JP5225491B2 - Image processing apparatus and image processing method - Google Patents

Description

  The present invention relates to digital image processing, and more particularly to a technique for improving the brightness distribution of a digital image.

  In order to obtain an image with preferable brightness and contrast, a method is known in which gradation correction is performed by analyzing a histogram of a captured image and subject information. In particular, a so-called backlight scene in which the brightness of the main subject is significantly darker than the brightness of the background can be said to be a scene where gradation correction is effective because the main subject portion is inevitably dark in the captured image.

  In the gradation correction, there is a method using a correction table (tone curve) for converting each input luminance value into a predetermined output luminance value. In particular, in a backlight scene or the like, there has been proposed a method of setting a correction table that suppresses correction so that a bright background area is not overexposed while correcting the main subject to a preferable brightness (see Patent Document 1). ). In addition, a method has been proposed in which gradation correction is performed using a low-frequency component signal of a luminance component of an image to obtain an effect such as so-called dodging (see Patent Document 2). In this method, tone curve correction is performed. In comparison, tone correction can be performed while maintaining the contrast of the image.

JP 2007-124604 A JP 2008-072604

  However, as in Patent Document 1, when tone correction is performed so that dark portions of an image are brightly corrected by tone curves and correction is originally performed on bright portions, the contrast is reduced in a luminance band between the main subject and the background. Sometimes it was lost and it became a crisp image. Further, as described in Patent Document 2, when tone correction is performed using a low-frequency component signal of a luminance component of an image, an image may be unnatural because there is too much contrast depending on the scene. Even when both the correction method of Patent Document 1 and the correction method of Patent Document 2 are used, it is difficult to set a correction amount corresponding to a change in the shooting conditions of the camera and various user image quality preferences. .

The present invention is for solving the above-described problems, and an image processing apparatus according to the present invention captures information based on a face brightness value acquired by the acquisition means for acquiring face information of a captured image. Calculating means for calculating a target value for gradation correction of an image; extracting means for extracting a luminance component image and a low-frequency component image of the luminance component image from the photographed image; the luminance component image and the low-frequency component image; the brighter the first gradation correction processing means for performing a first gradation correction process to brighten the dark part with respect to the captured image, the dark part with respect to the captured image by the tone curve correction using a preparative A second gradation correction processing unit that performs the second gradation correction processing, a setting unit that sets a gradation correction level in accordance with a user operation input, and a target value calculated by the calculation unit . By the setting means Based on the constant has been corrected level, and having a determining means for determining an auxiliary Seiryo of the first correction amount and the second gradation correction processing of the tone correction processing.

  According to the present invention, it is possible to perform gradation correction using both gradation correction using a low-frequency luminance component and gradation correction by tone curve correction, and obtain a corrected image having a user-preferred image quality. The effect that it is possible can be obtained.

It is a block diagram which shows the example of 1 structure of the digital camera which can implement | achieve the image processing system by this invention. It is a flowchart which shows a brightness | luminance low frequency component detection process. It is a flowchart which shows a correction amount calculation process. It is a figure which shows the face luminance acquisition area | region of the detected face. It is a flowchart which shows calculation of the representative value of the brightness | luminance of a face. It is a figure which shows an example of the detected histogram. It is a figure which shows the relationship between a correction table and a lookup table. It is a flowchart which shows development processing. It is a flowchart which shows a correction curve creation process. It is a figure which shows the user interface for determining the correction amount of gradation correction. It is a conceptual diagram which shows the calculation method of the correction amount of tone curve correction. It is a flowchart which shows the calculation method of the correction amount of tone curve correction. It is a figure which shows the correction table for every ISO sensitivity.

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

(First embodiment)
FIG. 1 is a block diagram illustrating a configuration example of a digital camera capable of realizing the image processing apparatus of the present invention. In FIG. 1, a subject optical image that has passed through a photographing lens (not shown) is formed on an image sensor 101 and converted into electric charges corresponding to the amount of light. The image sensor 101 is covered with, for example, R (red), G (green), and B (blue) color filters. Each color filter has a spectral sensitivity around the wavelength band of each color, and a photoelectric conversion element provided corresponding to each color filter photoelectrically converts light in the band that has passed through each color filter. The electric charge converted by each photoelectric conversion element is output as an electric signal from the imaging element 101 to the A / D conversion unit 102 and converted into a digital signal (image data) by A / D conversion processing.

