determining means for determining a gradation adjustment amount for the captured image data based on the calculated index;
Gradation conversion means for performing gradation conversion processing of the gradation adjustment amount determined by the adjustment amount determination means on the captured image data using the gradation adjustment method determined by the adjustment method determination means; It is characterized by having.

According to a twenty-ninth aspect of the present invention, the photographed image data is divided into regions each having a predetermined combination of brightness and hue, and the first occupation indicating the ratio of the divided regions to the whole photographed image data. The ratio is calculated, and the photographed image data is divided into predetermined regions each composed of a combination of the distance from the outer edge of the screen of the photographed image data and the brightness, and each of the divided regions occupies the entire photographed image data. An occupancy ratio calculating means for calculating a second occupancy ratio indicating a ratio;
A deviation amount calculating means for calculating a deviation amount indicating a deviation in gradation distribution of the photographed image data;
By multiplying the first occupancy ratio and the second occupancy ratio calculated by the occupancy ratio calculating means and the deviation amount calculated by the deviation amount calculating means by a coefficient set in advance according to the photographing condition. , An index calculating means for calculating an index for specifying the shooting conditions;
A discriminating means for discriminating a photographing condition of the photographed image data based on the calculated index and a discriminant map previously divided according to the accuracy of the photographing condition;
An adjustment method determining means for determining a method of gradation adjustment for the captured image data according to the determined imaging condition;
Gradation conversion means for performing gradation conversion processing on the photographed image data using the determined gradation adjustment method.

According to a thirty-third aspect of the present invention, the photographed image data is divided into regions each having a predetermined combination of brightness and hue, and a first occupation indicating a ratio of the divided regions to the whole photographed image data. The ratio is calculated, and the photographed image data is divided into predetermined regions each composed of a combination of the distance from the outer edge of the screen of the photographed image data and the brightness, and each of the divided regions occupies the entire photographed image data. An occupancy ratio calculating means for calculating a second occupancy ratio indicating a ratio;
A deviation amount calculating means for calculating a deviation amount indicating a deviation in gradation distribution of the photographed image data;
By multiplying the first occupancy ratio and the second occupancy ratio calculated by the occupancy ratio calculating means and the deviation amount calculated by the deviation amount calculating means by a coefficient set in advance according to the photographing condition. , An index calculating means for calculating an index for specifying the shooting conditions;
A discriminating means for discriminating a photographing condition of the photographed image data based on the calculated index and a discriminant map previously divided according to the accuracy of the photographing condition;
An adjustment method determining means for determining a method of gradation adjustment for the captured image data according to the determined imaging condition;
Adjustment amount determining means for determining a gradation adjustment amount for the captured image data based on the calculated index;
Gradation conversion means for performing gradation conversion processing of the gradation adjustment amount determined by the adjustment amount determination means on the captured image data using the gradation adjustment method determined by the adjustment method determination means; It is characterized by having.

The invention according to claim 31 is the image processing device according to claim 27 or 28, wherein a two-dimensional histogram is created by calculating the cumulative number of pixels for each distance and brightness from the outer edge of the screen of the photographed image data. Means to
The occupancy rate calculation means calculates the occupancy rate based on the created two-dimensional histogram.

A thirty-second aspect of the present invention is the image processing apparatus according to the twenty-ninth or thirty-third aspect, wherein a two-dimensional histogram is created by calculating a cumulative number of pixels for each distance and brightness from the outer edge of the screen of the captured image data. Means to
The occupancy rate calculation means calculates the second occupancy rate based on the created two-dimensional histogram.

According to a thirty-third aspect of the present invention, in the image processing apparatus according to the twenty-fifth or twenty-sixth aspect, means for creating a two-dimensional histogram by calculating the cumulative number of pixels for each predetermined hue and brightness of the photographed image data. Prepared,
The occupancy rate calculation means calculates the occupancy rate based on the created two-dimensional histogram.

According to a thirty-fourth aspect of the present invention, in the image processing apparatus according to the thirty-ninth or thirty-third aspect, means for creating a two-dimensional histogram by calculating the cumulative number of pixels for each predetermined hue and lightness of the photographed image data. Prepared,
The occupancy rate calculation means calculates the first occupancy rate based on the created two-dimensional histogram.

  The invention described in claim 35 is the image processing apparatus according to any one of claims 25, 26, 29, 30, 32 to 34, wherein the index calculating means includes a skin color hue region having a predetermined high brightness, The coefficient of a different sign is used for the hue area other than the high brightness skin color hue area.

  The invention described in claim 36 is the image processing device according to any one of claims 25, 26, 29, 30, 32 to 35, wherein the index calculating means includes an intermediate brightness area of a flesh-color hue area, It is characterized in that coefficients having different signs are used in lightness regions other than the intermediate lightness region.

  A thirty-seventh aspect of the present invention is the image processing apparatus according to the thirty-fifth aspect, characterized in that a lightness region of a hue region other than the high lightness skin color hue region is a predetermined high lightness region.

  According to a thirty-eighth aspect of the present invention, in the image processing apparatus according to the thirty-sixth aspect, the lightness area other than the intermediate lightness area is a lightness area within a flesh-color hue area.

  According to a thirty-ninth aspect of the present invention, in the image processing apparatus according to the thirty-fifth or thirty-seventh aspect, the high lightness skin color hue region includes a region having a lightness value of 170 to 224 in the HSV color system. It is characterized by that.

  According to a forty-second aspect of the present invention, in the image processing apparatus according to the thirty-sixth or thirty-eighth aspect, the intermediate lightness region includes a region in the range of 85 to 169 as a lightness value of the HSV color system. It is said.

  The invention according to claim 41 is the image processing apparatus according to any one of claims 35, 37, and 39, wherein a hue region other than the high brightness skin color hue region includes a blue hue region and a green hue region. It is characterized by including at least one of these.

  A forty-second aspect of the present invention is the image processing apparatus according to any one of the thirty-sixth, thirty-eight and thirty-fourth aspects, wherein the brightness area other than the intermediate brightness area is a shadow area.

  The invention according to claim 43 is the image processing apparatus according to claim 41, wherein a hue value of the blue hue region is in a range of 161 to 250 as a hue value of the HSV color system, and the green hue region The hue value is a hue value of the HSV color system and is in the range of 40 to 160.

  According to a 44th aspect of the present invention, in the image processing apparatus according to the 42nd aspect, the lightness value of the shadow area is in the range of 26 to 84 as the lightness value of the HSV color system.

  According to a 45th aspect of the present invention, in the image processing device according to any one of the 35th to 44th aspects, the hue value of the flesh color hue region is a hue value of HSV color system of 0 to 39 and 330 to It is characterized by being in the range of 359.

  The invention according to claim 46 is the image processing apparatus according to any one of claims 35 to 45, wherein the skin color hue region is divided into two regions by a predetermined conditional expression based on brightness and saturation. It is characterized by that.

  According to a 47th aspect of the present invention, in the image processing device according to any one of the 25th to 46th aspects, the deviation amount includes a deviation amount of brightness of the captured image data, a center of the screen of the captured image data. It is characterized in that at least one of an average brightness value and a brightness difference value calculated under different conditions is included.

The invention according to claim 48 is the image processing apparatus according to any one of claims 25 to 47, wherein the photographing condition indicates a light source condition and an exposure condition at the time of photographing,
The light source condition includes a flash photographing state, and the exposure condition includes an under photographing state derived from a shutter speed and an aperture value at the time of photographing.

The invention according to claim 49, the imaging means for capturing the captured image data by capturing the subject,
Occupancy rate calculating means for dividing the photographed image data into regions composed of combinations of predetermined brightness and hue, and for each of the divided regions, calculating an occupation rate indicating a proportion of the entire photographed image data;
A deviation amount calculating means for calculating a deviation amount indicating a deviation in gradation distribution of the photographed image data;
To specify the shooting condition by multiplying the occupation ratio of each area calculated by the occupancy ratio calculating means and the deviation amount calculated by the deviation amount calculating means by a coefficient set in advance according to the shooting conditions. Index calculating means for calculating the index of
A discriminating means for discriminating a photographing condition of the photographed image data based on the calculated index and a discriminant map previously divided according to the accuracy of the photographing condition;
An adjustment method determining means for determining a method of gradation adjustment for the captured image data according to the determined imaging condition;
Gradation conversion means for performing gradation conversion processing on the photographed image data using the determined gradation adjustment method.

The invention according to claim 50 is an imaging means for photographing a subject and acquiring photographed image data;
Occupancy rate calculating means for dividing the photographed image data into regions composed of combinations of predetermined brightness and hue, and for each of the divided regions, calculating an occupation rate indicating a proportion of the entire photographed image data;
A deviation amount calculating means for calculating a deviation amount indicating a deviation in gradation distribution of the photographed image data;
To specify the shooting condition by multiplying the occupation ratio of each area calculated by the occupancy ratio calculating means and the deviation amount calculated by the deviation amount calculating means by a coefficient set in advance according to the shooting conditions. Index calculating means for calculating the index of
A discriminating means for discriminating a photographing condition of the photographed image data based on the calculated index and a discriminant map previously divided according to the accuracy of the photographing condition;
An adjustment method determining means for determining a method of gradation adjustment for the captured image data according to the determined imaging condition;
Adjustment amount determining means for determining a gradation adjustment amount for the captured image data based on the calculated index;
Gradation conversion means for performing gradation conversion processing of the gradation adjustment amount determined by the adjustment amount determination means on the captured image data using the gradation adjustment method determined by the adjustment method determination means; It is characterized by having.

The invention according to claim 51, the imaging means for capturing the captured image data by capturing the subject,
Dividing the photographed image data into predetermined areas composed of a combination of the distance from the outer edge of the screen of the photographed image data and the brightness, and an occupancy ratio indicating a ratio of the entire photographed image data for each of the divided areas Occupancy ratio calculating means for calculating
A deviation amount calculating means for calculating a deviation amount indicating a deviation in gradation distribution of the photographed image data;
To specify the shooting condition by multiplying the occupation ratio of each area calculated by the occupancy ratio calculating means and the deviation amount calculated by the deviation amount calculating means by a coefficient set in advance according to the shooting conditions. Index calculating means for calculating the index of
A discriminating means for discriminating a photographing condition of the photographed image data based on the calculated index and a discriminant map previously divided according to the accuracy of the photographing condition;
An adjustment method determining means for determining a method of gradation adjustment for the captured image data according to the determined imaging condition;
Gradation conversion means for performing gradation conversion processing on the photographed image data using the determined gradation adjustment method.

The invention according to claim 52 is an imaging means for photographing a subject and obtaining photographed image data;
Dividing the photographed image data into predetermined areas composed of a combination of the distance from the outer edge of the screen of the photographed image data and the brightness, and an occupancy ratio indicating a ratio of the entire photographed image data for each of the divided areas Occupancy ratio calculating means for calculating
A deviation amount calculating means for calculating a deviation amount indicating a deviation in gradation distribution of the photographed image data;
To specify the shooting condition by multiplying the occupation ratio of each area calculated by the occupancy ratio calculating means and the deviation amount calculated by the deviation amount calculating means by a coefficient set in advance according to the shooting conditions. Index calculating means for calculating the index of
A discriminating means for discriminating a photographing condition of the photographed image data based on the calculated index and a discriminant map previously divided according to the accuracy of the photographing condition;
An adjustment method determining means for determining a method of gradation adjustment for the captured image data according to the determined imaging condition;
Adjustment amount determining means for determining a gradation adjustment amount for the captured image data based on the calculated index;
Gradation conversion means for performing gradation conversion processing of the gradation adjustment amount determined by the adjustment amount determination means on the captured image data using the gradation adjustment method determined by the adjustment method determination means; It is characterized by having.

The invention according to claim 53 is an imaging means for capturing a captured image data by capturing a subject;
The photographed image data is divided into regions composed of a combination of predetermined brightness and hue, and a first occupancy ratio indicating the proportion of the whole photographed image data is calculated for each of the divided regions, and the photographed image A second occupancy ratio that divides the data into a predetermined area composed of a combination of the distance from the outer edge of the screen of the captured image data and the brightness and occupies the entire captured image data for each of the divided areas Occupancy ratio calculating means for calculating
A deviation amount calculating means for calculating a deviation amount indicating a deviation in gradation distribution of the photographed image data;
By multiplying the first occupancy ratio and the second occupancy ratio calculated by the occupancy ratio calculating means and the deviation amount calculated by the deviation amount calculating means by a coefficient set in advance according to the photographing condition. , An index calculating means for calculating an index for specifying the shooting conditions;
A discriminating means for discriminating a photographing condition of the photographed image data based on the calculated index and a discriminant map previously divided according to the accuracy of the photographing condition;
An adjustment method determining means for determining a method of gradation adjustment for the captured image data according to the determined imaging condition;
Gradation conversion means for performing gradation conversion processing on the photographed image data using the determined gradation adjustment method.

The invention according to claim 54 is an imaging means for capturing a captured image data by capturing a subject;
The photographed image data is divided into regions composed of a combination of predetermined brightness and hue, and a first occupancy ratio indicating the proportion of the whole photographed image data is calculated for each of the divided regions, and the photographed image A second occupancy ratio that divides the data into a predetermined area composed of a combination of the distance from the outer edge of the screen of the captured image data and the brightness and occupies the entire captured image data for each of the divided areas Occupancy ratio calculating means for calculating
A deviation amount calculating means for calculating a deviation amount indicating a deviation in gradation distribution of the photographed image data;
By multiplying the first occupancy ratio and the second occupancy ratio calculated by the occupancy ratio calculating means and the deviation amount calculated by the deviation amount calculating means by a coefficient set in advance according to the photographing condition. , An index calculating means for calculating an index for specifying the shooting conditions;
A discriminating means for discriminating a photographing condition of the photographed image data based on the calculated index and a discriminant map previously divided according to the accuracy of the photographing condition;
An adjustment method determining means for determining a method of gradation adjustment for the captured image data according to the determined imaging condition;
Adjustment amount determining means for determining a gradation adjustment amount for the captured image data based on the calculated index;
Gradation conversion means for performing gradation conversion processing of the gradation adjustment amount determined by the adjustment amount determination means on the captured image data using the gradation adjustment method determined by the adjustment method determination means; It is characterized by having.

According to a 55th aspect of the present invention, in the imaging device according to the 51st or 52nd aspect, a two-dimensional histogram is created by calculating a cumulative number of pixels for each distance and brightness from the outer edge of the screen of the captured image data. With means,
The occupancy rate calculation means calculates the occupancy rate based on the created two-dimensional histogram.

According to a 56th aspect of the present invention, in the imaging device according to the 53rd or 54th aspect, a two-dimensional histogram is created by calculating the cumulative number of pixels for each distance and brightness from the outer edge of the screen of the captured image data. With means,
The occupancy rate calculation means calculates the second occupancy rate based on the created two-dimensional histogram.

The invention according to claim 57 is the imaging device according to claim 49 or 50, further comprising means for creating a two-dimensional histogram by calculating the cumulative number of pixels for each predetermined hue and brightness of the photographed image data. ,
The occupancy rate calculation means calculates the occupancy rate based on the created two-dimensional histogram.

The invention according to claim 58 is the imaging device according to claim 53 or 54, further comprising means for creating a two-dimensional histogram by calculating the cumulative number of pixels for each predetermined hue and brightness of the photographed image data. ,
The occupancy rate calculation means calculates the first occupancy rate based on the created two-dimensional histogram.

  According to a 59th aspect of the present invention, in the imaging apparatus according to any one of the 49th, 50th, 53rd, 54th, and 56th to 58th aspects, the index calculating unit includes a skin color hue region having a predetermined high brightness, A different sign coefficient is used in a hue area other than the high brightness skin color hue area.

  The invention according to claim 60 is the imaging device according to any one of claims 49, 50, 53, 54, 56 to 59, wherein the index calculating means includes an intermediate brightness area of a flesh-color hue area, and It is characterized in that coefficients having different signs are used in lightness regions other than the intermediate lightness region.

  The invention according to claim 61 is the imaging apparatus according to claim 59, characterized in that the brightness area of the hue area other than the high brightness skin color hue area is a predetermined high brightness area.

  According to a 62nd aspect of the present invention, in the imaging device according to the 60th aspect, the brightness area other than the intermediate brightness area is a brightness area within a flesh-color hue area.

  According to a 63rd aspect of the present invention, in the imaging device according to the 59th or 61th aspect, the high brightness skin color hue region includes a region in the range of 170 to 224 in terms of the brightness value of the HSV color system. It is characterized by.

  According to a 64th aspect of the present invention, in the imaging device according to the 60th or 62th aspect of the present invention, the intermediate lightness region includes a region having a lightness value in the HSV color system of 85 to 169. Yes.