  The digital signal (input image data) output from the A / D conversion unit 102 is sent to each of the luminance low-frequency component detection unit 103, the correction amount calculation unit 105, and the WB processing unit 104. The WB processing unit 104 adds the white balance gain values obtained by the WB detection unit 106 to the RGB pixel values of the image. The image data subjected to WB processing by the WB processing unit 104 is sent to the development processing unit 110, and the development processing unit 110 performs luminance correction processing (first gradation correction processing) and tone curve correction using luminance low-frequency components described later. Processing (second gradation correction processing) is performed. The image data output unit 111 outputs the image data that has undergone development processing as a file. For example, when the file format is converted to a JPEG file, the image data is converted into a JPEG file format by three-dimensional matrix conversion into YCrCb format and attached data.

Next, details of the processing of each block will be described. FIG. 2 is a flowchart showing processing performed by the luminance low-frequency component detection unit 103. In FIG. 2, first, in step S201, luminance signal extraction processing is performed on input image data. For example, when an image to be color-adjusted is expressed in the sRGB color space described in IEC 61966-2-1, the luminance component is extracted according to the method described in IEC 61966-2-1. That is, conversion into CIE1931XYZ is performed by gamma conversion and 3 × 3 matrix calculation. Here, XYZ data obtained by converting the pixel value (R (x, y), G (x, y), B (x, y)) at the position (x, y) by the above-described conversion into X (x , Y), Y (x, y), and Z (x, y). In this case, Y (x, y) is a luminance component extracted, and X (x, y) and Z (x, y) are color components. In the present embodiment, since the pixel value of the image is defined in the sRGB color space and the luminance is defined in the sYCC color space, the luminance component is calculated using the conversion formula (1) below.
Y = 0.299 * R + 0.587 * G + 0.114 * B Formula (1)
On the other hand, an approximate expression such as the following expression (2) may be used.

  Although an equal-magnification luminance component image can be acquired by the above processing, the sizes of the original image and the luminance component image do not need to match. For example, in the luminance component extraction in step S201, the input image data may be reduced. The reduction process may be any known method, but can be easily realized by, for example, a thinning process, a nearest neighbor method, an average value method, or the like.

  In subsequent step S202, low frequency component extraction processing is performed from the luminance component image created in step S201, and a luminance low frequency component image is generated. In the present embodiment, low-pass filter processing is performed as low-frequency component extraction. In this embodiment, three low-frequency component images are generated using three low-pass filters having different filter sizes in this step.

  FIG. 3 is a flowchart showing processing performed by the correction amount calculation unit 105. In FIG. 3, in step S301, WB detection processing is performed. Here, the WB detection unit 106 calculates a white balance gain value suitable for the shooting scene from the input image data.

  In subsequent step S302, histogram detection processing is performed. Here, the histogram detection unit 107 first applies a predetermined WB gain to the entire captured image data, and performs gamma processing on the applied data. Then, a histogram of the image data subjected to gamma processing is detected. In this embodiment, a method using a lookup table is applied to the gamma processing. Here, in this embodiment, the range in which the histogram is detected is the entire image data, but it may be detected from the end cut.

  In subsequent step S303, face detection pre-processing is performed. Here, the face detection unit 108 performs reduction processing, gamma processing, and the like on the input image data so that a face whose face is included in the image can be easily detected. In subsequent step S304, face detection processing is performed. Here, the face detection unit 108 detects a face area in the input image data. This detection processing includes texture detection processing for input image data and pattern recognition processing (recognition processing for regions such as eyes, nose, mouth, and face outline) for the result. Then, using a preset evaluation threshold value, the reliability of the face is evaluated for the area obtained by these processes.

  In subsequent step S305, the face detection unit 108 determines the presence or absence of a face based on the evaluation result of the face detection process in step S304. When there is one or more regions where the reliability of being a face is greater than the evaluation threshold, the face detection unit 108 determines that the region is a face. Then, the coordinates of the eyes included in the area are output, and the process proceeds to the step of face luminance calculation processing after step S306. If it is determined that there is no face area, the process proceeds to step S309.