  According to a 65th aspect of the present invention, in the imaging device according to any one of the 59th, 61th, and 63th aspects, a hue region other than the high brightness skin color hue region includes a blue hue region and a green hue region. It is characterized in that at least one of them is included.

  According to a 66th aspect of the present invention, in the imaging device according to any one of the 60th, 62th, and 64th aspects, the brightness area other than the intermediate brightness area is a shadow area.

  According to a 67th aspect of the present invention, in the imaging device according to the 65th aspect, a hue value of the blue hue region is in a range of 161 to 250 as a hue value of an HSV color system, and the hue value of the green hue region is The hue value is a hue value in the HSV color system and is characterized by being in the range of 40 to 160.

  According to a 68th aspect of the present invention, in the imaging apparatus according to the 66th aspect, the lightness value of the shadow region is in the range of 26 to 84 as the lightness value of the HSV color system.

  According to a 69th aspect of the present invention, in the imaging apparatus according to any one of the 59th to 68th aspects, the hue value of the flesh color hue region is a hue value of HSV color system 0 to 39 and 330 to 359. It is characterized by being in the range of.

  According to a 70th aspect of the present invention, in the imaging device according to any one of the 59th to 69th aspects, the skin color hue region is divided into two regions by a predetermined conditional expression based on brightness and saturation. It is characterized by that.

  The invention according to claim 71 is the imaging apparatus according to any one of claims 49 to 70, wherein the deviation amount includes a deviation amount of brightness of photographed image data, and a screen center portion of the photographed image data. At least one of an average value of brightness and a difference value of brightness calculated under different conditions.

The invention according to claim 72 is the imaging device according to any one of claims 49 to 71, wherein the photographing condition indicates a light source condition and an exposure condition at the time of photographing,
The light source condition includes a flash photographing state, and the exposure condition includes an under photographing state derived from a shutter speed and an aperture value at the time of photographing.

The invention according to claim 73 provides a computer for executing image processing,
Occupancy rate calculation function for dividing the captured image data into regions composed of combinations of predetermined brightness and hue, and for each of the divided regions, calculating an occupation rate indicating the proportion of the entire captured image data;
A deviation amount calculation function for calculating a deviation amount indicating a deviation in gradation distribution of the captured image data;
To specify the shooting condition by multiplying the occupation ratio of each area calculated by the occupation ratio calculation function and the deviation amount calculated by the deviation amount calculation function by a coefficient set in advance according to the imaging condition. An index calculation function to calculate
A discriminating function for discriminating the photographing condition of the photographed image data based on the calculated index and a discriminant map preliminarily divided according to the accuracy of the photographing condition;
An adjustment method determining function for determining a method of gradation adjustment for the captured image data according to the determined shooting condition;
An image processing program for realizing a gradation conversion function for performing gradation conversion processing on the photographed image data using the determined gradation adjustment method.

According to a 74th aspect of the present invention, there is provided a computer for executing image processing,
Occupancy rate calculation function for dividing the captured image data into regions composed of combinations of predetermined brightness and hue, and for each of the divided regions, calculating an occupation rate indicating the proportion of the entire captured image data;
A deviation amount calculation function for calculating a deviation amount indicating a deviation in gradation distribution of the captured image data;
To specify the shooting condition by multiplying the occupation ratio of each area calculated by the occupation ratio calculation function and the deviation amount calculated by the deviation amount calculation function by a coefficient set in advance according to the imaging condition. An index calculation function to calculate
A discriminating function for discriminating the photographing condition of the photographed image data based on the calculated index and a discriminant map preliminarily divided according to the accuracy of the photographing condition;
An adjustment method determining function for determining a method of gradation adjustment for the captured image data according to the determined shooting condition;
An adjustment amount determination function for determining a gradation adjustment amount for the captured image data based on the calculated index;
A gradation conversion function for performing gradation conversion processing of the gradation adjustment amount determined by the adjustment amount determination function on the captured image data using the gradation adjustment method determined by the adjustment method determination function; Is an image processing program for realizing the above.

The invention according to claim 75 provides a computer for executing image processing,
The photographed image data is divided into predetermined areas composed of a combination of the distance from the outer edge of the screen of the photographed image data and the brightness, and an occupancy ratio indicating the ratio of the entire photographed image data for each of the divided areas. Occupancy rate calculation function to calculate,
A deviation amount calculation function for calculating a deviation amount indicating a deviation in gradation distribution of the captured image data;
To specify the shooting condition by multiplying the occupation ratio of each area calculated by the occupation ratio calculation function and the deviation amount calculated by the deviation amount calculation function by a coefficient set in advance according to the imaging condition. An index calculation function to calculate
A discriminating function for discriminating the photographing condition of the photographed image data based on the calculated index and a discriminant map preliminarily divided according to the accuracy of the photographing condition;
An adjustment method determining function for determining a method of gradation adjustment for the captured image data according to the determined shooting condition;
An image processing program for realizing a gradation conversion function for performing gradation conversion processing on the photographed image data using the determined gradation adjustment method.

The invention according to claim 76 provides a computer for executing image processing,
The photographed image data is divided into predetermined areas composed of a combination of the distance from the outer edge of the screen of the photographed image data and the brightness, and an occupancy ratio indicating the ratio of the entire photographed image data for each of the divided areas. Occupancy rate calculation function to calculate,
A deviation amount calculation function for calculating a deviation amount indicating a deviation in gradation distribution of the captured image data;
To specify the shooting condition by multiplying the occupation ratio of each area calculated by the occupation ratio calculation function and the deviation amount calculated by the deviation amount calculation function by a coefficient set in advance according to the imaging condition. An index calculation function to calculate
A discriminating function for discriminating the photographing condition of the photographed image data based on the calculated index and a discriminant map preliminarily divided according to the accuracy of the photographing condition;
An adjustment method determining function for determining a method of gradation adjustment for the captured image data according to the determined shooting condition;
An adjustment amount determination function for determining a gradation adjustment amount for the captured image data based on the calculated index;
A gradation conversion function for performing gradation conversion processing of the gradation adjustment amount determined by the adjustment amount determination function on the captured image data using the gradation adjustment method determined by the adjustment method determination function; Is an image processing program for realizing the above.

The invention according to claim 77 provides a computer for executing image processing,
The photographed image data is divided into regions composed of a combination of predetermined brightness and hue, and a first occupancy ratio indicating the proportion of the whole photographed image data is calculated for each of the divided regions, and the photographed image data Is divided into predetermined areas composed of a combination of the distance from the outer edge of the screen of the photographed image data and the brightness, and a second occupancy ratio indicating the proportion of the whole photographed image data is determined for each of the divided areas. Occupancy rate calculation function to calculate,
A deviation amount calculation function for calculating a deviation amount indicating a deviation in gradation distribution of the captured image data;
By multiplying the first occupancy ratio and the second occupancy ratio calculated by the occupancy ratio calculation function and the deviation amount calculated by the deviation amount calculation function by a coefficient set in advance according to the shooting condition. , An index calculation function for calculating an index for specifying shooting conditions,
A discriminating function for discriminating the photographing condition of the photographed image data based on the calculated index and a discriminant map preliminarily divided according to the accuracy of the photographing condition;
An adjustment method determining function for determining a method of gradation adjustment for the captured image data according to the determined shooting condition;
An image processing program for realizing a gradation conversion function for performing gradation conversion processing on the photographed image data using the determined gradation adjustment method.

According to a 78th aspect of the present invention, there is provided a computer for executing image processing.
The photographed image data is divided into regions composed of a combination of predetermined brightness and hue, and a first occupancy ratio indicating the proportion of the whole photographed image data is calculated for each of the divided regions, and the photographed image data Is divided into predetermined areas composed of a combination of the distance from the outer edge of the screen of the photographed image data and the brightness, and a second occupancy ratio indicating the proportion of the whole photographed image data is determined for each of the divided areas. Occupancy rate calculation function to calculate,
A deviation amount calculation function for calculating a deviation amount indicating a deviation in gradation distribution of the captured image data;
By multiplying the first occupancy ratio and the second occupancy ratio calculated by the occupancy ratio calculation function and the deviation amount calculated by the deviation amount calculation function by a coefficient set in advance according to the shooting condition. , An index calculation function for calculating an index for specifying shooting conditions,
A discriminating function for discriminating the photographing condition of the photographed image data based on the calculated index and a discriminant map preliminarily divided according to the accuracy of the photographing condition;
An adjustment method determining function for determining a method of gradation adjustment for the captured image data according to the determined shooting condition;
An adjustment amount determination function for determining a gradation adjustment amount for the captured image data based on the calculated index;
A gradation conversion function for performing gradation conversion processing of the gradation adjustment amount determined by the adjustment amount determination function on the captured image data using the gradation adjustment method determined by the adjustment method determination function; Is an image processing program for realizing the above.

The invention according to claim 79 is the image processing program according to claim 75 or 76, wherein a two-dimensional histogram is created by calculating the cumulative number of pixels for each distance and brightness from the outer edge of the screen of the photographed image data. Realize the function to
When the occupancy rate calculation function is realized, the occupancy rate is calculated based on the created two-dimensional histogram.

The invention according to claim 80 is the image processing program according to claim 77 or 78, wherein a two-dimensional histogram is created by calculating the cumulative number of pixels for each distance and brightness from the outer edge of the screen of the photographed image data. Realize the function to
When the occupation rate calculation function is realized, the second occupation rate is calculated based on the created two-dimensional histogram.

The invention according to claim 81 is the image processing program according to claim 73 or 74, wherein the two-dimensional histogram is created by calculating the cumulative number of pixels for each predetermined hue and brightness of the photographed image data. Realized,
When the occupancy rate calculation function is realized, the occupancy rate is calculated based on the created two-dimensional histogram.

The invention according to claim 82 is the image processing program according to claim 77 or 78, wherein the two-dimensional histogram is created by calculating the cumulative number of pixels for each predetermined hue and lightness of the photographed image data. Realized,
When realizing the occupancy rate calculating function, the first occupancy rate is calculated based on the created two-dimensional histogram.

  According to an 83rd aspect of the present invention, in the image processing program according to any one of the 73rd, 74th, 77th, 78th and 80th to 82nd aspects, when the index calculation function is realized, a predetermined high brightness is obtained. It is characterized in that coefficients of different signs are used in the flesh color hue area and the hue area other than the high brightness flesh color hue area.

  The invention according to an 84th aspect is the image processing program according to any one of the 73rd, 74th, 77th, 78th and 80th to 83rd aspects, wherein when the index calculation function is realized, It is characterized in that coefficients of different signs are used in the brightness area and brightness areas other than the intermediate brightness area.

  According to an 85th aspect of the present invention, in the image processing program according to the 83rd aspect, the brightness area of the hue area other than the high brightness skin color hue area is a predetermined high brightness area.

  According to an 86th aspect of the present invention, in the image processing program according to the 84th aspect, the lightness area other than the intermediate lightness area is a lightness area in a flesh-color hue area.

  According to an 87th aspect of the present invention, in the image processing program according to the 83rd or 85th aspect, the high-brightness skin color hue region includes a region in the range of 170 to 224 in terms of the lightness value of the HSV color system. It is characterized by that.

  According to an 88th aspect of the present invention, in the image processing program according to the 84th or 86th aspect, the intermediate lightness area includes an area in the range of 85 to 169 as a lightness value of the HSV color system. It is said.

  The invention according to claim 89 is the image processing program according to any one of claims 83, 85, and 87, wherein the hue area other than the high brightness skin color hue area includes a blue hue area and a green hue area. It is characterized by including at least one of these.

  The invention described in item 90 is the image processing program according to any one of items 84, 86, 88, wherein the brightness area other than the intermediate brightness area is a shadow area.

  The invention according to claim 91 is the image processing program according to claim 89, wherein a hue value of the blue hue region is in a range of 161 to 250 as a hue value of the HSV color system, and the green hue region The hue value is a hue value of the HSV color system and is in the range of 40 to 160.

  The invention according to claim 92 is the image processing program according to claim 90, characterized in that the brightness value of the shadow area is in the range of 26 to 84 in terms of the brightness value of the HSV color system.

  The invention according to claim 93 is the image processing program according to any one of claims 83 to 92, wherein the hue value of the flesh color hue region is a hue value of HSV color system 0 to 39 and 330 to It is characterized by being in the range of 359.

  The invention according to claim 94 is the image processing program according to any one of claims 83 to 93, wherein the skin color hue region is divided into two regions by a predetermined conditional expression based on lightness and saturation. It is characterized by that.

  The invention according to claim 95 is the image processing program according to any one of claims 73 to 94, wherein the deviation amount includes a brightness deviation amount of the photographed image data, a screen center of the photographed image data. It is characterized in that at least one of an average brightness value and a brightness difference value calculated under different conditions is included.

The invention according to claim 96 is the image processing program according to any one of claims 73 to 95, wherein the photographing condition indicates a light source condition and an exposure condition at the time of photographing,
The light source condition includes a flash photographing state, and the exposure condition includes an under photographing state derived from a shutter speed and an aperture value at the time of photographing.

  According to the present invention, an index that quantitatively indicates the shooting condition of the captured image data is calculated, the shooting condition is determined based on the calculated index, and the gradation adjustment for the captured image data is performed according to the determination result. By determining the method, it is possible to appropriately correct the brightness of the subject. In particular, by determining the shooting conditions based on the determination map divided in advance according to the accuracy of the shooting conditions, the reliability of the determination result becomes high, and appropriate gradation conversion according to the shooting conditions can be performed. It becomes possible.

  Further, it is possible to appropriately correct the brightness of the subject by calculating an index quantitatively indicating the shooting condition of the captured image data and determining the gradation adjustment amount of the captured image data based on the calculated index. It becomes possible.

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

  FIG. 1 is a perspective view showing an external configuration of an image processing apparatus 1 according to an embodiment of the present invention. As shown in FIG. 1, the image processing apparatus 1 is provided with a magazine loading unit 3 for loading a photosensitive material on one side of a housing 2. Inside the housing 2 are provided an exposure processing unit 4 for exposing the photosensitive material, and a print creating unit 5 for developing and drying the exposed photosensitive material to create a print. On the other side surface of the housing 2, a tray 6 for discharging the print created by the print creation unit 5 is provided.

  In addition, a CRT (Cathode Ray Tube) 8 serving as a display device, a film scanner unit 9 serving as a device for reading a transparent document, a reflective document input device 10, and an operation unit 11 are provided on the upper portion of the housing 2. The CRT 8 constitutes display means for displaying an image of image information to be printed on the screen. Further, the housing 2 includes an image reading unit 14 that can read image information recorded on various digital recording media, and an image writing unit 15 that can write (output) image signals to various digital recording media. Yes. In addition, a control unit 7 that centrally controls these units is provided inside the housing 2.

  The image reading unit 14 includes a PC card adapter 14a and a floppy (registered trademark) disk adapter 14b, and a PC card 13a and a floppy (registered trademark) disk 13b can be inserted therein. The PC card 13a has, for example, a memory in which a plurality of frame image data captured by a digital camera is recorded. For example, a plurality of frame image data captured by a digital camera is recorded on the floppy (registered trademark) disk 13b. Examples of the recording medium on which frame image data is recorded other than the PC card 13a and the floppy (registered trademark) disk 13b include a multimedia card (registered trademark), a memory stick (registered trademark), MD data, and a CD-ROM. .

  The image writing unit 15 includes a floppy (registered trademark) disk adapter 15a, an MO adapter 15b, and an optical disk adapter 15c, and a floppy (registered trademark) disk 16a, MO 16b, and an optical disk 16c can be inserted into the image writing unit 15, respectively. ing. Examples of the optical disc 16c include a CD-R and a DVD-R.

  In FIG. 1, the operation unit 11, the CRT 8, the film scanner unit 9, the reflection original input device 10, and the image reading unit 14 are integrally provided in the housing 2. One or more may be provided separately.

  Further, in the image processing apparatus 1 shown in FIG. 1, there is exemplified an apparatus that creates a print by exposing to a photosensitive material and developing it, but the print creation system is not limited to this, for example, an inkjet system, an electronic system, etc. A method such as a photographic method, a thermal method, or a sublimation method may be used.

<Main part configuration of image processing apparatus 1>
FIG. 2 shows a main part configuration of the image processing apparatus 1. As shown in FIG. 2, the image processing apparatus 1 includes a control unit 7, an exposure processing unit 4, a print generation unit 5, a film scanner unit 9, a reflective original input device 10, an image reading unit 14, a communication means (input) 32, The image writing unit 15, the data storage unit 71, the template storage unit 72, the operation unit 11, the CRT 8, and the communication unit (output) 33 are configured.