  In step S306, the face luminance acquisition area is calculated. Here, the correction amount calculation unit 109 calculates a region for acquiring the face luminance based on the face detection result. For example, as shown in FIG. 4, in the entire range 401 of the image data, for each of the face detection areas 402 and 412, three areas under both eyes and between them, that is, areas 403, 404, 405, and area 413. 414, 415 are calculated. Here, the size of each region is a square region having a size determined by the ratio to the size of the face detection region 402 (412). In subsequent step S307, the correction amount calculation unit 109 obtains an average value of each of the R pixel, the G pixel, and the B pixel of the input image data for each face luminance acquisition region, and converts it into the luminance value Y by Expression (1). I do. For this conversion, an approximate expression such as Expression (2) may be used.

  In the subsequent step S308, the representative value of the brightness of the face is calculated. An example of this method is shown in the flowchart of FIG. First, in step S501, the maximum value is obtained from the three luminance values for each face. In subsequent step S502, it is determined whether there are a plurality of faces. If there are a plurality of faces, the process proceeds to step S503. If there is only one face, the maximum value of the brightness value obtained in step S501 for this face is set as the representative value of the face brightness (step S509). In the example of FIG. 4, since there are two faces (402, 412), the representative value Y0 is obtained for the areas 403, 404, and 405 of the face detection area 402, and Y1 is obtained for the areas 413, 414, and 415 of the face detection area 412. Is calculated.

  In step S503, a maximum value (Ya) of luminance values of a plurality of faces is obtained. In the example of FIG. 4, the larger one of Y0 and Y1 is Ya. In step S504, an average value (Yb) of luminance values of a plurality of faces is obtained. In the example of FIG. 4, the average value of the representative value Y0 for the face detection area 402 and the representative value Y1 for the face detection area 412 is obtained. In step S505, a weighted average value (Yc) obtained by applying a predetermined weight to the maximum face brightness value (Ya) and the average face brightness value (Yb) is obtained.

  In step S506, it is determined whether or not the difference between the maximum facial brightness value (Ya) and the weighted average value (Yc) is smaller than a predetermined threshold (Yth). If this difference is smaller than the threshold value, the weighted average value (Yc) is set as the representative value of the face luminance (step S507). Otherwise, the threshold value (Yth) is calculated from the maximum value (Ya) of the face luminance. The subtracted value is set as the representative value of the brightness of the face (step S508). By determining the representative value in this way, it is possible to correct the brightness fairly for a plurality of faces, but even when only one bright face is included by correction, it is possible to correct the face with reference to that face. It becomes possible, and failure photography can be reduced surely.

  Returning to FIG. 3, in step S <b> 309 corresponding to the case where no face is detected, the correction amount calculation unit 109 detects the feature amount of the histogram obtained by the histogram detection unit 107. Here, as shown in FIG. 6, in the histogram, the level (SD) to which a pixel with a cumulative frequency of 1% belongs from the dark side, the level (HL) to which a pixel with a cumulative frequency of 1% belongs from the highlight side, and the like. Ask.

  In the subsequent step S310, a correction target value is calculated. Various methods can be considered for calculating the target luminance level. In this embodiment, a method of generating a lookup table for the target luminance level using a correction table is adopted. That is, as shown in FIG. 7, a correction table that defines a target luminance level with respect to a representative value of the luminance of the face is held in advance in a memory (not shown). Then, by referring to this table, target values corresponding to three LSBs are obtained from the representative values of the face brightness, and the output brightness with respect to the input brightness level is determined by spline interpolation from these values and the minimum and maximum brightness values of the image. Create a level lookup table.

  FIG. 7 shows an example of creation when there is a face. Similarly, when there is no face, the correction table corresponding to the SD and HL values of the histogram obtained in step S309 is used similarly. A lookup table can be created.

  In the subsequent step S311, the correction amount of the correction using the luminance low frequency component and the correction using the tone curve is calculated, and the result is passed to the development processing unit 110, whereby the processing of the correction amount calculation unit 105 ends. The process in step S311 will be described in detail later.

  Details of the tone correction processing (first tone correction processing and second tone correction processing) of the development processing unit 110 will be described with reference to the flowchart of FIG. In step S801 in FIG. 8, luminance correction processing using a luminance low-frequency component is performed.

  This correction process is performed in the same manner as in Patent Document 2. That is, logarithmic transformation of the scaled luminance component distribution is performed, an average value at a different scale (different resolution) is obtained, a difference from the logarithmic transformation of the original luminance component is output, and the original is obtained by inverse transformation (exp calculation). The process of returning to the luminance unit is performed. Here, in order to adjust the degree of improvement according to the image, the logarithm conversion output of the scaled luminance component is multiplied by a coefficient. This coefficient is a parameter for adjusting the degree of improvement. The output of the improved luminance component based on the processing described above is expressed by the following equation (3).

  However, Y ′ (x, y), Fn (x, y), and n are the output of the improved luminance component with the coordinate value (x, y), the Gaussian function and the scale at the coordinate (x, y), respectively. It is a parameter to represent. Further, γ0 and γ1 are a parameter 0 indicating the degree of improvement and a parameter 1 indicating the degree of improvement. * Represents a product-sum operation, and Avg represents an average value operation.

  When the luminance conversion is configured by hardware, it can be configured by, for example, an average value calculation circuit, a circuit for creating a lookup table, a table storage unit, a table reference circuit (gamma conversion part), and a division circuit. The average value calculation circuit may be provided in a portion that realizes the low-frequency luminance signal extraction.

  As will be described later, the intensity of the luminance correction processing using the luminance low frequency component is represented by a look-up table constituting the curve 1102 in FIG. The parameter γ0 representing the degree of improvement and the parameter γ1 representing the degree of improvement in the above equation (3) are determined by the values in this lookup table.

  In the subsequent step S802, a color adjustment process associated with the brightness correction process using the brightness low frequency component is performed. In the color adjustment process, the color component is corrected according to the change in the luminance component so that the color of the processed image data does not change as much as possible. Preferably, for example, the color components X (x, y) and Z (x, y) are respectively multiplied by the ratio Y ′ (x, y) / Y (x, y) before and after the change of the luminance component. Alternatively, only Y (x, y) is changed to Y ′ (x, y), and the processing is simplified such that the processing is not performed on the color components X (x, y) and Z (x, y). Is easy.

  In the subsequent step S803, luminance correction processing using a tone curve is performed. For this, a look-up table of output luminance data for each input luminance is used. In the subsequent step S804, color adjustment processing accompanying luminance correction processing using a tone curve is performed. This may be performed in the same manner as in step S802. In addition, step S802 and step S804 may be combined, and color adjustment processing may be performed last according to changes in luminance values by luminance correction processing using a low-frequency luminance component and correction processing using a tone curve.

  Next, details of the correction amount calculation processing in step S311 of FIG. 3 will be described. A flowchart of this calculation process is shown in FIG. In step S901 in FIG. 9, a correction amount for correction using the luminance low-frequency component image is calculated. In the present embodiment, three luminance low frequency component images having different frequency bands generated by the luminance low frequency component detection unit 103 are used. Further, pixel values after correction using the plurality of luminance low-frequency component images are calculated, and these are weighted and added to obtain a final corrected image.

  The luminance low-frequency component pixel Fn (x, y) * Y (x, y) having the image data described in Expression (3) will be described as Ln (x, y) hereinafter. In this embodiment, among the three luminance low-frequency component images, the highest frequency component is LH (x, y), the lowest frequency component is LL (x, y), and the remaining intermediate frequency components. Is LM (x, y).

  As will be apparent from Equation (4) described later, the correction processing in this step is not limited to the luminance value Y (x, y) of the target pixel, but also the luminance low frequency components LH (x, y) and LM (x, y The corrected pixel value is determined only when y) and LL (x, y) are present. However, since the target value of the correction amount obtained in step S310 is a target value for only the luminance value Y (x, y) of the target pixel, correction using only the luminance value Y (x, y) of the target pixel. That is, the correction amount is calculated by approximating the correction by the tone curve.

  In this embodiment, the user can set a correction level for correction using a low-frequency luminance component before shooting. FIG. 10 shows an example of the user interface, and a camera CPU (not shown) controls the operation. On the setting screen displayed on the liquid crystal panel included in the camera, “strong”, “standard”, “weak”, and “no” are displayed as correction level selection items. A user operates a predetermined operation member to select an item. When an operation input for selecting any item is made, a correction table corresponding to the selected item is read from a memory (not shown) in response to the selection operation. If “No” is selected, the correction ratio using the low-frequency luminance component is “0”.