  The control unit 7 is configured by a microcomputer, and cooperates with various control programs stored in a storage unit (not shown) such as a ROM (Read Only Memory) and a CPU (Central Processing Unit) (not shown). The operation of each unit constituting the image processing apparatus 1 is controlled.

  The control unit 7 includes an image processing unit 70 according to the image processing apparatus of the present invention, and is read from the film scanner unit 9 or the reflective original input device 10 based on an input signal (command information) from the operation unit 11. Image processing is performed on the image signal, the image signal read from the image reading unit 14, and the image signal input from the external device via the communication unit 32 to form exposure image information, and the exposure processing unit 4 Output. Further, the image processing unit 70 performs a conversion process corresponding to the output form on the image signal subjected to the image processing, and outputs the image signal. Output destinations of the image processing unit 70 include the CRT 8, the image writing unit 15, the communication means (output) 33, and the like.

  The exposure processing unit 4 exposes an image to the photosensitive material and outputs the photosensitive material to the print creating unit 5. The print creating unit 5 develops and exposes the exposed photosensitive material to create prints P1, P2, and P3. The print P1 is a service size, high-definition size, panoramic size print, the print P2 is an A4 size print, and the print P3 is a business card size print.

  The film scanner unit 9 reads a frame image recorded on a transparent original such as a developed negative film N or a reversal film imaged by an analog camera, and acquires a digital image signal of the frame image. The reflective original input device 10 reads an image on a print P (photo print, document, various printed materials) by a flat bed scanner, and acquires a digital image signal.

  The image reading unit 14 reads frame image information recorded on the PC card 13 a or the floppy (registered trademark) disk 13 b and transfers the frame image information to the control unit 7. The image reading unit 14 includes, as the image transfer means 30, a PC card adapter 14a, a floppy (registered trademark) disk adapter 14b, and the like. The image reading unit 14 reads frame image information recorded on the PC card 13a inserted into the PC card adapter 14a or the floppy (registered trademark) disk 13b inserted into the floppy (registered trademark) disk adapter 14b. Transfer to the control unit 7. For example, a PC card reader or a PC card slot is used as the PC card adapter 14a.

  The communication means (input) 32 receives an image signal representing a captured image and a print command signal from another computer in the facility where the image processing apparatus 1 is installed, or a remote computer via the Internet or the like.

  The image writing unit 15 includes, as the image conveying unit 31, a floppy (registered trademark) disk adapter 15a, an MO adapter 15b, and an optical disk adapter 15c. In accordance with a write signal input from the control unit 7, the image writing unit 15 includes a floppy (registered trademark) disk 16a inserted into the floppy (registered trademark) disk adapter 15a, an MO 16b inserted into the MO adapter 15b, The image signal generated by the image processing method according to the present invention is written to the optical disk 16c inserted into the optical disk adapter 15c.

  The data storage unit 71 stores and sequentially stores image information and order information corresponding to the image information (information on how many prints are to be created from images of which frames, print size information, and the like).

  The template storage means 72 stores at least one template data for setting a synthesis area and a background image, an illustration image, and the like, which are sample image data corresponding to the sample identification information D1, D2, and D3. A predetermined template is selected from a plurality of templates that are set by the operation of the operator and stored in advance in the template storage means 72, and the frame image information is synthesized by the selected template and designated sample identification information D1, D2, D3 The sample image data selected on the basis of the image data and the image data and / or character data based on the order are combined to create a print based on the specified sample. The synthesis using this template is performed by a well-known chroma key method.

  Note that sample identification information D1, D2, and D3 for specifying a print sample is configured to be input from the operation unit 211. These sample identification information is recorded on a print sample or an order sheet. Therefore, it can be read by reading means such as OCR. Or it can also input by an operator's keyboard operation.

  In this way, sample image data is recorded corresponding to the sample identification information D1 for designating the print sample, the sample identification information D1 for designating the print sample is input, and based on the input sample identification information D1. Select the sample image data, synthesize the selected sample image data with the image data and / or text data based on the order, and create a print based on the specified sample. Can actually place a print order and meet the diverse requirements of a wide range of users.

  Also, the first sample identification information D2 designating the first sample and the image data of the first sample are stored, and the second sample identification information D3 designating the second sample and the second sample The image data is stored, the sample image data selected based on the designated first and second sample identification information D2 and D3, and the image data and / or character data based on the order are synthesized, and according to the designation In order to create a print based on a sample, it is possible to synthesize a wider variety of images, and it is possible to create a print that meets a wider variety of user requirements.

  The operation unit 11 includes information input means 12. The information input unit 12 is configured by a touch panel, for example, and outputs a pressing signal of the information input unit 12 to the control unit 7 as an input signal. Note that the operation unit 11 may be configured to include a keyboard, a mouse, and the like. The CRT 8 displays image information and the like according to a display control signal input from the control unit 7.

  The communication means (output) 33 sends an image signal representing a photographed image after image processing of the present invention and order information attached thereto to other computers in the facility where the image processing apparatus 1 is installed, the Internet Etc. to a distant computer via

  As shown in FIG. 2, the image processing apparatus 1 displays an image input unit that captures image information obtained by dividing and metering images of various digital media and an image original, an image processing unit, and a processed image. Print output, image output means for writing to an image recording medium, and means for transmitting image data and accompanying order information to another computer in the facility or a distant computer via the Internet via a communication line, Prepare.

<Internal Configuration of Image Processing Unit 70>
FIG. 3 shows an internal configuration of the image processing unit 70. As shown in FIG. 3, the image processing unit 70 includes an image adjustment processing unit 701, a film scan data processing unit 702, a reflected original scan data processing unit 703, an image data format decoding processing unit 704, a template processing unit 705, and CRT specific processing. 706, printer specific processing unit A707, printer specific processing unit B708, and image data format creation processing unit 709.

  The film scan data processing unit 702 performs a calibration operation specific to the film scanner unit 9, negative / positive reversal (in the case of a negative document), dust scratch removal, contrast adjustment, granular noise removal, and sharpness for the image data input from the film scanner unit 9. Processing such as conversion enhancement is performed, and processed image data is output to the image adjustment processing unit 701. In addition, the film size, the negative / positive type, information relating to the main subject optically or magnetically recorded on the film, information relating to the photographing conditions (for example, information content described in APS), and the like are also output to the image adjustment processing unit 701. .

  The reflection original scan data processing unit 703 performs a calibration operation unique to the reflection original input device 10, negative / positive reversal (in the case of a negative original), dust flaw removal, contrast adjustment, and noise removal on the image data input from the reflection original input device 10. Then, processing such as sharpening enhancement is performed, and processed image data is output to the image adjustment processing unit 701.

  The image data format decoding processing unit 704 restores the compression code, if necessary, according to the data format of the image data input from the image transfer means 30 and / or the communication means (input) 32, and the color data. Are converted into a data format suitable for computation in the image processing unit 70 and output to the image adjustment processing unit 701. Further, when the size of the output image is specified from any of the operation unit 11, the communication unit (input) 32, and the image transfer unit 30, the image data format decoding processing unit 704 detects the specified information, The image is output to the image adjustment processing unit 701. Information about the size of the output image designated by the image transfer means 30 is embedded in the header information and tag information of the image data acquired by the image transfer means 30.

  The image adjustment processing unit 701 receives from the film scanner unit 9, the reflection original input device 10, the image transfer unit 30, the communication unit (input) 32, and the template processing unit 705 based on the command from the operation unit 11 or the control unit 7. The image data described below is subjected to image processing (see FIGS. 6, 7, 13, and 17) to generate digital image data for image formation optimized for viewing on the output medium, and CRT The data is output to the specific processing unit 706, the printer specific processing unit A 707, the printer specific processing unit B 708, the image data format creation processing unit 709, and the data storage unit 71.

  In the optimization process, for example, when it is assumed that the image is displayed on a CRT display monitor compliant with the sRGB standard, the optimal color reproduction is performed within the sRGB standard color gamut. If output to silver salt photographic paper is assumed, processing is performed so that optimum color reproduction is obtained within the color gamut of silver salt photographic paper. In addition to the compression of the color gamut, gradation processing from 16 bits to 8 bits, reduction of the number of output pixels, processing corresponding to output characteristics (LUT) of the output device, and the like are also included. Furthermore, it goes without saying that tone compression processing such as noise suppression, sharpening, gray balance adjustment, saturation adjustment, or dodging processing is performed.

  As shown in FIG. 3, the image adjustment processing unit 701 determines a gradation adjustment condition (gradation adjustment method, gradation adjustment amount) by determining a photographing condition of photographed image data, and the determination. The gradation conversion unit 711 performs gradation conversion processing according to the adjusted gradation adjustment conditions.

In the present embodiment, shooting conditions are classified into light source conditions and exposure conditions.
The light source condition is derived from the light source at the time of photographing, the positional relationship between the main subject (mainly a person) and the photographer. In a broad sense, the type of light source (sunlight, strobe light, tungsten illumination and fluorescent lamp) is also included. Backlit scenes occur when the sun is located in the background of the main subject. Further, a strobe (close-up shooting) scene is generated when strobe light is intensely applied to a main subject. Both scenes have the same shooting brightness (ratio of light and darkness), and the relationship between the foreground and background brightness of the main subject is merely reversed.

  On the other hand, the exposure condition is derived from the settings of the camera shutter speed, aperture value, etc., and the underexposure state is referred to as under, the proper exposure state is referred to as normal, and the overexposure state is referred to as over. In a broad sense, so-called “white jump” and “shadow collapse” are also included. Under all light source conditions, under or over exposure conditions can be set. In particular, in a DSC (digital still camera) with a narrow dynamic range, even if the automatic exposure adjustment function is used, the frequency of underexposure exposure conditions is high due to setting conditions intended to suppress overexposure. .

  FIG. 4A shows an internal configuration of the scene determination unit 710. As shown in FIG. 4A, the scene determination unit 710 includes a ratio calculation unit 712, a bias calculation unit 722, an index calculation unit 713, and an image processing condition calculation unit 714. As shown in FIG. 4B, the ratio calculation unit 712 includes a color system conversion unit 715, a histogram creation unit 716, and an occupation rate calculation unit 717.

  The color system conversion unit 715 converts RGB (Red, Green, Blue) values of the captured image data into the HSV color system. The HSV color system is a representation of image data in terms of three elements: Hue, Saturation, and Lightness (Value or Brightness), and is based on the color system proposed by Munsell. It has been devised.

  In the claims and this embodiment, “brightness” means “brightness” generally used unless otherwise specified. 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. The captured image data in the present embodiment is assumed to be image data having a person as a main subject.

  The histogram creation unit 716 creates a two-dimensional histogram by dividing the photographed image data into regions composed of a predetermined combination of hue and brightness, and calculating the cumulative number of pixels for each of the divided regions. In addition, the histogram creation unit 716 divides the captured image data into predetermined regions composed of combinations of the distance from the outer edge of the screen of the captured image data and the brightness, and calculates the cumulative number of pixels for each of the divided regions. To create a two-dimensional histogram. Note that the captured image data is divided into regions including combinations of the distance from the outer edge of the screen of the captured image data, brightness, and hue, and a cumulative pixel count is calculated for each of the divided regions, thereby creating a three-dimensional histogram. You may do it. In the following, it is assumed that a method of creating a two-dimensional histogram is adopted.

  The occupancy calculating unit 717 has a first occupancy indicating the ratio of the cumulative number of pixels calculated by the histogram creation unit 716 to the total number of pixels (the entire captured image data) for each region divided by the combination of brightness and hue. The rate (see Table 1) is calculated. In addition, the occupation ratio calculation unit 717 calculates the total number of pixels (shooted image data) of the cumulative number of pixels calculated by the histogram creation unit 716 for each region divided by the combination of the distance from the outer edge of the screen of the shot image data and the brightness. A second occupancy ratio (see Table 4) indicating a ratio of the total) is calculated.

  The bias calculation unit 722 calculates a bias amount indicating the bias of the gradation distribution of the captured image data. Here, the deviation amount is a standard deviation of luminance values of the captured image data, a luminance difference value, a skin color average luminance value at the center of the screen, an average luminance value at the center of the screen, and a skin color luminance distribution value. The calculation processing of these deviation amounts will be described in detail later with reference to FIG.

  The index calculation unit 713 uses a first coefficient (see, for example, Table 2) set in advance (for example, by discriminant analysis) in accordance with the shooting conditions in the first occupancy calculated for each region in the occupancy calculation unit 717. ) To obtain a sum, thereby calculating an index 1 for specifying the photographing condition. The index 1 indicates characteristics at the time of strobe shooting such as indoor shooting degree, close-up shooting degree, face color high brightness, and the like, and is for separating an image that should be identified as a strobe from other shooting conditions.

  When calculating the index 1, the index calculation unit 713 uses coefficients of different signs for a predetermined high brightness skin color hue area and a hue area other than the high brightness skin color hue area. Here, the predetermined high lightness skin color hue region includes regions 170 to 224 in the lightness value of the HSV color system. Further, the hue area other than the predetermined high brightness skin color hue area includes at least one high brightness area of the blue hue area (hue values 161 to 250) and the green hue area (hue values 40 to 160).

  The index calculation unit 713 also sets a second coefficient (table) set in advance (for example, by discriminant analysis) to the first occupancy calculated for each region in the occupancy calculation unit 717 according to the shooting conditions. The index 2 for specifying the photographing condition is calculated by multiplying (see 3) and taking the sum. The index 2 is a composite indication of characteristics at the time of backlight photographing such as outdoor photographing degree, sky blue high lightness, facial color low lightness, etc., and is for separating an image that should be distinguished from backlighting from other photographing conditions. .

  When calculating the index 2, the index calculation unit 713 uses coefficients of different signs in the intermediate brightness area of the flesh color hue area (hue values 0 to 39, 330 to 359) and the brightness areas other than the intermediate brightness area. . The intermediate lightness area of the flesh color hue area includes lightness values of 85 to 169. The brightness area other than the intermediate brightness area includes, for example, a shadow area (brightness values 26 to 84).

  Further, the index calculation unit 713 uses the third coefficient (table) set in advance (for example, by discriminant analysis) in accordance with the shooting conditions in the second occupancy calculated for each region in the occupancy calculation unit 717. 5) to obtain a sum to calculate an index 3 for specifying the photographing condition. The index 3 indicates the difference in contrast between the center and the outside of the screen of the captured image data between the backlight and the strobe, and quantitatively indicates only the image that should be distinguished from the backlight or the strobe. When calculating the index 3, the index calculation unit 713 uses different values of coefficients according to the distance from the outer edge of the screen of the captured image data.

  In addition, the index calculation unit 713 uses coefficients set in advance (for example, by discriminant analysis) according to shooting conditions for the average brightness value of the skin color area in the center of the screen of the index 1, the index 3, and the captured image data. The index 4 is calculated by multiplying and taking the sum. Further, the index calculation unit 713 multiplies the average luminance value of the skin color area in the index 2, index 3, and center portion of the screen by a coefficient set in advance (for example, by discriminant analysis) according to the shooting condition. The index 5 is calculated by taking In addition, the index calculation unit 713 multiplies the deviation amount calculated by the bias calculation unit 722 by a fourth coefficient (see Table 6) set in advance (for example, by discriminant analysis) according to the shooting conditions. The index 6 is calculated by taking A specific method for calculating the indices 1 to 6 in the index calculating unit 713 will be described in detail in the operation description of the present embodiment described later.

  FIG. 4C shows the internal configuration of the image processing condition calculation unit 714. As shown in FIG. 4C, the image processing condition calculation unit 714 includes a scene determination unit 718, a gradation adjustment method determination unit 719, a gradation adjustment parameter calculation unit 720, and a gradation adjustment amount calculation unit 721. .

  The scene discriminating unit 718 is divided into regions in advance according to the values of the index 4, the index 5 and the index 6 calculated by the index calculating unit 713 and the accuracy of the shooting conditions, and evaluates the reliability of the index (FIG. 19). Based on the reference), the shooting condition of the shot image data is determined.

  A gradation adjustment method determination unit 719 determines a method of gradation adjustment for the captured image data according to the imaging conditions determined by the scene determination unit 718. For example, when the shooting condition is direct light or strobe light, as shown in FIG. 21A, there is a method (tone adjustment method A) for correcting the translation (offset) of the pixel value of the input captured image data. Applied. When the shooting condition is backlit or under, as shown in FIG. 21B, a method (gradation adjustment method B) for applying gamma correction to the pixel value of the input captured image data is applied. Further, when the photographing condition is intermediate between backlight and direct light (low accuracy region (1)), or intermediate between strobe and under light (low accuracy region (2)), as shown in FIG. A method (tone adjustment method C) for applying gamma correction and translation (offset) correction to the pixel value of the input captured image data is applied.

  The tone adjustment parameter calculation unit 720 calculates parameters (key correction values and the like) necessary for tone adjustment based on the values of the index 4, the index 5, and the index 6 calculated by the index calculation unit 713.

  The tone adjustment amount calculation unit 721 calculates (determines) the tone adjustment amount for the captured image data based on the tone adjustment parameter calculated by the tone adjustment parameter calculation unit 720. Specifically, the tone adjustment amount calculation unit 721 selects a tone adjustment parameter from a plurality of tone conversion curves set in advance corresponding to the tone adjustment method determined by the tone adjustment method determination unit 719. A gradation conversion curve corresponding to the gradation adjustment parameter calculated by the calculation unit 720 is selected. Note that the tone conversion curve (tone adjustment amount) may be calculated based on the tone adjustment parameter calculated by the tone adjustment parameter calculation unit 720.

  The method for determining the shooting condition in the scene determination unit 718 and the method for calculating the gradation adjustment parameter in the gradation adjustment parameter calculation unit 720 will be described in detail in the operation description of the present embodiment described later.

  In FIG. 3, the gradation conversion unit 711 performs gradation conversion of the captured image data according to the gradation conversion curve determined by the gradation adjustment amount calculation unit 721.

  The template processing unit 705 reads out predetermined image data (template) from the template storage unit 72 based on a command from the image adjustment processing unit 701, and performs template processing for combining the image data to be processed with the template. The image data after the template processing is output to the image adjustment processing unit 701.

  The CRT specific processing unit 706 performs a process such as changing the number of pixels and color matching on the image data input from the image adjustment processing unit 701 as necessary, and combines the information with information that needs to be displayed, such as control information. Image data is output to the CRT 8.

  The printer-specific processing unit A707 performs printer-specific calibration processing, color matching, pixel number change processing, and the like as necessary, and outputs processed image data to the exposure processing unit 4.

  When an external printer 51 such as a large-format ink jet printer can be connected to the image processing apparatus 1 of the present invention, a printer specific processing unit B708 is provided for each printer apparatus to be connected. The printer-specific processing unit B708 performs printer-specific calibration processing, color matching, pixel number change, and the like, and outputs processed image data to the external printer 51.

  The image data format creation processing unit 709 converts the image data input from the image adjustment processing unit 701 into various general-purpose image formats typified by JPEG, TIFF, Exif, and the like as necessary. The completed image data is output to the image transport unit 31 and the communication means (output) 33.

  Note that the film scan data processing unit 702, the reflection original scan data processing unit 703, the image data format decoding processing unit 704, the image adjustment processing unit 701, the CRT specific processing unit 706, the printer specific processing unit A707, and the printer specific shown in FIG. The divisions of the processing unit B708 and the image data format creation processing unit 709 are provided to assist understanding of the functions of the image processing unit 70, and are not necessarily realized as physically independent devices. Alternatively, it may be realized as a type of software processing performed by a single CPU.

Next, the operation in this embodiment will be described.
First, the flow of processing executed in the image adjustment processing unit 701 will be described with reference to the flowchart of FIG.

  First, the size of the captured image data is reduced (step T1). As a method for reducing the size of the captured image data, a known method (for example, a bilinear method, a bicubic method, a nearest neighbor method, or the like) can be used. The reduction ratio is not particularly limited, but is preferably about 1/2 to 1/10 of the original image from the viewpoint of processing speed and shooting condition determination accuracy.

  Next, DSC white balance adjustment correction processing is performed on the reduced photographed image data (step T2), and an index (index 1) for specifying the photographing condition based on the photographed image data after the correction processing. ˜6) is calculated (step T3). The index calculation process in step T3 will be described in detail later with reference to FIG.

  Next, the gradation that determines the shooting condition of the captured image data based on the index calculated in step T3 and the determination map, and determines the gradation adjustment condition (gradation adjustment method, gradation adjustment amount) for the captured image data Adjustment condition determination processing is performed (step T4). The gradation adjustment condition determination processing in step T4 will be described in detail later with reference to FIG.

  Next, gradation conversion processing is performed on the original photographed image data in accordance with the gradation adjustment conditions determined in step T4 (step T5). Then, a process for adjusting the sharpness is performed on the captured image data after the gradation conversion process (step T6). In step T6, it is preferable to adjust the processing amount according to the photographing conditions and the output print size.

  Next, a process for removing the noise enhanced by the gradation adjustment and the enhancement of sharpness is performed (step T7). Next, color correction processing is performed to convert the color space in accordance with the type of medium that outputs the captured image data (step T8), and the captured image data after image processing is output to the designated medium.

  Next, the index calculation process (step T3 in FIG. 5) executed in the scene determination unit 710 will be described with reference to the flowchart in FIG. In the following index calculation processing, “photographed image data” is image data reduced in step T1 in FIG.

  First, the ratio calculation unit 712 calculates the occupancy ratio (first occupancy ratio, second occupancy ratio) indicating the ratio of each divided area to the entire captured image data, after the captured image data is divided into predetermined image areas. An occupation rate calculation process is performed (step S1). Details of the occupation rate calculation process will be described later with reference to FIGS.

  Next, in the bias calculation unit 722, a bias amount calculation process for calculating a bias amount indicating a bias in the gradation distribution of the captured image data is performed (step S2). The bias amount calculation process in step S2 will be described later in detail with reference to FIG.

  Next, an index for specifying the light source condition is calculated based on the occupation ratio calculated by the ratio calculation unit 712 and a coefficient set in advance according to the imaging condition (step S3). Also, an index for specifying the exposure condition is calculated based on the occupation ratio calculated in the ratio calculation unit 712 and a coefficient set in advance according to the shooting condition (step S4), and this index calculation process ends. To do. The index calculation method in steps S3 and S4 will be described in detail later.

  Next, the first occupancy ratio calculation process executed in the ratio calculation unit 712 will be described in detail with reference to the flowchart of FIG.

  First, the RGB values of the photographed image data are converted into the HSV color system (step S10). FIG. 8 shows an example of a conversion program (HSV conversion program) that obtains a hue value, a saturation value, and a lightness value by converting from RGB to the HSV color system using program code (c language). In the HSV conversion program shown in FIG. 8, the values of the digital image data as input image data are defined as InR, InG, and InB, the calculated hue value is defined as OutH, the scale is defined as 0 to 360, and the saturation The value is OutS, the brightness value is OutV, and the unit is defined as 0 to 255.

  Next, the photographed image data is divided into regions composed of combinations of predetermined brightness and hue, and a two-dimensional histogram is created by calculating the cumulative number of pixels for each divided region (step S11). Hereinafter, the area division of the captured image data will be described in detail.

The lightness value (V) is 0-25 (v1), 26-50 (v2), 51-84 (v3), 85-169 (v4), 170-199 (v5), 200-224 (v6) , 225 to 255 (v7). Hue (H) is a skin hue hue area (H1 and H2) with a hue value of 0 to 39, 330 to 359, a green hue area (H3) with a hue value of 40 to 160, and a blue hue area with a hue value of 161 to 250 It is divided into four areas (H4) and a red hue area (H5). Note that the red hue region (H5) is not used in the following calculation because it is known that the contribution to the determination of the imaging condition is small. The flesh-color hue area is further divided into a flesh-color area (H1) and other areas (H2). Hereinafter, among the flesh color hue regions (H = 0 to 39, 330 to 359), a hue color '(H) that satisfies the following equation (1) is defined as a flesh color region (H1), and a region that does not satisfy the equation (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) = InR x 0.30 + InG x 0.59 + InB x 0.11 (A)
As
Hue '(H) / Luminance (Y) <3.0 × (Saturation (S) / 255) +0.7 (1)
Therefore, the number of divided areas of the captured image data is 4 × 7 = 28. In addition, it is also possible to use the brightness (V) in the formula (1).

When the two-dimensional histogram is created, a first occupancy ratio indicating the ratio of the cumulative number of pixels calculated for each divided region to the total number of pixels (the entire captured image) is calculated (step S12), and the main occupancy ratio calculation is performed. The process ends. Assuming that the first occupancy ratio calculated in the divided area composed of the combination of the lightness area vi and the hue area Hj is Rij, the first occupancy ratio in each divided area is expressed as shown in Table 1.

Next, a method for calculating the index 1 and the index 2 will be described.
Table 2 shows the first coefficient necessary for calculating the index 1 that quantitatively indicates the accuracy of strobe shooting, that is, the brightness state of the face area at the time of strobe shooting, for each divided area. The coefficient of each divided area shown in Table 2 is a weighting coefficient by which the first occupancy ratio Rij of each divided area shown in Table 1 is multiplied, and is set in advance according to the shooting conditions.

  FIG. 9 shows a lightness (v) -hue (H) plane. According to Table 2, a positive (+) coefficient is used for the first occupancy calculated from the region (r1) distributed in the skin color hue region of high brightness in FIG. 9, and blue other than that is blue. A negative (−) coefficient is used for the first occupancy calculated from the hue region (r2). FIG. 11 shows a curve (coefficient curve) in which the first coefficient in the skin color area (H1) and the first coefficient in the other areas (green hue area (H3)) change continuously over the entire brightness. It is shown. According to Table 2 and FIG. 11, in the region of high brightness (V = 170 to 224), the sign of the first coefficient in the skin color region (H1) is positive (+), and other regions (for example, the green hue region) The sign of the first coefficient in (H3)) is negative (-), and it can be seen that the signs of the two are different.

従って、H1〜H4領域の和は、下記の式(2-1)〜式(2-4)のように表される。
H1領域の和＝R11×(-44.0)＋R21×(-16.0)＋（中略）...＋R71×(-11.3) (2-1)
H2領域の和＝R12×0.0＋R22×8.6＋（中略）... ＋R72×(-11.1) (2-2)
H3領域の和＝R13×0.0＋R23×(-6.3)＋（中略）...＋R73×(-10.0) (2-3)
H4領域の和＝R14×0.0＋R24×(-1.8)＋（中略）...＋R74×(-14.6) (2-4) When the first coefficient in the lightness region vi and the hue region Hj is Cij, the sum of the Hk regions for calculating the index 1 is defined as in Expression (2).

Accordingly, the sum of the H1 to H4 regions is expressed by the following formulas (2-1) to (2-4).
H1 area sum = R11 x (-44.0) + R21 x (-16.0) + (omitted) ... + R71 x (-11.3) (2-1)
Sum of H2 area = R12 x 0.0 + R22 x 8.6 + (omitted) ... + R72 x (-11.1) (2-2)
Sum of H3 area = R13 x 0.0 + R23 x (-6.3) + (omitted) ... + R73 x (-10.0) (2-3)
Sum of H4 area = R14 x 0.0 + R24 x (-1.8) + (omitted) ... + R74 x (-14.6) (2-4)

The index 1 is defined as Expression (3) using the sum of the H1 to H4 regions shown in Expressions (2-1) to (2-4).
Index 1 = sum of H1 area + sum of H2 area + sum of H3 area + sum of H4 area + 4.424 (3)

Table 3 shows, for each divided region, the second coefficient necessary for calculating the index 2 that quantitatively indicates the accuracy as backlight photographing, that is, the brightness state of the face region at the time of backlight photographing. The coefficient of each divided area shown in Table 3 is a weighting coefficient by which the first occupancy rate Rij of each divided area shown in Table 1 is multiplied, and is set in advance according to the shooting conditions.

  FIG. 10 shows the lightness (v) -hue (H) plane. According to Table 3, a negative (-) coefficient is used for the occupancy calculated from the region (r4) distributed in the intermediate lightness of the flesh color hue region in FIG. 10, and the low lightness (shadow) region ( A positive (+) coefficient is used for the occupation ratio calculated from r3). FIG. 12 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 3 and FIG. 12, the sign of the second coefficient of the intermediate lightness region of the flesh color hue region having the lightness value of 85 to 169 (v4) is negative (−), and the lightness value is 26 to 84 (v2, It can be seen that the sign of the second coefficient in the low brightness (shadow) region of v3) is positive (+), and the sign of the coefficient in both regions is different.

従って、H1〜H4領域の和は、下記の式(4-1)〜式(4-4)のように表される。
H1領域の和＝R11×(-27.0)＋R21×4.5＋（中略）...＋R71×(-24.0) (4-1)
H2領域の和＝R12×0.0＋R22×4.7＋（中略）... ＋R72×(-8.5) (4-2)
H3領域の和＝R13×0.0＋R23×0.0＋（中略）...＋R73×0.0 (4-3)
H4領域の和＝R14×0.0＋R24×(-5.1)＋（中略）...＋R74×7.2 (4-4) When the second coefficient in the lightness area vi and the hue area Hj is Dij, the sum of the Hk areas for calculating the index 2 is defined as in Expression (4).

Therefore, the sum of the H1 to H4 regions is expressed by the following formulas (4-1) to (4-4).
H1 area sum = R11 x (-27.0) + R21 x 4.5 + (omitted) ... + R71 x (-24.0) (4-1)
Sum of H2 area = R12 x 0.0 + R22 x 4.7 + (omitted) ... + R72 x (-8.5) (4-2)
Sum of H3 area = R13 x 0.0 + R23 x 0.0 + (omitted) ... + R73 x 0.0 (4-3)
H4 area sum = R14 x 0.0 + R24 x (-5.1) + (omitted) ... + R74 x 7.2 (4-4)

The index 2 is defined as in Expression (5) using the sum of the H1 to H4 regions shown in Expressions (4-1) to (4-4).
Index 2 = sum of H1 area + sum of H2 area + sum of H3 area + sum of H4 area + 1.554 (5)
Since the index 1 and the index 2 are calculated based on the brightness and hue distribution amount of the captured image data, the index 1 and the index 2 are effective in determining the imaging condition when the captured image data is a color image.

  Next, the second occupancy rate calculation process executed in the ratio calculation unit 712 to calculate the index 3 will be described in detail with reference to the flowchart of FIG.

  First, the RGB values of the photographed image data are converted into the HSV color system (step S20). Next, the photographed image data is divided into regions each composed of a combination of the distance from the outer edge of the photographed image screen and the brightness, and a two-dimensional histogram is created by calculating the cumulative number of pixels for each divided region (step S21). Hereinafter, the area division of the captured image data will be described in detail.

  14A to 14D show four regions n1 to n4 that are divided according to the distance from the outer edge of the screen of the captured image data. The area n1 shown in FIG. 14A is an outer frame, the area n2 shown in FIG. 14B is an area inside the outer frame, and the area n3 shown in FIG. A region n4 shown in FIG. 14D is an inner region and is a central region of the captured image screen. Further, the lightness is divided into seven regions v1 to v7 as described above. Therefore, when the captured image data is divided into regions composed of combinations of the distance from the outer edge of the captured image screen and the brightness, the number of divided regions is 4 × 7 = 28.

When the two-dimensional histogram is created, a second occupancy ratio indicating the ratio of the cumulative number of pixels calculated for each divided region to the total number of pixels (the entire captured image) is calculated (step S22), and the main occupancy ratio calculation is performed. The process ends. If the second occupancy calculated in the divided area composed of the combination of the brightness area vi and the screen area nj is Qij, the second occupancy in each divided area is expressed as shown in Table 4.

図１５は、画面領域ｎ１〜ｎ４における第３の係数を、明度全体に渡って連続的に変化する曲線（係数曲線）として示したものである。 Next, a method for calculating the index 3 will be described.
Table 5 shows the third coefficient necessary for calculating the index 3 for each divided region. The coefficient of each divided area shown in Table 5 is a weighting coefficient by which the second occupancy rate Qij of each divided area shown in Table 4 is multiplied, and is set in advance according to the shooting conditions.

FIG. 15 shows the third coefficient in the screen areas n1 to n4 as a curve (coefficient curve) that continuously changes over the entire brightness.

従って、n1〜n4領域の和は、下記の式(6-1)〜式(6-4)のように表される。
n1領域の和＝Q11×40.1＋Q21×37.0＋（中略）...＋Q71×22.0 (6-1)
n2領域の和＝Q12×(-14.8)＋Q22×(-10.5)＋（中略）...＋Q72×0.0 (6-2)
n3領域の和＝Q13×24.6＋Q23×12.1＋（中略）...＋Q73×10.1 (6-3)
n4領域の和＝Q14×1.5＋Q24×(-32.9)＋（中略）...＋Q74×(-52.2) (6-4) 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 n4 regions is expressed as the following formulas (6-1) to (6-4).
n1 area sum = Q11 x 40.1 + Q21 x 37.0 + (omitted) ... + Q71 x 22.0 (6-1)
Sum of n2 area = Q12 x (-14.8) + Q22 x (-10.5) + (omitted) ... + Q72 x 0.0 (6-2)
n3 area sum = Q13 x 24.6 + Q23 x 12.1 + (omitted) ... + Q73 x 10.1 (6-3)
n4 area sum = Q14 x 1.5 + Q24 x (-32.9) + (omitted) ... + Q74 x (-52.2) (6-4)

The index 3 is defined as in Expression (7) using the sum of the N1 to H4 regions shown in Expressions (6-1) to (6-4).
Index 3 = sum of n1 regions + sum of n2 regions + sum of n3 regions + sum of n4 regions−12.6201 (7)
The index 3 is calculated based on a compositional characteristic (distance from the outer edge of the screen of the captured image data) based on the distribution position of the brightness of the captured image data. It is also effective.

  Next, a bias amount calculation process (step S2 in FIG. 6) executed in the bias calculation unit 722 will be described with reference to the flowchart in FIG.

式（８）において、画素輝度値とは、撮影画像データの各画素の輝度であり、平均輝度値とは、撮影画像データの輝度の平均値である。また、全体画素数とは、撮影画像データ全体の画素数である。 First, the luminance Y (brightness) of each pixel is calculated from the RGB (Red, Green, Blue) values of the photographed image data using Equation (A), and the luminance standard deviation (x1) is calculated (step 1). S23). The standard deviation (x1) of luminance is expressed as shown in Equation (8).

In Expression (8), the pixel luminance value is the luminance of each pixel of the captured image data, and the average luminance value is the average value of the luminance of the captured image data. The total number of pixels is the number of pixels of the entire captured image data.

Next, as shown in Expression (9), a luminance difference value (x2) is calculated (step S24).
Difference in luminance value (x2) = (maximum luminance value-average luminance value) / 255 (9)
In Equation (9), the maximum luminance value is the maximum luminance value of the captured image data.

  Next, the average luminance value (x3) of the skin color area in the center of the screen of the captured image data is calculated (step S25), and further, the average luminance value (x4) in the center of the screen is calculated (step S26). Here, the screen center portion is, for example, a region constituted by a region n3 and a region n4 in FIG.

Next, the flesh color luminance distribution value (x5) is calculated (step S27), and this deviation amount calculation processing is completed. Assuming that the maximum luminance value of the skin color area of the captured image data is Yskin_max, the minimum luminance value of the skin color area is Yskin_min, and the average luminance value of the skin color area is Yskin_ave, the skin color luminance distribution value (x5) is expressed as shown in Expression (10). Is done.
x5 = (Yskin_max−Yskin_min) / 2−Yskin_ave (10)

Let x6 be the average luminance value of the skin color area in the center of the screen of the captured image data. Here, the center of the screen is, for example, an area composed of the area n2, the area n3, and the area n4 in FIG. At this time, the index 4 is defined as in Expression (11) using the index 1, index 3, and x6, and the index 5 is defined as in Expression (12) using the index 2, index 3, and x6. The
Index 4 = 0.46 × Index 1 + 0.61 × Index 3 + 0.01 × x6−0.79 (11)
Index 5 = 0.58 x Index 2 + 0.18 x Index 3 + (-0.03) x x6 + 3.34 (12)
Here, the weighting coefficient by which each index is multiplied in Expression (11) and Expression (12) is set in advance according to the shooting conditions.

指標６は、式（１３）のように表される。
指標６＝x1×0.02＋x2×1.13＋x3×0.06＋x4×(-0.01)＋x5×0.03−6.49 （１３）
この指標６は、撮影画像データの画面の構図的な特徴だけでなく、輝度ヒストグラム分布情報を持ち合わせており、特に、ストロボ撮影シーンとアンダー撮影シーンの判別に有効である。 The index 6 is obtained by multiplying the deviation amounts (x1) to (x5) calculated in the deviation amount calculation process by a fourth coefficient set in advance according to the shooting conditions. Table 6 shows a fourth coefficient which is a weighting coefficient by which each deviation amount is multiplied.

The index 6 is expressed as in Expression (13).
Index 6 = x1 x 0.02 + x2 x 1.13 + x3 x 0.06 + x4 x (-0.01) + x5 x 0.03-6.49 (13)
This index 6 has not only the compositional characteristics of the screen of the photographed image data but also the luminance histogram distribution information, and is particularly effective for discriminating between the flash photography scene and the under photography scene.

  Next, the tone adjustment condition determination process (step T4 in FIG. 5) executed in the image processing condition calculation unit 714 will be described with reference to the flowchart in FIG.

  First, the shooting conditions of the captured image data are determined based on the indexes calculated by the index calculation unit 713 (indexes 4 to 6) and the determination map divided in advance according to the shooting conditions (step S30). Hereinafter, a method for determining the photographing condition will be described.

  In FIG. 18A, 60 images are captured under each of the following light, backlight, and strobe shooting conditions, and index 4 and index 5 are calculated for a total of 180 digital image data. The value of index 5 is plotted. FIG. 18B is a graph in which the values of the index 4 and the index 6 of an image in which 60 images are captured under the respective strobe and under imaging conditions and the index 4 is greater than 0.5 are plotted.

  The discriminant map is for evaluating the reliability of the index. As shown in FIG. 19, the basic areas of the following light, the backlight, the strobe and the under, and the low accuracy area (1) between the backlight and the following light, the strobe It consists of a low accuracy region (2) between the under and under. Note that other low-accuracy regions such as a low-accuracy region between backlight and strobe also exist on the discrimination map, but are omitted in this embodiment.

このように、指標４及び指標５の値により光源条件を定量的に判別することができ、指標４及び指標６の値により露出条件を定量的に判別することができる。また、指標４及び指標５の値により、順光と逆光の中間の低確度領域（１）を判別でき、指標４及び指標６の値により、ストロボとアンダーの中間の低確度領域（２）を判別することができる。 Table 7 shows the plots of the index values shown in FIG. 18 and the shooting conditions determined by the determination map of FIG.

Thus, the light source condition can be determined quantitatively based on the values of the index 4 and the index 5, and the exposure condition can be determined quantitatively based on the values of the index 4 and the index 6. Further, the low accuracy region (1) between the forward light and the backlight can be discriminated by the values of the index 4 and the index 5, and the low accuracy region (2) between the strobe and the under can be determined by the values of the index 4 and the index 6. Can be determined.

  When the shooting condition is determined, a gradation adjustment method for the shot image data is determined according to the determined shooting condition (step S31). As shown in FIG. 20, the gradation adjustment method A (FIG. 21 (a)) is selected when the photographing condition is normal light or strobe light, and the gradation adjustment method B (FIG. b)) is selected. In addition, when the shooting condition is intermediate between backlight and direct light or intermediate between strobe and under (that is, a low accuracy region on the discrimination map), the gradation adjustment method C (FIG. 21C) is selected. The

  Thus, since the correction amount is relatively small when the shooting condition is direct light, applying the gradation adjustment method A that translates (offsets) the pixel value of the captured image data can reduce the gamma variation. It is preferable from the viewpoint of suppression. In addition, when the shooting condition is backlight or under, the correction amount is relatively large. Therefore, when the gradation adjustment method A is applied, the gradation where the image data does not exist is remarkably increased. The brightness will be reduced. Therefore, when the shooting condition is backlight or under, it is preferable to apply the gradation adjustment method B in which the pixel value of the shot image data is gamma corrected. Also, in the case of shooting conditions in the low accuracy region on the discrimination map, the tone adjustment method for one of the adjacent shooting conditions is A or B in any low accuracy region, so both tone adjustment methods are mixed. It is preferable to apply the gradation adjustment method C. By setting the low accuracy region in this way, the processing result can be smoothly transferred even when different gradation adjustment methods are used. In addition, it is possible to reduce variations in density among a plurality of photographic prints taken of the same subject. Note that the tone conversion curve shown in FIG. 21B is convex upward, but may be convex downward. Further, the gradation conversion curve shown in FIG. 21C is convex downward, but may be convex upward.

  When the gradation adjustment method is determined, parameters necessary for gradation adjustment are calculated based on the index calculated by the index calculation unit 713 (step S32). Hereinafter, the calculation method of the gradation adjustment parameter calculated in step S32 will be described. In the following description, it is assumed that the 8-bit captured image data is converted in advance to 16 bits, and the unit of the value of the captured image data is 16 bits.

As parameters necessary for gradation adjustment (gradation adjustment parameters), the following parameters P1 to P10 are calculated.
P1: Average brightness of the entire shooting screen
P2: Block division average brightness
P3: Average brightness of skin tone area (H1)
P4: Brightness correction value 1 = P1-P2
P5: Reproduction target correction value = Brightness reproduction target value (30360)-P4
P6: Offset value 1 = P5-P1
P7: Key correction value
P7 ': Key correction value 2
P8: Brightness correction value 2
P9: Offset value 2 = P5-P8-P1
P10: Offset value 3

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

Next, normalized image data for any pixel (Rx, Gx, Bx) of the captured image data is calculated. When Rx normalization data in the R plane is R _point , Gx normalization data in the G plane is G _point , and Bx normalization data in the B plane is B _point , the normalization data R _point , G _point , and B _point are , Respectively, are expressed as in Expression (14) to Expression (16).
R _point = {(Rx−Rmin) / (Rmax−Rmin)} × 65535 (14)
G _point = {(Gx−Gmin) / (Gmax−Gmin)} × 65535 (15)
B _point = {(Bx−Bmin) / (Bmax−Bmin)} × 65535 (16)
Next, the luminance N _point of the pixel (Rx, Gx, Bx) is calculated by Expression (17).
N _point = (B _point + G _point + R _point ) / 3 (17)

  FIG. 22A shows a frequency distribution (histogram) of luminance of RGB pixels before normalization. In FIG. 22A, 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 captured image data according to equations (14) to (16). FIG. 22B shows a histogram of luminance calculated by the equation (17). Since the captured image data is normalized by 65535, each pixel takes an arbitrary value between the maximum value 65535 and the minimum value 0.

  When the luminance histogram shown in FIG. 22B is divided into blocks divided by a predetermined range, a frequency distribution as shown in FIG. 22C is obtained. In FIG. 22C, the horizontal axis is the block number (luminance), and the vertical axis is the frequency.

  Next, a process of deleting highlight and shadow areas is performed from the luminance histogram shown in FIG. This is because the average brightness is very high in white walls and snow scenes, and the average brightness is very low in dark scenes, so highlights and shadow areas adversely affect average brightness control. . Therefore, by limiting the highlight area and shadow area of the luminance histogram shown in FIG. 22C, 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. 23A (or FIG. 22C), the result is as shown in FIG.

  Next, as shown in FIG. 23C, 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. 23C, the number of pixels equal to or greater than the threshold is limited in the luminance histogram. FIG. 23D is a luminance histogram after the pixel number limiting process is performed.

  Each block number of the luminance histogram (FIG. 23 (d)) obtained by deleting the high luminance region and the low luminance region from the normalized luminance histogram, and further limiting the cumulative number of pixels, and the respective frequencies The parameter P2 is obtained by calculating the average luminance based on the above.

The parameter P1 is an average value of the luminance of the entire captured image data, and the parameter P3 is an average value of the luminance of the skin color area (H1) in the captured image data. The key correction value of the parameter P7, the key correction value 2 of the parameter P7 ′, and the luminance correction value 2 of the parameter P8 are defined as Expression (18), Expression (19), and Expression (20), respectively.
P7 (key correction value) = [P3-((index 5/6) x 18000) + 22000)] / 24.78 (18)
P7 '(key correction value 2) = [P3-((index 6/6) x 10000 + 30000)] / 24.78 (19)
P8 (Luminance correction value 2) = (Indicator 4/6) x 17500 (20)

  The offset value 3 of the parameter P10 is a gradation adjustment parameter in the case of shooting conditions corresponding to the low accuracy region (1) or (2) on the discrimination map. Hereinafter, a method for calculating the parameter P10 will be described.

First, a reference index is determined among the indexes in the corresponding low-accuracy region. For example, in the low accuracy region (1), the index 5 is determined as the reference index, and in the low accuracy region (2), the index 6 is determined as the reference index. Then, by normalizing the value of the reference index in the range of 0 to 1, the reference index is converted into a normalized index. The normalization index is defined as in Expression (21).
Normalized index = (reference index−index minimum value) / (index maximum value−index minimum value) (21)
In Expression (21), the index maximum value and the index minimum value are the maximum value and the minimum value of the reference index in the corresponding low accuracy region, respectively.

The correction amounts at the boundary between the corresponding low-accuracy region and two regions adjacent to the low-accuracy region are α and β, respectively. The correction amounts α and β are fixed values calculated in advance using a reproduction target value defined at the boundary of each region on the discrimination map. The parameter P10 is expressed as in Expression (22) using the normalized index of Expression (21) and the correction amounts α and β.
P10 = (β−α) × normalization index + α (22)
In this embodiment, the correlation between the normalization index and the correction amount is a linear relationship, but a curve relationship may be used so that the correction amount can be shifted more gently.

  When the gradation adjustment parameter is calculated, the gradation adjustment amount for the captured image data is determined based on the calculated gradation adjustment parameter (step S33), and the gradation adjustment condition determination process ends. In step S33, specifically, the step corresponding to the gradation adjustment parameter calculated in step S32 is selected from a plurality of gradation conversion curves set in advance corresponding to the gradation adjustment method determined in step S31. A key conversion curve is selected (determined). Note that the gradation conversion curve (gradation adjustment amount) may be calculated based on the gradation adjustment parameter calculated in step S32. When the gradation conversion curve is determined, the photographed image data is gradation converted according to the determined gradation conversion curve.

Hereinafter, a method for determining a gradation conversion curve for each shooting condition will be described.
<For direct light>
When the photographing condition is direct light, offset correction (parallel shift of 8-bit value) for matching the parameter P1 with P5 is performed by the following equation (23).
RGB value of output image = RGB value of input image + P6 (23)
Therefore, when the shooting condition is normal light, a gradation conversion curve corresponding to Expression (23) is selected from the plurality of gradation conversion curves shown in FIG. Alternatively, the gradation conversion curve may be calculated (determined) based on Expression (23).

<In the case of backlight>
When the photographing condition is backlight, a gradation conversion curve corresponding to the parameter P7 (key correction value) shown in Expression (18) is selected from the plurality of gradation conversion curves shown in FIG. A specific example of the gradation conversion curve of FIG. 21B is shown in FIG. The correspondence between the value of parameter P7 and the selected gradation conversion curve is shown below.
When -50 <P7 <+50 → L3
When +50 ≤ P7 <+150 → L4
When +150 ≤ P7 <+250 → L5
When -150 <P7 ≤ -50 → L2
When -250 <P7 ≤ -150 → L1
When the photographing condition is backlight, it is preferable to perform the dodging process together with the gradation conversion process. In this case, it is desirable to adjust the degree of dodging process according to the index 5 indicating the backlight intensity.

<In case of under>
When the shooting condition is under, corresponding to the parameter P7 ′ (key correction value 2) shown in Expression (19) from among the plurality of gradation conversion curves shown in FIG. A tone conversion curve is selected. The correspondence between the value of the parameter P7 ′ and the gradation conversion curve selected in FIG. 24 is shown below.
When -50 <P7 '<+50 → L3
When +50 ≤ P7 '<+150 → L4
When +150 ≤ P7 '<+250 → L5
If -150 <P7 '≤ -50 → L2
-250 <P7 '≤ -150 → L1
When the shooting condition is under, dodging processing as shown in the case of backlight is not performed.

<In the case of strobe>
When the shooting condition is a strobe, offset correction (parallel shift of 8-bit value) is performed by Expression (24).
RGB value of output image = RGB value of input image + P9 (24)
Therefore, when the shooting condition is a strobe, a gradation conversion curve corresponding to Expression (24) is selected from a plurality of gradation conversion curves shown in FIG. Alternatively, the gradation conversion curve may be calculated (determined) based on Expression (24).

<In the case of shooting conditions in the low accuracy area>
When the shooting condition is a low-accuracy region, offset correction (parallel shift of 8-bit value) is performed by Expression (25).
RGB value of output image = RGB value of input image + P10 (25)
Therefore, in the case of the low accuracy region, the gradation conversion curve corresponding to the equation (25) is selected from the plurality of gradation conversion curves shown in FIG. Alternatively, the gradation conversion curve may be calculated (determined) based on Expression (25).

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

  As described above, according to the image processing apparatus 1 of the present embodiment, the index that quantitatively indicates the shooting condition of the captured image data is calculated, and the area is divided in advance according to the calculated index and the accuracy of the shooting condition. By determining the shooting conditions based on the determined determination map, determining the gradation adjustment method for the captured image data according to the determination result, and determining the gradation adjustment amount (gradation conversion curve) of the captured image data It is possible to appropriately correct the brightness of the subject. In particular, by determining the shooting condition based on the determination map, the reliability of the determination result is increased, and appropriate gradation conversion according to the shooting condition can be performed.

  Further, in addition to the index 1 that quantitatively indicates the accuracy as strobe shooting and the index 2 that quantitatively indicates the accuracy as backlight shooting, the shooting is performed using the index 3 derived from the compositional elements of the captured image data. By determining the conditions, it is possible to improve the accuracy of determining the imaging conditions. Further, by using the index 6 calculated from the compositional elements of the photographed image data and the distribution information of the histogram, it is possible to discriminate between the stroboscopic scene and the under-photographed scene, thereby further improving the photographic condition discrimination accuracy. be able to.

<Examples applied to imaging devices>
The image processing method shown in the above embodiment can be applied to an imaging apparatus such as a digital camera. FIG. 25 shows a configuration of a digital camera 200 to which the imaging apparatus of the present invention is applied. As shown in FIG. 25, the digital camera 200 includes a CPU 201, an optical system 202, an imaging sensor unit 203, an AF calculation unit 204, a WB calculation unit 205, an AE calculation unit 206, a lens control unit 207, an image processing unit 208, and a display unit. 209, a recording data creation unit 210, a recording medium 211, a scene mode setting key 212, a color space setting key 213, a release button 214, and other operation keys 215.

  The CPU 201 controls the overall operation of the digital camera 200. The optical system 202 is a zoom lens, and forms a subject image on a CCD (Charge-Coupled Device) image sensor in the image sensor unit 203. The imaging sensor unit 203 photoelectrically converts an optical image by a CCD image sensor, converts it into a digital signal (A / D conversion), and outputs it. The image data output from the imaging sensor unit 203 is input to the AF calculation unit 204, the WB calculation unit 205, the AE calculation unit 206, and the image processing unit 208.

  The AF calculation unit 204 calculates and outputs the distances of the AF areas provided at nine places in the screen. The determination of the distance is performed by determining the contrast of the image, and the CPU 201 selects a value at the shortest distance among them and sets it as the subject distance. The WB calculation unit 205 calculates and outputs a white balance evaluation value of the image. The white balance evaluation value is a gain value necessary for matching the RGB output values of a neutral subject under the light source at the time of photographing, and is calculated as a ratio of R / G and B / G with reference to the G channel. The calculated evaluation value is input to the image processing unit 208, and the white balance of the image is adjusted. The AE calculation unit 206 calculates and outputs an appropriate exposure value from the image data, and the CPU 201 calculates an aperture value and a shutter speed value so that the calculated appropriate exposure value matches the current exposure value. The aperture value is output to the lens control unit 207, and the corresponding aperture diameter is set. The shutter speed value is output to the image sensor unit 203, and the corresponding CCD integration time is set.

  The image processing unit 208 performs processing such as white balance processing, CCD filter array interpolation processing, color conversion, primary gradation conversion, and sharpness correction on the captured image data, and then, similarly to the above-described embodiment. It is preferable to calculate an index (index 1 to 6) for specifying the shooting condition, determine the shooting condition based on the calculated index, and perform the gradation conversion process determined based on the determination result. Convert to image. Thereafter, conversion such as JPEG compression is executed. The JPEG-compressed image data is output to the display unit 209 and the recording data creation unit 210.

  The display unit 209 displays captured image data on a liquid crystal display and various information according to instructions from the CPU 201. The recording data creation unit 210 formats the JPEG-compressed image data and various captured image data input from the CPU 201 into an Exif (Exchangeable Image File Format) file, and records it in the recording medium 211. In the recording medium 211, there is a part called a maker note as a space where each maker can write free information, and the determination result of the photographing condition and the index 4, the index 5 and the index 6 may be recorded.

  In the digital camera 200, the shooting scene mode can be switched by a user setting. In other words, three modes, a normal mode, a portrait mode, and a landscape mode scene, can be selected as the shooting scene mode. The user operates the scene mode setting key 212, and when the subject is a person, the portrait mode and the landscape mode are selected. In this case, the primary gradation conversion suitable for the subject is performed by switching to the landscape mode. In addition, the digital camera 200 adds and records information on the selected shooting scene mode to the maker note portion of the image data file. In addition, the digital camera 200 similarly records the position information of the AF area selected as the subject in the image file.

  In the digital camera 200, the user can set the output color space using the color space setting key 213. As the output color space, sRGB (IEC61966-2-1) and Raw can be selected. When sRGB is selected, image processing according to the present embodiment is executed. When Raw is selected, image processing according to the present embodiment is not performed, and output is performed in a color space unique to the CCD.

  As described above, according to the digital camera 200 to which the imaging apparatus of the present invention is applied, as in the above-described image processing apparatus 1, an index that quantitatively indicates the shooting condition of the shot image data is calculated, and the calculated The shooting condition is determined based on the index, the gradation adjustment method for the captured image data is determined according to the determination result, and the gradation adjustment amount (gradation conversion curve) of the captured image data is determined. It becomes possible to correct the brightness appropriately. As described above, even when the digital camera 200 and the printer are directly connected without going through a personal computer by performing appropriate gradation conversion processing according to the shooting conditions inside the digital camera 200. A preferable image can be output.

  Note that the description in the present embodiment can be changed as appropriate without departing from the spirit of the present invention.

  For example, a face image may be detected from the photographed image data, the photographing condition may be determined based on the detected face image, and the gradation adjustment condition may be determined. Further, Exif information may be used to determine the shooting condition. By using Exif information, it is possible to further improve the accuracy of determining the shooting conditions.

1 is a perspective view showing an external configuration of an image processing apparatus according to an embodiment of the present invention. 1 is a block diagram showing an internal configuration of an image processing apparatus according to an embodiment. The block diagram which shows the principal part structure of the image processing part of FIG. The figure which shows the internal structure (a) of a scene discrimination | determination part, the internal structure (b) of a ratio calculation part, and the internal structure (c) of an image processing condition calculation part. 5 is a flowchart showing a flow of processing executed in an image adjustment processing unit. The flowchart which shows the parameter | index calculation process performed in a scene discrimination | determination part. The flowchart which shows the 1st occupation rate calculation process which calculates the 1st occupation rate for every area | region of lightness and hue. The figure which shows an example of the program which converts from RGB to HSV color system. The figure which shows the brightness | luminance (V) -hue (H) plane, and the area | region r1 and the area | region r2 on a VH plane. The figure which shows the brightness | luminance (V) -hue (H) plane, and the area | region r3 and the area | region r4 on a VH plane. The figure which shows the curve showing the 1st coefficient by which the 1st occupation rate for calculating the parameter | index 1 is multiplied. The figure which shows the curve showing the 2nd coefficient by which the 1st occupation rate for calculating the parameter | index 2 is multiplied. The flowchart which shows the 2nd occupation rate calculation process which calculates a 2nd occupation rate based on the composition of picked-up image data. The figure which shows the area | regions n1-n4 determined according to the distance from the outer edge of the screen of picked-up image data. The figure which shows the curve showing the 3rd coefficient for multiplying the 2nd occupation rate for calculating the parameter | index 3 according to area | region (n1-n4). The flowchart which shows the deviation amount calculation process performed in a deviation calculation part. 6 is a flowchart illustrating tone adjustment condition determination processing executed in an image processing condition calculation unit. The plot figure of the parameter | index 4-6 calculated according to imaging | photography conditions. The figure which shows the discrimination | determination map for discriminating imaging conditions. The figure which shows the relationship between the parameter | index for specifying imaging | photography conditions, parameters AC, and gradation adjustment methods AC. The figure which shows the gradation conversion curve corresponding to each gradation adjustment method. The figure which shows the frequency distribution (histogram) (a) of brightness | luminance, the normalized histogram (b), and the block-divided histogram (c). The figure ((a) and (b)) explaining deletion of the low-intensity area | region and the high-intensity area | region from the brightness | luminance histogram, and the figure ((c) and (d)) explaining the restriction | limiting of the frequency of a brightness | luminance. The figure which shows the gradation conversion curve showing the gradation adjustment conditions in case imaging | photography conditions are backlight or under. 1 is a block diagram illustrating a configuration of a digital camera to which an imaging apparatus of the present invention is applied.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Image processing apparatus 2 Case 3 Magazine loading part 4 Exposure processing part 5 Print preparation part 7 Control part 8 CRT
DESCRIPTION OF SYMBOLS 9 Film scanner part 10 Reflected original input device 11 Operation part 12 Information input means 14 Image reading part 15 Image writing part 30 Image transfer means 31 Image conveying part 32 Communication means (input)
33 Communication means (output)
51 External Printer 70 Image Processing Unit 72 Template Storage Unit 701 Image Adjustment Processing Unit 702 Film Scan Data Processing Unit 703 Reflected Original Scan Data Processing Unit 704 Image Data Format Decoding Processing Unit 705 Template Processing Unit 706 CRT Specific Processing Unit 707 Print Specific Processing Unit A
708 Print unique processing section B
709 Image data format creation processing unit 710 Scene determination unit 711 Gradation conversion unit 712 Ratio calculation unit 713 Index calculation unit 714 Image processing condition calculation unit 715 Color system conversion unit 716 Histogram creation unit 717 Occupancy calculation unit 718 Scene determination unit 719 Gradation adjustment method determination unit 720 Gradation adjustment parameter calculation unit 721 Gradation adjustment amount calculation unit 722 Bias calculation unit 200 Digital camera (imaging device)
208 Image processing unit

Claims (96)

Occupancy rate calculating step of dividing the captured image data into regions composed of combinations of predetermined brightness and hue, and calculating an occupancy ratio indicating the proportion of the entire captured image data for each of the divided regions;
A deviation amount calculating step of calculating a deviation amount indicating a deviation in gradation distribution of the photographed image data;
In order to specify the shooting condition by multiplying the occupation ratio of each region calculated in the occupation ratio calculation step and the deviation amount calculated in the deviation amount calculation step by a coefficient set in advance according to the imaging condition An index calculation process for calculating an index of
A determination step of determining a shooting condition of the captured image data based on the calculated index and a determination map divided in advance according to the accuracy of the shooting condition;
An adjustment method determining step for determining a method of gradation adjustment for the captured image data according to the determined imaging condition;
A gradation conversion step of performing gradation conversion processing on the photographed image data using the determined gradation adjustment method;
An image processing method comprising: Occupancy rate calculating step of dividing the captured image data into regions composed of combinations of predetermined brightness and hue, and calculating an occupancy ratio indicating the proportion of the entire captured image data for each of the divided regions;
A deviation amount calculating step of calculating a deviation amount indicating a deviation in gradation distribution of the photographed image data;
In order to specify the shooting condition by multiplying the occupation ratio of each region calculated in the occupation ratio calculation step and the deviation amount calculated in the deviation amount calculation step by a coefficient set in advance according to the imaging condition An index calculation process for calculating an index of
A determination step of determining a shooting condition of the captured image data based on the calculated index and a determination map divided in advance according to the accuracy of the shooting condition;
An adjustment method determining step for determining a method of gradation adjustment for the captured image data according to the determined imaging condition;
An adjustment amount determining step for determining a gradation adjustment amount for the captured image data based on the calculated index;
A gradation conversion step of performing gradation conversion processing of the gradation adjustment amount determined in the adjustment amount determination step on the captured image data using the gradation adjustment method determined in the adjustment method determination step;
An image processing method comprising: The photographed image data is divided into predetermined areas composed of a combination of the distance from the outer edge of the screen of the photographed image data and the brightness, and an occupancy ratio indicating the ratio of the entire photographed image data for each of the divided areas. An occupancy calculation step to calculate,
A deviation amount calculating step of calculating a deviation amount indicating a deviation in gradation distribution of the photographed image data;
In order to specify the shooting condition by multiplying the occupation ratio of each region calculated in the occupation ratio calculation step and the deviation amount calculated in the deviation amount calculation step by a coefficient set in advance according to the imaging condition An index calculation process for calculating an index of
A determination step of determining a shooting condition of the captured image data based on the calculated index and a determination map divided in advance according to the accuracy of the shooting condition;
An adjustment method determining step for determining a method of gradation adjustment for the captured image data according to the determined imaging condition;
A gradation conversion step of performing gradation conversion processing on the photographed image data using the determined gradation adjustment method;
An image processing method comprising: The photographed image data is divided into predetermined areas composed of a combination of the distance from the outer edge of the screen of the photographed image data and the brightness, and an occupancy ratio indicating the ratio of the entire photographed image data for each of the divided areas. An occupancy calculation step to calculate,
A deviation amount calculating step of calculating a deviation amount indicating a deviation in gradation distribution of the photographed image data;
In order to specify the shooting condition by multiplying the occupation ratio of each region calculated in the occupation ratio calculation step and the deviation amount calculated in the deviation amount calculation step by a coefficient set in advance according to the imaging condition An index calculation process for calculating an index of
A determination step of determining a shooting condition of the captured image data based on the calculated index and a determination map divided in advance according to the accuracy of the shooting condition;
An adjustment method determining step for determining a method of gradation adjustment for the captured image data according to the determined imaging condition;
An adjustment amount determining step for determining a gradation adjustment amount for the captured image data based on the calculated index;
A gradation conversion step of performing gradation conversion processing of the gradation adjustment amount determined in the adjustment amount determination step on the captured image data using the gradation adjustment method determined in the adjustment method determination step;
An image processing method comprising: The photographed image data is divided into regions composed of a combination of predetermined brightness and hue, and a first occupancy ratio indicating the proportion of the whole photographed image data is calculated for each of the divided regions, and the photographed image data Is divided into predetermined areas composed of a combination of the distance from the outer edge of the screen of the photographed image data and the brightness, and a second occupancy ratio indicating the proportion of the whole photographed image data is determined for each of the divided areas. An occupancy calculation step to calculate,
A deviation amount calculating step of calculating a deviation amount indicating a deviation in gradation distribution of the photographed image data;
By multiplying the first occupancy ratio and the second occupancy ratio calculated in the occupancy ratio calculation step and the deviation amount calculated in the deviation amount calculation step by a coefficient set in advance according to the shooting condition. An index calculation step for calculating an index for specifying the shooting conditions;
A determination step of determining a shooting condition of the captured image data based on the calculated index and a determination map divided in advance according to the accuracy of the shooting condition;
An adjustment method determining step for determining a method of gradation adjustment for the captured image data according to the determined imaging condition;
A gradation conversion step of performing gradation conversion processing on the photographed image data using the determined gradation adjustment method;
An image processing method comprising: The photographed image data is divided into regions composed of a combination of predetermined brightness and hue, and a first occupancy ratio indicating the proportion of the whole photographed image data is calculated for each of the divided regions, and the photographed image data Is divided into predetermined areas composed of a combination of the distance from the outer edge of the screen of the photographed image data and the brightness, and a second occupancy ratio indicating the proportion of the whole photographed image data is determined for each of the divided areas. An occupancy calculation step to calculate,
A deviation amount calculating step of calculating a deviation amount indicating a deviation in gradation distribution of the photographed image data;
By multiplying the first occupancy ratio and the second occupancy ratio calculated in the occupancy ratio calculation step and the deviation amount calculated in the deviation amount calculation step by a coefficient set in advance according to the shooting condition. An index calculation step for calculating an index for specifying the shooting conditions;
A determination step of determining a shooting condition of the captured image data based on the calculated index and a determination map divided in advance according to the accuracy of the shooting condition;
An adjustment method determining step for determining a method of gradation adjustment for the captured image data according to the determined imaging condition;
An adjustment amount determining step for determining a gradation adjustment amount for the captured image data based on the calculated index;
A gradation conversion step of performing gradation conversion processing of the gradation adjustment amount determined in the adjustment amount determination step on the captured image data using the gradation adjustment method determined in the adjustment method determination step;
An image processing method comprising: Creating a two-dimensional histogram by calculating the cumulative number of pixels for each distance and brightness from the outer edge of the screen of the captured image data,
The image processing method according to claim 3 or 4, wherein, in the occupancy rate calculating step, the occupancy rate is calculated based on the created two-dimensional histogram. Creating a two-dimensional histogram by calculating the cumulative number of pixels for each distance and brightness from the outer edge of the screen of the captured image data,
The image processing method according to claim 5 or 6, wherein, in the occupancy rate calculating step, the second occupancy rate is calculated based on the created two-dimensional histogram. Creating a two-dimensional histogram by calculating the cumulative number of pixels for each predetermined hue and brightness of the captured image data;
The image processing method according to claim 1, wherein, in the occupancy rate calculating step, the occupancy rate is calculated based on the created two-dimensional histogram. Creating a two-dimensional histogram by calculating the cumulative number of pixels for each predetermined hue and brightness of the captured image data;
The image processing method according to claim 5 or 6, wherein, in the occupancy rate calculating step, the first occupancy rate is calculated based on the created two-dimensional histogram.   In the index calculation step, coefficients having different signs are used in a predetermined high-lightness skin color hue region and a hue region other than the high-lightness skin color hue region. The image processing method according to any one of 6, 8 to 10.   12. The index calculation step uses coefficients having different signs for an intermediate brightness area of a flesh hue area and a brightness area other than the intermediate brightness area. An image processing method according to any one of the above.   The image processing method according to claim 11, wherein a lightness region of a hue region other than the high lightness skin color hue region is a predetermined high lightness region.   The image processing method according to claim 12, wherein the brightness area other than the intermediate brightness area is a brightness area in a flesh-color hue area.   The image processing method according to claim 11 or 13, wherein the high lightness skin color hue region includes a region having a lightness value of HSV color system in a range of 170 to 224.   The image processing method according to claim 12 or 14, wherein the intermediate lightness region includes a region having a lightness value of HSV color system in a range of 85 to 169.   16. The image processing method according to claim 11, wherein the hue area other than the high brightness skin color hue area includes at least one of a blue hue area and a green hue area. .   The image processing method according to any one of claims 12, 14, and 16, wherein a brightness area other than the intermediate brightness area is a shadow area.   The hue value of the blue hue region is in the range of 161 to 250 as the hue value of the HSV color system, and the hue value of the green hue region is in the range of from 40 to 160 as the hue value of the HSV color system. The image processing method according to claim 17, wherein the image processing method is provided.   The image processing method according to claim 18, wherein the brightness value of the shadow area is in the range of 26 to 84 as the brightness value of the HSV color system.   21. The image processing method according to claim 11, wherein a hue value of the flesh color hue region is in a range of 0 to 39 and 330 to 359 as a hue value of the HSV color system. .   The image processing method according to any one of claims 11 to 21, wherein the skin color hue region is divided into two regions by a predetermined conditional expression based on brightness and saturation.   The deviation amount includes at least one of the brightness deviation amount of the captured image data, the average brightness value of the captured image data at the center of the screen, and the brightness difference value calculated under different conditions. The image processing method according to claim 1, wherein the image processing method is an image processing method. The shooting conditions indicate light source conditions and exposure conditions during shooting,
The light source condition includes a strobe shooting state, and the exposure condition includes an under shooting state derived from a shutter speed and an aperture value at the time of shooting. An image processing method described in 1. Occupancy rate calculating means for dividing the captured image data into regions composed of combinations of predetermined brightness and hue, and for each of the divided regions, calculating an occupancy rate indicating the proportion of the entire captured image data;
A deviation amount calculating means for calculating a deviation amount indicating a deviation in gradation distribution of the photographed image data;
To specify the shooting condition by multiplying the occupation ratio of each area calculated by the occupancy ratio calculating means and the deviation amount calculated by the deviation amount calculating means by a coefficient set in advance according to the shooting conditions. Index calculating means for calculating the index of
A discriminating means for discriminating a photographing condition of the photographed image data based on the calculated index and a discriminant map previously divided according to the accuracy of the photographing condition;
An adjustment method determining means for determining a method of gradation adjustment for the captured image data according to the determined imaging condition;
Gradation conversion means for performing gradation conversion processing on the captured image data using the determined gradation adjustment method;
An image processing apparatus comprising: Occupancy rate calculating means for dividing the captured image data into regions composed of combinations of predetermined brightness and hue, and for each of the divided regions, calculating an occupancy rate indicating the proportion of the entire captured image data;
A deviation amount calculating means for calculating a deviation amount indicating a deviation in gradation distribution of the photographed image data;
To specify the shooting condition by multiplying the occupation ratio of each area calculated by the occupancy ratio calculating means and the deviation amount calculated by the deviation amount calculating means by a coefficient set in advance according to the shooting conditions. Index calculating means for calculating the index of
A discriminating means for discriminating a photographing condition of the photographed image data based on the calculated index and a discriminant map previously divided according to the accuracy of the photographing condition;
An adjustment method determining means for determining a method of gradation adjustment for the captured image data according to the determined imaging condition;
Adjustment amount determining means for determining a gradation adjustment amount for the captured image data based on the calculated index;
Gradation conversion means for performing gradation conversion processing of the gradation adjustment amount determined by the adjustment amount determination means on the captured image data using the gradation adjustment method determined by the adjustment method determination means;
An image processing apparatus comprising: The photographed image data is divided into predetermined areas composed of a combination of the distance from the outer edge of the screen of the photographed image data and the brightness, and an occupation ratio indicating a ratio of the whole photographed image data for each of the divided areas. Occupancy ratio calculating means for calculating;
A deviation amount calculating means for calculating a deviation amount indicating a deviation in gradation distribution of the photographed image data;
To specify the shooting condition by multiplying the occupation ratio of each area calculated by the occupancy ratio calculating means and the deviation amount calculated by the deviation amount calculating means by a coefficient set in advance according to the shooting conditions. Index calculating means for calculating the index of
A discriminating means for discriminating a photographing condition of the photographed image data based on the calculated index and a discriminant map previously divided according to the accuracy of the photographing condition;
An adjustment method determining means for determining a method of gradation adjustment for the captured image data according to the determined imaging condition;
Gradation conversion means for performing gradation conversion processing on the captured image data using the determined gradation adjustment method;
An image processing apparatus comprising: The photographed image data is divided into predetermined areas composed of a combination of the distance from the outer edge of the screen of the photographed image data and the brightness, and an occupation ratio indicating a ratio of the whole photographed image data for each of the divided areas. Occupancy ratio calculating means for calculating;
A deviation amount calculating means for calculating a deviation amount indicating a deviation in gradation distribution of the photographed image data;
To specify the shooting condition by multiplying the occupation ratio of each area calculated by the occupancy ratio calculating means and the deviation amount calculated by the deviation amount calculating means by a coefficient set in advance according to the shooting conditions. Index calculating means for calculating the index of
A discriminating means for discriminating a photographing condition of the photographed image data based on the calculated index and a discriminant map previously divided according to the accuracy of the photographing condition;
An adjustment method determining means for determining a method of gradation adjustment for the captured image data according to the determined imaging condition;
Adjustment amount determining means for determining a gradation adjustment amount for the captured image data based on the calculated index;
Gradation conversion means for performing gradation conversion processing of the gradation adjustment amount determined by the adjustment amount determination means on the captured image data using the gradation adjustment method determined by the adjustment method determination means;
An image processing apparatus comprising: The photographed image data is divided into regions composed of a combination of predetermined brightness and hue, and a first occupation ratio indicating a ratio of the whole photographed image data is calculated for each of the divided regions, and the photographed image data Is divided into predetermined areas consisting of a combination of the distance from the outer edge of the screen of the photographed image data and the brightness, and a second occupancy ratio indicating the proportion of the whole photographed image data for each of the divided areas is obtained. Occupancy ratio calculating means for calculating;
A deviation amount calculating means for calculating a deviation amount indicating a deviation in gradation distribution of the photographed image data;
By multiplying the first occupancy ratio and the second occupancy ratio calculated by the occupancy ratio calculating means and the deviation amount calculated by the deviation amount calculating means by a coefficient set in advance according to the photographing condition. , An index calculating means for calculating an index for specifying the shooting conditions;
A discriminating means for discriminating a photographing condition of the photographed image data based on the calculated index and a discriminant map previously divided according to the accuracy of the photographing condition;
An adjustment method determining means for determining a method of gradation adjustment for the captured image data according to the determined imaging condition;
Gradation conversion means for performing gradation conversion processing on the captured image data using the determined gradation adjustment method;
An image processing apparatus comprising: The photographed image data is divided into regions composed of a combination of predetermined brightness and hue, and a first occupation ratio indicating a ratio of the whole photographed image data is calculated for each of the divided regions, and the photographed image data Is divided into predetermined areas consisting of a combination of the distance from the outer edge of the screen of the photographed image data and the brightness, and a second occupancy ratio indicating the proportion of the whole photographed image data for each of the divided areas is obtained. Occupancy ratio calculating means for calculating;
A deviation amount calculating means for calculating a deviation amount indicating a deviation in gradation distribution of the photographed image data;
By multiplying the first occupancy ratio and the second occupancy ratio calculated by the occupancy ratio calculating means and the deviation amount calculated by the deviation amount calculating means by a coefficient set in advance according to the photographing condition. , An index calculating means for calculating an index for specifying the shooting conditions;
A discriminating means for discriminating a photographing condition of the photographed image data based on the calculated index and a discriminant map previously divided according to the accuracy of the photographing condition;
An adjustment method determining means for determining a method of gradation adjustment for the captured image data according to the determined imaging condition;
Adjustment amount determining means for determining a gradation adjustment amount for the captured image data based on the calculated index;
Gradation conversion means for performing gradation conversion processing of the gradation adjustment amount determined by the adjustment amount determination means on the captured image data using the gradation adjustment method determined by the adjustment method determination means;
An image processing apparatus comprising: Means for creating a two-dimensional histogram by calculating the cumulative number of pixels for each distance and brightness from the outer edge of the screen of the captured image data;
The image processing apparatus according to claim 27 or 28, wherein the occupancy ratio calculating unit calculates the occupancy ratio based on the created two-dimensional histogram. Means for creating a two-dimensional histogram by calculating the cumulative number of pixels for each distance and brightness from the outer edge of the screen of the captured image data;
31. The image processing apparatus according to claim 29, wherein the occupancy rate calculating unit calculates the second occupancy rate based on the created two-dimensional histogram. Means for creating a two-dimensional histogram by calculating the cumulative number of pixels for each predetermined hue and brightness of the photographed image data;
27. The image processing apparatus according to claim 25, wherein the occupancy ratio calculating unit calculates the occupancy ratio based on the created two-dimensional histogram. Means for creating a two-dimensional histogram by calculating the cumulative number of pixels for each predetermined hue and brightness of the photographed image data;
31. The image processing apparatus according to claim 29, wherein the occupancy rate calculating unit calculates the first occupancy rate based on the created two-dimensional histogram.   The coefficient calculation unit uses coefficients of different signs for a predetermined high-lightness skin color hue region and a hue region other than the high-lightness skin color hue region, 25, 26, 29, The image processing apparatus according to any one of 30, 32 and 34.   The coefficient calculation unit uses coefficients with different signs for an intermediate brightness area of a flesh-color hue area and a brightness area other than the intermediate brightness area. The image processing apparatus according to any one of the above.   36. The image processing apparatus according to claim 35, wherein a brightness area of a hue area other than the high brightness skin color hue area is a predetermined high brightness area.   37. The image processing apparatus according to claim 36, wherein the brightness area other than the intermediate brightness area is a brightness area within a flesh-color hue area.   38. The image processing apparatus according to claim 35, wherein the high lightness skin color hue region includes a region having a lightness value in the HSV color system of 170 to 224.   39. The image processing apparatus according to claim 36 or 38, wherein the intermediate brightness area includes an area having a brightness value in the HSV color system of 85 to 169.   The image processing apparatus according to any one of claims 35, 37, and 39, wherein the hue area other than the high brightness skin color hue area includes at least one of a blue hue area and a green hue area. .   41. The image processing apparatus according to claim 36, 38, or 40, wherein the brightness area other than the intermediate brightness area is a shadow area.   The hue value of the blue hue region is in the range of 161 to 250 as the hue value of the HSV color system, and the hue value of the green hue region is in the range of from 40 to 160 as the hue value of the HSV color system. The image processing apparatus according to claim 41, wherein the image processing apparatus is provided.   43. The image processing apparatus according to claim 42, wherein a lightness value of the shadow area is within a range of 26 to 84 as a lightness value of the HSV color system.   45. The image processing apparatus according to claim 35, wherein a hue value of the skin color hue region is in a range of 0 to 39 and 330 to 359 as a hue value of the HSV color system. .   The image processing device according to any one of claims 35 to 45, wherein the skin color hue region is divided into two regions according to a predetermined conditional expression based on lightness and saturation.   The deviation amount includes at least one of the brightness deviation amount of the captured image data, the average brightness value of the captured image data at the center of the screen, and the brightness difference value calculated under different conditions. The image processing apparatus according to any one of claims 25 to 46, wherein: The shooting conditions indicate light source conditions and exposure conditions during shooting,
48. The light source condition includes a strobe shooting state, and the exposure condition includes an under shooting state derived from a shutter speed and an aperture value at the time of shooting. An image processing apparatus according to 1. Imaging means for photographing a subject and obtaining photographed image data;
Occupancy rate calculating means for dividing the photographed image data into regions composed of combinations of predetermined brightness and hue, and for each of the divided regions, calculating an occupation rate indicating a proportion of the entire photographed image data;
A deviation amount calculating means for calculating a deviation amount indicating a deviation in gradation distribution of the photographed image data;
To specify the shooting condition by multiplying the occupation ratio of each area calculated by the occupancy ratio calculating means and the deviation amount calculated by the deviation amount calculating means by a coefficient set in advance according to the shooting conditions. Index calculating means for calculating the index of
A discriminating means for discriminating a photographing condition of the photographed image data based on the calculated index and a discriminant map previously divided according to the accuracy of the photographing condition;
An adjustment method determining means for determining a method of gradation adjustment for the captured image data according to the determined imaging condition;
Gradation conversion means for performing gradation conversion processing on the captured image data using the determined gradation adjustment method;
An imaging apparatus comprising: Imaging means for photographing a subject and obtaining photographed image data;
Occupancy rate calculating means for dividing the photographed image data into regions composed of combinations of predetermined brightness and hue, and for each of the divided regions, calculating an occupation rate indicating a proportion of the entire photographed image data;
A deviation amount calculating means for calculating a deviation amount indicating a deviation in gradation distribution of the photographed image data;
To specify the shooting condition by multiplying the occupation ratio of each area calculated by the occupancy ratio calculating means and the deviation amount calculated by the deviation amount calculating means by a coefficient set in advance according to the shooting conditions. Index calculating means for calculating the index of
A discriminating means for discriminating a photographing condition of the photographed image data based on the calculated index and a discriminant map previously divided according to the accuracy of the photographing condition;
An adjustment method determining means for determining a method of gradation adjustment for the captured image data according to the determined imaging condition;
Adjustment amount determining means for determining a gradation adjustment amount for the captured image data based on the calculated index;
Gradation conversion means for performing gradation conversion processing of the gradation adjustment amount determined by the adjustment amount determination means on the captured image data using the gradation adjustment method determined by the adjustment method determination means;
An imaging apparatus comprising: Imaging means for photographing a subject and obtaining photographed image data;
Dividing the photographed image data into predetermined areas composed of a combination of the distance from the outer edge of the screen of the photographed image data and the brightness, and an occupancy ratio indicating a ratio of the entire photographed image data for each of the divided areas Occupancy ratio calculating means for calculating
A deviation amount calculating means for calculating a deviation amount indicating a deviation in gradation distribution of the photographed image data;
To specify the shooting condition by multiplying the occupation ratio of each area calculated by the occupancy ratio calculating means and the deviation amount calculated by the deviation amount calculating means by a coefficient set in advance according to the shooting conditions. Index calculating means for calculating the index of
A discriminating means for discriminating a photographing condition of the photographed image data based on the calculated index and a discriminant map previously divided according to the accuracy of the photographing condition;
An adjustment method determining means for determining a method of gradation adjustment for the captured image data according to the determined imaging condition;
Gradation conversion means for performing gradation conversion processing on the captured image data using the determined gradation adjustment method;
An imaging apparatus comprising: Imaging means for photographing a subject and obtaining photographed image data;
Dividing the photographed image data into predetermined areas composed of a combination of the distance from the outer edge of the screen of the photographed image data and the brightness, and an occupancy ratio indicating a ratio of the entire photographed image data for each of the divided areas Occupancy ratio calculating means for calculating
A deviation amount calculating means for calculating a deviation amount indicating a deviation in gradation distribution of the photographed image data;
To specify the shooting condition by multiplying the occupation ratio of each area calculated by the occupancy ratio calculating means and the deviation amount calculated by the deviation amount calculating means by a coefficient set in advance according to the shooting conditions. Index calculating means for calculating the index of
A discriminating means for discriminating a photographing condition of the photographed image data based on the calculated index and a discriminant map previously divided according to the accuracy of the photographing condition;
An adjustment method determining means for determining a method of gradation adjustment for the captured image data according to the determined imaging condition;
Adjustment amount determining means for determining a gradation adjustment amount for the captured image data based on the calculated index;
Gradation conversion means for performing gradation conversion processing of the gradation adjustment amount determined by the adjustment amount determination means on the captured image data using the gradation adjustment method determined by the adjustment method determination means;
An imaging apparatus comprising: Imaging means for photographing a subject and obtaining photographed image data;
The photographed image data is divided into regions composed of a combination of predetermined brightness and hue, and a first occupancy ratio indicating the proportion of the whole photographed image data is calculated for each of the divided regions, and the photographed image A second occupancy ratio that divides the data into a predetermined area composed of a combination of the distance from the outer edge of the screen of the captured image data and the brightness and occupies the entire captured image data for each of the divided areas Occupancy ratio calculating means for calculating
A deviation amount calculating means for calculating a deviation amount indicating a deviation in gradation distribution of the photographed image data;
By multiplying the first occupancy ratio and the second occupancy ratio calculated by the occupancy ratio calculating means and the deviation amount calculated by the deviation amount calculating means by a coefficient set in advance according to the photographing condition. , An index calculating means for calculating an index for specifying the shooting conditions;
A discriminating means for discriminating a photographing condition of the photographed image data based on the calculated index and a discriminant map previously divided according to the accuracy of the photographing condition;
An adjustment method determining means for determining a method of gradation adjustment for the captured image data according to the determined imaging condition;
Gradation conversion means for performing gradation conversion processing on the captured image data using the determined gradation adjustment method;
An imaging apparatus comprising: Imaging means for photographing a subject and obtaining photographed image data;
The photographed image data is divided into regions composed of a combination of predetermined brightness and hue, and a first occupancy ratio indicating the proportion of the whole photographed image data is calculated for each of the divided regions, and the photographed image A second occupancy ratio that divides the data into a predetermined area composed of a combination of the distance from the outer edge of the screen of the captured image data and the brightness and occupies the entire captured image data for each of the divided areas Occupancy ratio calculating means for calculating
A deviation amount calculating means for calculating a deviation amount indicating a deviation in gradation distribution of the photographed image data;
By multiplying the first occupancy ratio and the second occupancy ratio calculated by the occupancy ratio calculating means and the deviation amount calculated by the deviation amount calculating means by a coefficient set in advance according to the photographing condition. , An index calculating means for calculating an index for specifying the shooting conditions;
A discriminating means for discriminating a photographing condition of the photographed image data based on the calculated index and a discriminant map previously divided according to the accuracy of the photographing condition;
An adjustment method determining means for determining a method of gradation adjustment for the captured image data according to the determined imaging condition;
Adjustment amount determining means for determining a gradation adjustment amount for the captured image data based on the calculated index;
Gradation conversion means for performing gradation conversion processing of the gradation adjustment amount determined by the adjustment amount determination means on the captured image data using the gradation adjustment method determined by the adjustment method determination means;
An imaging apparatus comprising: Means for creating a two-dimensional histogram by calculating the cumulative number of pixels for each distance and brightness from the outer edge of the screen of the captured image data;
53. The imaging apparatus according to claim 51, wherein the occupancy ratio calculating unit calculates the occupancy ratio based on the created two-dimensional histogram. Means for creating a two-dimensional histogram by calculating the cumulative number of pixels for each distance and brightness from the outer edge of the screen of the captured image data;
55. The imaging apparatus according to claim 53 or 54, wherein the occupancy rate calculating unit calculates the second occupancy rate based on the created two-dimensional histogram. Means for creating a two-dimensional histogram by calculating the cumulative number of pixels for each predetermined hue and brightness of the photographed image data;
51. The imaging apparatus according to claim 49, wherein the occupancy rate calculation unit calculates the occupancy rate based on the created two-dimensional histogram. Means for creating a two-dimensional histogram by calculating the cumulative number of pixels for each predetermined hue and brightness of the photographed image data;
55. The imaging apparatus according to claim 53 or 54, wherein the occupancy rate calculating means calculates the first occupancy rate based on the created two-dimensional histogram.   The coefficient calculation means uses coefficients of different signs for a predetermined high-lightness skin color hue region and a hue region other than the high-lightness skin color hue region, 49, 50, 53, 54. The imaging device according to any one of 54, 56 to 58.   The index calculation means uses coefficients of different signs for the intermediate brightness area of the flesh hue area and the brightness areas other than the intermediate brightness area. The imaging device according to any one of the above.   60. The imaging apparatus according to claim 59, wherein a brightness area of a hue area other than the high brightness skin color hue area is a predetermined high brightness area.   61. The imaging apparatus according to claim 60, wherein the brightness area other than the intermediate brightness area is a brightness area in a flesh-color hue area.   62. The imaging apparatus according to claim 59 or 61, wherein the skin color hue region of high brightness includes a region in the range of 170 to 224 in terms of brightness values of the HSV color system.   63. The imaging apparatus according to claim 60, wherein the intermediate lightness region includes a region having a lightness value of HSV color system in a range of 85 to 169.   64. The imaging apparatus according to claim 59, wherein the hue area other than the high brightness skin color hue area includes at least one of a blue hue area and a green hue area.   The imaging apparatus according to any one of claims 60, 62, and 64, wherein the brightness area other than the intermediate brightness area is a shadow area.   The hue value of the blue hue region is in the range of 161 to 250 as the hue value of the HSV color system, and the hue value of the green hue region is in the range of from 40 to 160 as the hue value of the HSV color system. The imaging apparatus according to claim 65, wherein the imaging apparatus is provided.   67. The imaging apparatus according to claim 66, wherein the brightness value of the shadow region is in the range of 26 to 84 as the brightness value of the HSV color system.   69. The image pickup apparatus according to any one of claims 59 to 68, wherein a hue value of the skin color hue region is in a range of 0 to 39 and 330 to 359 as a hue value of an HSV color system.   The imaging apparatus according to any one of claims 59 to 69, wherein the skin color hue region is divided into two regions according to a predetermined conditional expression based on brightness and saturation.   The deviation amount includes at least one of the brightness deviation amount of the captured image data, the average brightness value of the captured image data at the center of the screen, and the brightness difference value calculated under different conditions. The imaging device according to any one of claims 49 to 70, wherein: The shooting conditions indicate light source conditions and exposure conditions during shooting,
72. The light source condition includes a strobe shooting state, and the exposure condition includes an under shooting state derived from a shutter speed and an aperture value at the time of shooting. The imaging device described in 1. In the computer for executing image processing,
Occupancy rate calculation function for dividing the captured image data into regions composed of combinations of predetermined brightness and hue, and for each of the divided regions, calculating an occupation rate indicating the proportion of the entire captured image data;
A deviation amount calculation function for calculating a deviation amount indicating a deviation in gradation distribution of the captured image data;
To specify the shooting condition by multiplying the occupation ratio of each area calculated by the occupation ratio calculation function and the deviation amount calculated by the deviation amount calculation function by a coefficient set in advance according to the imaging condition. An index calculation function to calculate
A discriminating function for discriminating the photographing condition of the photographed image data based on the calculated index and a discriminant map preliminarily divided according to the accuracy of the photographing condition;
An adjustment method determining function for determining a method of gradation adjustment for the captured image data according to the determined shooting condition;
A gradation conversion function for performing gradation conversion processing on the captured image data using the determined gradation adjustment method;
An image processing program for realizing In the computer for executing image processing,
Occupancy rate calculation function for dividing the captured image data into regions composed of combinations of predetermined brightness and hue, and for each of the divided regions, calculating an occupation rate indicating the proportion of the entire captured image data;
A deviation amount calculation function for calculating a deviation amount indicating a deviation in gradation distribution of the captured image data;
To specify the shooting condition by multiplying the occupation ratio of each area calculated by the occupation ratio calculation function and the deviation amount calculated by the deviation amount calculation function by a coefficient set in advance according to the imaging condition. An index calculation function to calculate
A discriminating function for discriminating the photographing condition of the photographed image data based on the calculated index and a discriminant map preliminarily divided according to the accuracy of the photographing condition;
An adjustment method determining function for determining a method of gradation adjustment for the captured image data according to the determined shooting condition;
An adjustment amount determination function for determining a gradation adjustment amount for the captured image data based on the calculated index;
A gradation conversion function for performing gradation conversion processing of the gradation adjustment amount determined by the adjustment amount determination function on the captured image data using the gradation adjustment method determined by the adjustment method determination function;
An image processing program for realizing In the computer for executing image processing,
The photographed image data is divided into predetermined areas composed of a combination of the distance from the outer edge of the screen of the photographed image data and the brightness, and an occupancy ratio indicating the ratio of the entire photographed image data for each of the divided areas. Occupancy rate calculation function to calculate,
A deviation amount calculation function for calculating a deviation amount indicating a deviation in gradation distribution of the captured image data;
To specify the shooting condition by multiplying the occupation ratio of each area calculated by the occupation ratio calculation function and the deviation amount calculated by the deviation amount calculation function by a coefficient set in advance according to the imaging condition. An index calculation function to calculate
A discriminating function for discriminating the photographing condition of the photographed image data based on the calculated index and a discriminant map preliminarily divided according to the accuracy of the photographing condition;
An adjustment method determining function for determining a method of gradation adjustment for the captured image data according to the determined shooting condition;
A gradation conversion function for performing gradation conversion processing on the captured image data using the determined gradation adjustment method;
An image processing program for realizing In the computer for executing image processing,
The photographed image data is divided into predetermined areas composed of a combination of the distance from the outer edge of the screen of the photographed image data and the brightness, and an occupancy ratio indicating the ratio of the entire photographed image data for each of the divided areas. Occupancy rate calculation function to calculate,
A deviation amount calculation function for calculating a deviation amount indicating a deviation in gradation distribution of the captured image data;
To specify the shooting condition by multiplying the occupation ratio of each area calculated by the occupation ratio calculation function and the deviation amount calculated by the deviation amount calculation function by a coefficient set in advance according to the imaging condition. An index calculation function to calculate
A discriminating function for discriminating the photographing condition of the photographed image data based on the calculated index and a discriminant map preliminarily divided according to the accuracy of the photographing condition;
An adjustment method determining function for determining a method of gradation adjustment for the captured image data according to the determined shooting condition;
An adjustment amount determination function for determining a gradation adjustment amount for the captured image data based on the calculated index;
A gradation conversion function for performing gradation conversion processing of the gradation adjustment amount determined by the adjustment amount determination function on the captured image data using the gradation adjustment method determined by the adjustment method determination function;
An image processing program for realizing In the computer for executing image processing,
The photographed image data is divided into regions composed of a combination of predetermined brightness and hue, and a first occupancy ratio indicating the proportion of the whole photographed image data is calculated for each of the divided regions, and the photographed image data Is divided into predetermined areas composed of a combination of the distance from the outer edge of the screen of the photographed image data and the brightness, and a second occupancy ratio indicating the proportion of the whole photographed image data is determined for each of the divided areas. Occupancy rate calculation function to calculate,
A deviation amount calculation function for calculating a deviation amount indicating a deviation in gradation distribution of the captured image data;
By multiplying the first occupancy ratio and the second occupancy ratio calculated by the occupancy ratio calculation function and the deviation amount calculated by the deviation amount calculation function by a coefficient set in advance according to the shooting condition. , An index calculation function for calculating an index for specifying shooting conditions,
A discriminating function for discriminating the photographing condition of the photographed image data based on the calculated index and a discriminant map preliminarily divided according to the accuracy of the photographing condition;
An adjustment method determining function for determining a method of gradation adjustment for the captured image data according to the determined shooting condition;
A gradation conversion function for performing gradation conversion processing on the captured image data using the determined gradation adjustment method;
An image processing program for realizing In the computer for executing image processing,
The photographed image data is divided into regions composed of a combination of predetermined brightness and hue, and a first occupancy ratio indicating the proportion of the whole photographed image data is calculated for each of the divided regions, and the photographed image data Is divided into predetermined areas composed of a combination of the distance from the outer edge of the screen of the photographed image data and the brightness, and a second occupancy ratio indicating the proportion of the whole photographed image data is determined for each of the divided areas. Occupancy rate calculation function to calculate,
A deviation amount calculation function for calculating a deviation amount indicating a deviation in gradation distribution of the captured image data;
By multiplying the first occupancy ratio and the second occupancy ratio calculated by the occupancy ratio calculation function and the deviation amount calculated by the deviation amount calculation function by a coefficient set in advance according to the shooting condition. , An index calculation function for calculating an index for specifying shooting conditions,
A discriminating function for discriminating the photographing condition of the photographed image data based on the calculated index and a discriminant map preliminarily divided according to the accuracy of the photographing condition;
An adjustment method determining function for determining a method of gradation adjustment for the captured image data according to the determined shooting condition;
An adjustment amount determination function for determining a gradation adjustment amount for the captured image data based on the calculated index;
A gradation conversion function for performing gradation conversion processing of the gradation adjustment amount determined by the adjustment amount determination function on the captured image data using the gradation adjustment method determined by the adjustment method determination function;
An image processing program for realizing Realizing the function of creating a two-dimensional histogram by calculating the cumulative number of pixels for each distance and brightness from the outer edge of the screen of the captured image data,
The image processing program according to claim 75 or 76, wherein the occupancy rate is calculated based on the created two-dimensional histogram when the occupancy rate calculation function is realized. Realizing the function of creating a two-dimensional histogram by calculating the cumulative number of pixels for each distance and brightness from the outer edge of the screen of the captured image data,
The image processing program according to claim 77 or 78, wherein the second occupation ratio is calculated based on the created two-dimensional histogram when the occupation ratio calculation function is realized. Realizing a function of creating a two-dimensional histogram by calculating the cumulative number of pixels for each predetermined hue and brightness of the captured image data;
The image processing program according to claim 73 or 74, wherein the occupancy ratio is calculated based on the created two-dimensional histogram when the occupancy ratio calculation function is realized. Realizing a function of creating a two-dimensional histogram by calculating the cumulative number of pixels for each predetermined hue and brightness of the captured image data;
The image processing program according to claim 77 or 78, wherein when the occupancy rate calculation function is realized, the first occupancy rate is calculated based on the created two-dimensional histogram.   73. When realizing the index calculation function, coefficients having different signs are used in a predetermined high-lightness skin color hue region and a hue region other than the high-lightness skin color hue region. 74. The image processing program according to any one of 74, 77, 78, and 80 to 82.   73, 74, 77, 78, wherein, when realizing the index calculation function, coefficients having different signs are used in an intermediate brightness area of a flesh hue area and a brightness area other than the intermediate brightness area. 80. The image processing program according to any one of 80 to 83.   84. The image processing program according to claim 83, wherein a brightness area of a hue area other than the high brightness skin color hue area is a predetermined high brightness area.   85. The image processing program according to claim 84, wherein the brightness area other than the intermediate brightness area is a brightness area within a flesh-color hue area.   86. The image processing program according to claim 83, wherein the skin color hue region of high brightness includes a region in the range of 170 to 224 in terms of brightness values of the HSV color system.   The image processing program according to claim 84 or 86, wherein the intermediate brightness area includes an area in the range of 85 to 169 in terms of brightness values of the HSV color system.   The image processing program according to any one of claims 83, 85, and 87, wherein the hue area other than the high brightness skin color hue area includes at least one of a blue hue area and a green hue area. .   The image processing program according to any one of claims 84, 86, and 88, wherein the brightness area other than the intermediate brightness area is a shadow area.   The hue value of the blue hue region is in the range of 161 to 250 as the hue value of the HSV color system, and the hue value of the green hue region is in the range of from 40 to 160 as the hue value of the HSV color system. 90. The image processing program according to claim 89, wherein:   The image processing program according to claim 90, wherein the brightness value of the shadow area is in the range of 26 to 84 as the brightness value of the HSV color system.   The image processing program according to any one of claims 83 to 92, wherein a hue value of the flesh color hue region is in a range of 0 to 39 and 330 to 359 as a hue value of the HSV color system. .   The image processing program according to any one of claims 83 to 93, wherein the skin color hue region is divided into two regions according to a predetermined conditional expression based on brightness and saturation.   The deviation amount includes at least one of the brightness deviation amount of the captured image data, the average brightness value of the captured image data at the center of the screen, and the brightness difference value calculated under different conditions. The image processing program according to any one of claims 73 to 94, wherein: The shooting conditions indicate light source conditions and exposure conditions during shooting,
96. The light source condition includes a strobe shooting state, and the exposure condition includes an under shooting state derived from a shutter speed and an aperture value at the time of shooting. The image processing program described in 1.

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