  After shooting is started, a correction correction amount lookup table using luminance low-frequency components (curve in FIG. 11) is obtained from the relationship between the read correction table and the correction target value lookup table determined from the captured image. 1102) is generated. Since the correction table corresponding to each item determines the absolute amount of correction, the value of this lookup table may exceed the correction amount of the target value. In such a case, the correction amount calculation unit 109 adjusts the lookup table so that the correction amount of the target value becomes the correction amount of correction using the low-frequency luminance component.

  In the present embodiment, the absolute amount of correction is determined based on a user operation, but it is possible to set the ratio of the correction amount using the low-frequency luminance component to the target value of the entire correction instead of the absolute amount. It may be. Also, when setting this absolute amount or ratio, if it is determined not only by a user operation but also as a result of face detection that there is a face, a value larger than the originally set ratio should be set. It may be. In this way, it is possible to perform correction so that the contrast of the face portion is not impaired without taking time and effort for the user to determine whether or not the face is present and adjust and photograph again.

  In subsequent step S902, the correction amount calculation unit 109 calculates the correction amount using the tone curve. Here, the correction amount using the tone curve is calculated so that the correction using the low-frequency luminance component obtained previously and the correction using the tone curve are combined to obtain the target value of the correction amount obtained previously. Since the correction using the low-frequency luminance component uses the low-frequency luminance components LH (x, y), LM (x, y), and LL (x, y), correction of pixels having the same luminance level as the correction result The previous luminance value varies. Therefore, a correction amount for tone curve correction is calculated by approximating correction using only the luminance value Y (x, y) of the target pixel, that is, correction using a tone curve.

  To obtain the correction amount for tone curve correction, that is, the output value for a certain input value, obtain the input value for correction using the low-frequency luminance component for which the output value for correction using the low-frequency luminance component is this input value. The target value of the correction amount for this input value may be calculated. FIG. 11 shows an example of the calculation. In FIG. 11, reference numeral 1101 denotes a curve indicating a target value for correction, and 1102 denotes a curve indicating a correction amount using a low-frequency luminance component, each of which includes a discrete look-up table having output luminance value data for the input luminance value. Is done.

  The tone curve correction look-up table shows that when the “output value (β) of correction using a low-frequency luminance component for the input value (α)” is the input value (β), the “correction amount for the input value (α)” Of the target value (γ) ”of the output value (γ). In FIG. 11, γ1 corresponding to the values α1 and β1 and γ2 corresponding to the values α2 and β2 respectively constitute a look-up table for tone curve correction. Here, the correction and correction amount target values using the low-frequency luminance component are look-up tables having discrete values, so that each value is calculated by interpolating data by linear interpolation.

  A flowchart of this process is shown in FIG. In step S1201 of FIG. 12, first, the input luminance value of the tone curve correction and the input luminance value of the correction lookup table using the low-frequency luminance component are initialized to the minimum luminance value (for example, 0) that the image can take.

  In subsequent step S1202, the input luminance value for tone curve correction is compared with the output luminance value for the input luminance value for correction using the luminance low frequency component. If the former is larger (No in step S1202), the correction input luminance value using the luminance low frequency component is replaced with the next luminance value, and the process proceeds to step S1202 (step S1204).

  If the latter is larger or the former latter is the same (Yes in step S1202), the output luminance value Y [i] for tone curve correction is determined by the following equation (4) using linear interpolation (step S1202). S1203).

  Here, i is an input luminance value for tone curve correction, and j is an input luminance value for correction using a low-frequency luminance component. Y1 [i] is a target luminance value for correction with respect to the input luminance value i, and Y2 [i] is an output luminance value for correction using a luminance low-frequency component with respect to the input luminance value i.

  In subsequent step S1205, it is determined whether or not the input luminance value of tone curve correction has been completed up to the maximum luminance value (for example, 255) that the image can take. If it is not the maximum luminance value, in step S1206, the input luminance value for tone curve correction is replaced with the next luminance value, and the process proceeds to step S1202. If the luminance value is the maximum luminance value, the process ends. With the above processing, a lookup table for tone curve correction can be created.

  In this embodiment, first, the correction amount of the correction using the low-frequency luminance component is determined, and the correction amount of the tone curve correction is calculated so that the remaining correction amount with respect to the correction amount of the target value is corrected by the tone curve correction. . However, the present invention is not limited to this. For example, the correction amount of the tone curve correction is first determined, and the remaining correction amount with respect to the correction amount of the target value is corrected using the luminance low-frequency component. A correction amount of correction using the low frequency component may be calculated. Also in this case, if the correction using the luminance low frequency component is approximated to the correction using only the luminance value Y (x, y) of the target pixel, the correction using the luminance low frequency component and the tone curve correction are equivalent. Since it can be regarded as a process, the same process as in this embodiment may be performed.

  As described above, according to the present embodiment, when performing gradation correction of a captured image, information on the main subject and information on the histogram of the captured image are acquired from the captured image, and the level of the captured image is based on these information. The target value for tone correction was calculated. Then, the respective correction amounts of the correction using the luminance low frequency component and the tone correction by the tone curve correction are calculated, and the tone correction of the image is performed by the correction using the luminance low frequency component and the tone curve correction. . By performing such correction, an image correction result with good brightness and contrast can be obtained.

  In addition, the correction strength using the low-frequency luminance component can be determined by the user's operation. As a result, the correction amount using the low-frequency luminance component and the correction amount for tone curve correction can be easily determined according to the user's image quality preference related to contrast strength.

(Second Embodiment)
In the first embodiment, the correction target value is determined from the information of the main subject of the captured image or the histogram of the captured image, and the influence on the image quality due to the shooting conditions of the camera is taken into consideration for the determination of the correction target value. It wasn't.

  In the present embodiment, a correction target value is set according to the ISO sensitivity setting as an example of the shooting condition. The flow for determining the correction target value is the same as that in the first embodiment. However, the present embodiment is different in that the correction table shown in FIG. 7 of the first embodiment is provided for each ISO sensitivity.

  An example is shown in FIG. The correction tables are different for ISO sensitivity settings of 200, 400, and 800, respectively. The ISO sensitivity is set by user settings before shooting, and at the time of shooting, a table corresponding to the set ISO sensitivity is read, and interpolation processing similar to that shown in FIG. A value lookup table is created.

  Thus, by having a plurality of correction tables according to the ISO sensitivity, it is possible to determine a more appropriate correction target value in consideration of the influence on the image quality due to shooting at each ISO sensitivity.

Claims (6)

Acquisition means for acquiring face information of the captured image;
Calculating means for calculating a target value for gradation correction of the photographed image based on the brightness value of the face acquired by the acquiring means;
Extraction means for extracting a luminance component image and a low-frequency component image of the luminance component image from the captured image;
First gradation correction processing means for performing first gradation correction processing for brightening a dark portion of the captured image using the luminance component image and the low-frequency component image;
Second tone correction processing means for performing second tone correction processing for brightening a dark portion of the captured image by tone curve correction;
Setting means for setting a gradation correction level according to a user operation input;
So that the target value calculated by the calculation means, based on the tone correction level set by said setting means, said first gradation correction processing correction amount and the second tone correction process and determining means for determining the complement Seiryo,
An image processing apparatus comprising:   When the acquisition unit acquires face information, the determination unit increases the ratio of the correction amount of the first gradation correction process as compared with a case where face information is not acquired. The image processing apparatus according to claim 1.   The image processing apparatus according to claim 1, wherein the calculation unit calculates a target value for the gradation correction according to an ISO sensitivity in photographing the photographed image. The determining means obtains the amount obtained by subtracting one of the correction values of the first gradation correction process and the second gradation correction process from the target value, and the first gradation correction process and the first gradation correction process . claims 1, characterized in that the other correction amounts of the gradation correction processing 2 to the image processing apparatus according to any one of 3. 5. The image according to claim 1, wherein when the acquisition unit does not acquire face information, the calculation unit calculates the target value based on information of a histogram of the captured image. 6. Processing equipment. An acquisition step of acquiring face information of the captured image;
A calculation step of calculating a target value for gradation correction of the captured image based on the luminance value of the face acquired by the acquisition step;
An extraction step of extracting a luminance component image and a low-frequency component image of the luminance component image from the captured image;
A first gradation correction processing step of performing a first gradation correction process for brightening a dark portion of the captured image using the luminance component image and the low-frequency component image;
A second gradation correction processing step of performing a second gradation correction process for brightening a dark portion of the captured image by tone curve correction;
A setting step for setting a gradation correction level according to a user operation input;
So that the target value calculated by the calculating step, on the basis of the correction level set by the setting step, the first gradation correction processing correction and compensation of the second tone correction process a determination step of determining the amount,
An image processing method comprising: