JP2005159650A - Image processor, image processing method, storing medium and program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To set the gradation correcting conditions in an output unit to satisfactorily reproduce the gradation characteristics of a taken image and set the gradation characteristics according to statistic values of the brightness components expressing features of the image, thereby exactly reproducing the brightness characteristics of the image. <P>SOLUTION: The image processor processes an image obtained by photographing an object using a photographic apparatus, and outputs the image using an output unit. It comprises a means for generating a gradation conversion table showing the relation of the brightness of the image to the density of an output image outputted by the output unit, and a means for correcting the image, based on the gradation conversion table. The generating means generates the gradation conversion table so that the brightness (X1) of the image of a part of the object imaged in its specified region corresponds to the density (Y1) of the output image outputted from the image in the specified region, using the output unit. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

  The present invention relates to a method for generating gradation conversion conditions according to an image.

  The range of brightness that can be photographed with a digital camera is different from the range of brightness that can be printed with a printer, and it is generally known that the range of brightness that can be photographed with a digital camera is wider. Yes. Therefore, an image photographed with a digital camera is printed after being compressed within a brightness range that can be expressed by a printer. The gradation characteristics (hereinafter referred to as “total gradation characteristics”) representing the overall relationship between input and output at this time usually draws an S-curve as shown by the curve (a) in FIG.

  Here, the overall gradation characteristics will be described. The curve (a) in FIG. 1 is a gradation characteristic obtained by simply combining the gradation characteristics of the digital camera and the printer, and the curve (b) in FIG. 1 and the curve (c) in FIG. The gradation characteristics are shown respectively. In general, the gradation that is preferred by the user varies depending on the scene (subject) such as a person or landscape, so that the total gradation that is optimized also varies from scene to scene. In the case of the example in FIG. 1, the curve (b) is the overall gradation optimized for the person scene, and the curve (c) is optimized for the landscape scene. Then, the image acquired by the digital camera is converted and output along the overall gradation characteristic shown by the curve (b) in FIG. 1 or the curve (c) in FIG.

As an image processing technique involving such gradation conversion, for example, Japanese Patent Laid-Open No. 2002-16875 can be cited. According to the publication, a gradation conversion table is prepared for each type of cloudy sky, backlight scene, close-up strobe, etc., and the gradation is converted after absorbing differences in the camera model. can do.
JP 2002-16875 A

  However, in the case of the invention disclosed in Japanese Patent Laid-Open No. 2002-16875, the image is subjected to gradation conversion based on the reference gradation conversion table, so that the brightness of the main subject in the image is kept constant. There is a problem that it cannot be kept. For example, when the captured image is converted according to a fixed shape characteristic as shown in the curve (b) in FIG. 1 or the curve (c) in FIG. The brightness is made brighter or darker than necessary, and the print with the exposure intended by the photographer cannot be obtained. In particular, as in the example shown in FIG. 2, when conversion is performed in a system having a strong overall gradation characteristic, the result is that the latitude of the digital camera is narrowed, and the gradation of the main subject is skipped. Or there is a risk that it will be changed to a failed photo that is crushed.

  The present invention has been made in view of the above problems, and an object of the present invention is to enable the output device to set gradation correction conditions so that the gradation characteristics of a photographed image can be reproduced satisfactorily. It is another object of the present invention to appropriately reproduce the brightness characteristics of an image by setting gradation characteristics according to the statistical value of the brightness component indicating the characteristics of the image.

In order to achieve the above object, an image processing method according to the present invention comprises the following arrangement. That is,
An image processing method for processing image data obtained by photographing a subject with a photographing device and generating image data for output using an output device,
A generation step of generating a gradation conversion condition for converting a brightness component of the image data into a density output by the output device;
A correction step of correcting the image based on the gradation conversion condition,
The generating step includes
A statistical value calculating step for obtaining a statistical value related to a brightness component of the image data;
A first control point setting step of setting a first control point of the gradation conversion condition so that the brightness of the statistical value is reproduced by the output device;
A second control point setting step for setting a second control point set according to the brightness range of the image and the density range of the output device;
And a generation step of generating the gradation conversion condition based on the first control point and the second control point.

  According to the present invention, it is possible to set the gradation correction condition in the output device so that the gradation characteristic of the photographed image can be reproduced well. In addition, by setting the gradation characteristic according to the statistical value of the brightness component indicating the feature of the image, it becomes possible to appropriately reproduce the brightness characteristic of the image.

[First embodiment]
As a first embodiment, a case where an image photographed by a digital camera is printed out by a printer will be described. In addition, as a printer that performs print output, a generally popular inkjet printer or the like is assumed.

  FIG. 3 is a diagram showing the configuration of an image processing apparatus common to the embodiments of the present invention. When an image is printed out using the image processing apparatus 300, a print output request is made from the application 301 to the OS 302, a graphics portion is a graphics drawing command, and an image image portion is a drawing indicating an output image composed of an image drawing command. An instruction group is issued to the OS 302. The OS 302 receives an application print output request and issues a drawing command group to the printer driver 303 corresponding to the printer 305. The printer driver 303 processes a print output request and a drawing command group input from the OS 302, creates print data that can be printed by the printer 305, and transfers the print data to the printer 305. When the printer 305 is a raster printer, the printer driver 303 sequentially performs image correction processing on the rendering command group from the OS 302, sequentially rasterizes it into the RGB 24-bit page memory, and rasterizes all the rendering command groups. The contents of the RGB 24-bit page memory are converted into a data format printable by the printer 305, for example, CMYK data, and transferred to the printer 305.

  Next, processing performed by the printer driver 303 will be described with reference to FIG.

  The image correction processing unit 401 performs image correction processing to obtain a print (output image) that suits the user's preference for the RGB color information (RGB 8-bit images) included in the drawing command group input from the OS 302. I do. Details of this image correction processing will be described later.

  First, the printer correction processing unit 402 rasterizes the RGB color information subjected to the image correction processing, generates a raster image on the RGB 24-bit page memory, performs color reproduction space mapping processing, color separation processing into CMYK, and tone correction processing. The CMYK data depending on the color reproducibility of the printer is generated for each pixel, and transferred to the printer 305 as print data.

  Hereinafter, processing in the image correction processing unit 401 illustrated in FIG. 4 will be described in detail.

  FIG. 5 is a diagram illustrating details of processing of the image correction processing unit 401. First, in step S501, it is determined whether or not a person's face is included in the RGB color information (RGB 8-bit images) included in the drawing command group input from the OS 302. If at least one face area is detected in the image, the average brightness in the face area detected in step S504 is obtained. If not detected, the average brightness of the entire image is obtained in step S505.

  Next, in step S505, a gradation conversion table for converting an image to a gradation according to the user's preference is created. At this time, the gradation conversion table is created so as not to change the average brightness obtained in step S504 or step S505. Using this gradation conversion table, image conversion is performed in step S506. Hereinafter, processing in each step will be described in detail.

<Details of Face Detection Processing (Step S501)>
FIG. 6 shows details of the face detection process. This shows in detail the processing of step S501 in FIG.

  In step S601, an area where each R, G, B value is smaller than the threshold value T is locally marked based on the RGB value of the input image.

  In step S602, the regions marked in step S601 are grouped two by two, and it is determined whether or not the two groups are eyes from the uniformity of the size of the regions, the difference in luminance, the angle with respect to the horizontal, etc. (FIG. 7 (a)).

  In step S603, for the group determined to be an eye, a rectangular area centering on the two is set. Then, the edge near the boundary of the region and the RGB value in the region are determined. The edge determines whether there is a face outline. As for the RGB values, it is determined whether or not the average value in the rectangular area is within a preset skin color area. Then, the face area is determined. The face area is given by the rectangular area (FIGS. 7B and 7C).

  In step S604, mask data for masking the determined face area is created and stored in the RAM 309 on the PC. Here, the mask data is given as a binary image in which the face area is 1 and the other areas are 0. An example of the created mask data is shown in FIG.

<Details of Average Brightness Calculation Processing for Face Area (Step S503)>
First, the mask data created in step S501 is extracted. Next, in the area where the mask data takes a value of 1, the RGB value at each pixel of the input image is converted to the coordinate value in the CIEL * a * b * color system, and the average value and the standard value of only the L * value are converted. Calculate the deviation. At this time, in order to calculate the average brightness of only the skin color excluding the hair and eyes, the average L * may be calculated using only pixels having a * value and b * value within a certain range.

<Details of Average Brightness Calculation Processing of Whole Image (Step S504)>
Similar to step S503, the average brightness and standard deviation are calculated for the entire area of the input image.

<Details of Tone Conversion Table Creation Processing (Step S505)>
FIG. 9 is a diagram for explaining the gradation conversion table creation processing. In FIG. 9, the target characteristic (1) is a target overall gradation characteristic, and the brightness (relative value) of a scene (subject) photographed with a digital camera and an image obtained by photographing are printed. It represents the relationship with the concentration of. This target characteristic (1) is adaptively set for each image by a method described later.

  The digital camera characteristic (2) represents the relationship (output characteristic) between the relative luminance of the scene and the output value (RGB average value) of the digital camera. As the characteristics of the digital camera, for example, average characteristics of a commercially available digital camera such as a characteristic of γ = 0.45 are stored in the HD 307 in advance. In addition, when the model of the digital camera photographed can be determined based on the tag information of the image and the characteristics of the model are stored in the HD 307 in advance, the characteristics of the corresponding digital camera are used based on the determination result. You may make it do.

  The printer characteristic (4) represents the density (output characteristic) of a print output when an RGB value (R = G = B) is input to the printer to be printed, and is stored in advance in the HD 307. And The gradation conversion table (3) is a conversion table for converting an image in order to obtain a print having the target characteristic (1). The digital camera output value (RGB average value) and the printer input value (RGB value). , R = G = B).

  When the target characteristic (1) is set, the gradation conversion table (3) is inevitably determined from the digital camera characteristic (2) and the printer characteristic (4). First, as shown in step 902 in FIG. 9, the input value (relative luminance of the scene) of the digital camera corresponding to the RGB value as the digital camera output is obtained using the digital camera characteristic (2). Next, the printer output density value (print density value) is obtained from the input value of the digital camera using the target characteristic (1) (step 902 in FIG. 9). Finally, a printer input value (RGB value) corresponding to the printer output density is obtained using the printer characteristic (4) (step 903 in FIG. 9), and gradation is obtained by taking correspondence with the RGB value as the digital camera output. A translation table is created.

  Next, a method for setting the target characteristic (1) will be described with reference to FIGS. Here, FIG. 10 corresponds to the target characteristic (1) in FIG. 11 explains the flow of the target characteristic setting method shown in FIG. 10, and FIG. 12 explains the flow of each step in FIG. 11 in more detail.

  First, in step S1101 in FIG. 11, a point A in FIG. 10 is obtained. First, the RGB value (R = G = B) corresponding to the average brightness obtained by the average brightness calculation process (step S503) of the face area of the image shown in FIG. 5 or the average brightness calculation process of the entire image (step S504). The relative luminance of the scene corresponding to this RGB value is obtained from the digital camera characteristic (2) in FIG. The relative luminance of this scene is set as the X coordinate X1 of the point A (step S1201 in FIG. 12A). Next, the density of the print output when the RGB value corresponding to the average brightness is input to the printer is obtained and set as the Y coordinate Y1 of the point A (step S1202 in FIG. 12A). That is, in this process, the initial value of the gradation conversion table shown in (3) of FIG. 9 is set to linear (no conversion), and the point on the target characteristic of (1) of FIG. 9 corresponding to the average brightness is obtained. Is equivalent to

  Next, in step S1102 of FIG. 11, points B1 and B2 in FIG. 10 are obtained. First, a straight line L passing through the point A and having an optimum inclination (tan θ in FIG. 10) for each scene is obtained (steps S1203 and 1204 in FIG. 12B). In this embodiment, the optimum inclination for a scene is a value determined in advance for each person and landscape scene. For example, the inclination of a person scene (when a face area is detected in step S501 in FIG. 5). Is 1.2, and the inclination of the landscape scene (when no face area is detected in step S501 in FIG. 5) is 1.6. Then, as shown in steps S1205 and S1206 of FIG. 12C, ΔX is a standard deviation with respect to the average brightness, for example, a value obtained by adding ΔX to X1 is X2, a value obtained by subtracting ΔX from X1 is X3, and a straight line L The upper points B1 (X2, Y2) and B2 (X3, Y3) are obtained.

  Next, the maximum value X4 of the relative luminance of the scene (the relative luminance of the scene where the output value of the digital camera is R = G = B = 255 in the digital camera characteristic (2) in FIG. 9) and the minimum density Y4 that the printer can output. The point C1 (X4, Y4) consisting of the above, the minimum value X5 of the relative luminance of the scene (the relative luminance of the scene where the output value of the digital camera is R = G = B = 0 in the digital camera characteristic (2) in FIG. 9) And a point C2 (X5, Y5) consisting of the maximum density Y5 that can be output by the printer. That is, point C1 and point C2 are set according to the relative luminance range of the image and the density range of the printer (step S1104 in FIG. 11).

  Finally, the control points C1, B1, A, B2, and C2 are interpolated by a spline curve or the like to obtain target characteristics (step S1105 in FIG. 11).

  In this way, a print having a contrast suitable for the scene can be obtained by setting the target characteristics according to a plurality of control points determined according to the statistical value, the luminance range of the image, and the density range reproducible by the output device. Can be obtained. Then, by making the statistical value the statistical value of the subject that is the center, it is possible to appropriately reproduce the contrast of the subject.

<Details of Tone Conversion Process (Step S506)>
FIG. 13 is a diagram showing a detailed block configuration of the gradation conversion process (step S506). In order to convert only the brightness (contrast) without changing the color of the input image, first, each RGB value of the color information is the same table using the conversion table created in step S505 in FIG. Are converted into L * a * b * values (CIEL * a * b * color system) (1301 and 1303). Next, the L * value obtained by the processing of the L * a * b conversion unit 1303 and the a * and b * values obtained by the processing of the L * a * b conversion unit 1301 are inversely converted into RGB values (1304). ). Also, here, the color information is converted by converting the color information into L * a * b * values and replacing only the L * value that is the lightness component. However, the present invention is not limited to this, and is input. It is also possible to use a value obtained by table-converting RGB values of color information as it is, or to convert only luminance information (Y value) in another color space such as YCbCr.

  As is apparent from the above description, according to the present embodiment, the face area is automatically recognized, and the print contrast is determined according to the result, so that the brightness of the skin color is not changed in the portrait. In addition, in a non-person photograph, a high-quality print having a contrast suitable for each subject can be automatically obtained without changing the brightness of the entire image.

[Second Embodiment]
As a second embodiment, a case where a user interface (UI) is incorporated in the image correction processing unit 401 will be described. The present embodiment is characterized in that the user has a function of selecting an arbitrary area and adjusting the contrast centered on the average brightness of the area. Since the configuration and the data flow in the present embodiment are the same as those in the first embodiment, description thereof is omitted here, and only the processing in the image correction processing unit 401 is described in detail below.

  FIG. 14 shows the UI of the image correction processing unit 401 in the second embodiment, and FIG. 15 shows the flow of processing. In FIG. 14, an image display unit 1401 is a part that displays a preview of an image to be printed. The selection area 1402 is a rectangular area designated by the user. This area can be arbitrarily designated by the user using an input device such as a mouse (not shown). The data display unit 1403 is a part for displaying the target characteristic, and for example, the characteristic as shown in FIG. 10 is displayed. The data display portions 1404 to 1406 are portions for displaying the X coordinate, the Y coordinate, and the inclination θ at the A point, which are parameters of the characteristics in FIG. The data display sections 1403 to 1406 can be input by the user. For example, the user can arbitrarily move the point A, the point B1, and the point B2 shown in FIG. 10 with respect to the target characteristic displayed on the data display unit 1403 by an input device such as a mouse (not shown). In the data display units 1404 and 1406, the user can set an arbitrary value using an input device such as a keyboard (not shown). However, when any one of the data display units 1403 to 1406 is updated by the user, the values of the other data display units are also updated in real time accordingly. Buttons 1407 to 1410 are buttons for the user to execute specific processing, and when each button is clicked with an input device such as a mouse (not shown), specific processing corresponding to the button is performed. This process will be described later.

  Next, a processing flow of the image correction processing unit 401 in the second embodiment will be described with reference to FIG. First, in step S1501, the UI shown in FIG. At this time, an image before gradation conversion (hereinafter referred to as an original image) is displayed on the image display unit 1401 in FIG. The data display unit 1403 displays a comprehensive gradation characteristic (hereinafter referred to as a default target characteristic) when the digital camera and the printer are used in combination. At this time, points A, B1, and B2 are set to predetermined values so as to be on the target characteristics. For example, the X value of the point A is an intermediate value of the range that the scene relative luminance can take in the digital camera characteristic, and the value of the default target characteristic corresponding to the X coordinate is the Y value of the point A. The points B1 and B2 are set on the default target characteristics, and are set so that the points B1, A, and B2 are connected by a straight line. In addition, these parameters are such that the X value of the point A is in the data display unit 1404, the Y value of the point A is in the data display unit 1405, and tan θ that is the slope of the straight line connecting the points B1, A, and B2 is the data display unit 1406. Respectively. Here, the image displayed on the image display unit 1401 is displayed as it is on the monitor 306 as it is, but the present invention is not limited to this, and more printing is performed in consideration of the gradation characteristics of the monitor 306. A gradation conversion table that cancels the gradation characteristics of the monitor 306 may be created so that an image close to the result is displayed, and the converted image data may be displayed on the monitor 306 using this table.

  The user looks at the image displayed on the image display unit 1401 and determines whether or not to print. If printing is performed, the print button 1409 is clicked with a mouse (not shown), and the process is transferred to the printer correction processing unit 402 (step S1502 in FIG. 15). Similarly, when the printing is to be stopped, the printing process is stopped by clicking a cancel button 1410 (step S1503 in FIG. 15).

  At this time, the user can convert the image so as to obtain a print result having a desired gradation. First, the user selects an arbitrary rectangular area on the image displayed on the image display unit 1401 shown in FIG. 14 using an input device such as a mouse. Alternatively, the target characteristic of the data display unit 1403 or the data of the data display units 1404 to 1406 is changed. Next, the user clicks a setting button 1407. When the setting button is clicked, a gradation conversion table is created based on the selected rectangular area on the image display unit 1401 and the values of the data display units 1403 to 1406 (step S1504 in FIG. 15).

  The flow of processing at this time is shown in FIG. In FIG. 16, first, it is checked whether a new area is selected on the image display unit 1401 by the user (step S1601 in FIG. 16). If a new area is selected, the average brightness in the selected area is calculated, and the target characteristics are updated (steps S1602 and S1603 in FIG. 16). Next, the target characteristics and parameters of the target characteristics are displayed on the data display sections 1403 to 1406 (step S1604 in FIG. 16). Based on this target characteristic, a gradation conversion table is created (step S1605 in FIG. 16). If a new area has not been selected, it is confirmed whether any of the data display units 1403 to 1406 has been updated. If it has been updated, a gradation conversion table is created based on the updated target characteristics ( Steps S1606 and S1607 in FIG.

  In step S1506 in FIG. 15, the original image created by the above processing is converted using the gradation conversion table. The converted image is displayed on the image display unit 1401 (steps S1504 to S1507 in FIG. 15). The user can repeatedly perform the above processing while viewing the image on the image display unit 1401. If the redo button 1408 is clicked, the values of the data display units 1403 to 1406 are returned to the settings at the time of UI activation, and the original image is displayed on the image display unit 1401 (steps S1508 to S1510 in FIG. 15). Note that the average brightness calculation processing in the selected region, the gradation conversion table creation method, and the image conversion method have already been described in the first embodiment, and are omitted here.

  As is clear from the above description, according to the present embodiment, since the user can select the area intended by the user and at the same time the contrast in the print can be adjusted, the brightness of any subject selected by the user can be adjusted. The desired contrast according to the subject can be given to the print without changing the image.

[Third embodiment]
In the first embodiment, the face is detected and the process is performed according to the result. However, the present invention is not limited to this. For example, the sky area or the green area is detected, and the result is detected. Processing may be performed. Further, the face detection process in the first embodiment is not limited to this, and any process may be used as long as it detects a face area. At this time, it goes without saying that the shape of the face region is not limited to a rectangular region, and may be any region.

  Moreover, although the said embodiment demonstrated using the brightness | luminance, you may use the other component which shows a brightness.

[Other embodiments]
Note that the present invention can be applied to a system including a plurality of devices (for example, a host computer, an interface device, a reader, and a printer), and a device (for example, a copying machine and a facsimile device) including a single device. You may apply to.

  Another object of the present invention is to supply a storage medium storing software program codes for implementing the functions of the above-described embodiments to a system or apparatus, and the computer (or CPU or MPU) of the system or apparatus stores the storage medium. Needless to say, this can also be achieved by reading and executing the program code stored in.

  In this case, the program code itself read from the storage medium realizes the functions of the above-described embodiments, and the storage medium storing the program code constitutes the present invention.

  As a storage medium for supplying the program code, for example, a floppy (registered trademark) disk, hard disk, optical disk, magneto-optical disk, CD-ROM, CD-R, magnetic tape, nonvolatile memory card, ROM, or the like is used. be able to.

  Further, by executing the program code read by the computer, not only the functions of the above-described embodiments are realized, but also an OS (operating system) operating on the computer based on the instruction of the program code. It goes without saying that a case where the function of the above-described embodiment is realized by performing part or all of the actual processing and the processing is included.

  Further, after the program code read from the storage medium is written into a memory provided in a function expansion board inserted into the computer or a function expansion unit connected to the computer, the function expansion is performed based on the instruction of the program code. It goes without saying that the CPU or the like provided in the board or the function expansion unit performs part or all of the actual processing, and the functions of the above-described embodiments are realized by the processing.

It is a figure explaining a comprehensive gradation characteristic. It is a figure for demonstrating the harmful effect which arises by converting a gradation property. 1 is a block diagram showing a system configuration of an image processing apparatus according to a first embodiment of the present invention. 2 is a block diagram illustrating a functional configuration of a printer driver. FIG. It is a figure which shows the flow of a process in the image correction process part. It is a figure which shows the flow of a process in a face detection process (step S501). It is a figure which shows the detail of the process in a face detection process (step S501). It is a figure which shows the example of mask data. It is a figure which shows the conversion method in gradation conversion table preparation (step S505). It is a figure which shows the example of target characteristics. It is a figure which shows the flow of the setting process of a target characteristic. It is a figure which shows the flow of each process in the setting process of a target characteristic. It is a block diagram which shows the process structure in an image data converter (step S506). It is a figure which shows UI which the image processing apparatus concerning the 2nd Embodiment of this invention has. It is a figure which shows the flow of a process in the image correction process part of the image processing apparatus concerning the 2nd Embodiment of this invention. It is a figure which shows the flow of a process of the parameter acquisition step (S1505) among the processes in an image correction process part.

Explanation of symbols

301 Application 302 OS
303 Printer Driver 305 Printer 401 Image Correction Processing Unit 402 Printer Correction Processing Unit 1301 L * a * b * Conversion Unit 1302 Table Conversion Unit 1303 L * a * b * Conversion Unit 1304 L * a * b * Reverse Conversion Unit 1401 Image Display unit 1402 Selection area 1403 Data display unit (target characteristic display unit)
1404 Data display part (Point A, X value display part)
1405 Data display section (Point A, Y value display section)
1406 Data display part (inclination display part at point A)
1407 Setting button 1408 Redo button 1409 Print button 1410 Cancel button

Claims (13)

An image processing device that processes an image obtained by photographing a subject with a photographing device and outputs the image using an output device,
Generating means for generating a gradation conversion table representing the relationship between the luminance of the image and the density of the output image output using the output device;
Correction means for correcting the image based on the gradation conversion table,
The generating means is configured so that a luminance of a subject imaged in a predetermined region of the image of the subject corresponds to a density of an output image obtained by outputting the image of the predetermined region using the output device. An image processing apparatus that generates a gradation conversion table. The predetermined area refers to an area including a person's face when the image includes a person's face, and refers to an entire image area when the image includes no person's face. The image processing apparatus according to claim 1. The image processing apparatus according to claim 1, further comprising a predetermined area specifying unit that specifies the predetermined area. A target characteristic setting means for setting, as a target characteristic, a relationship between the luminance of the subject and the density of the output image output using the output device;
The generating means includes
The gradation conversion table is generated based on a target characteristic set by the target characteristic setting unit, an output characteristic of the photographing apparatus, and an output characteristic of the output apparatus. Image processing device. Target characteristic display means for displaying the target characteristic;
Changing means for changing the target characteristic;
The image processing apparatus according to claim 4, further comprising: a corrected image display unit that displays an image corrected by the correcting unit. The correction means includes
When the RGB value of the image is converted into a Lab value, the a value and the b value, and the L value converted into the Lab value after converting the RGB value of the image into the Lab conversion table are converted into RGB values. The image processing apparatus according to claim 1, wherein the image is corrected by conversion. An image processing method for processing image data obtained by photographing a subject with a photographing device and generating image data for output using an output device,
A generation step of generating a gradation conversion condition for converting a brightness component of the image data into a density output by the output device;
A correction step of correcting the image based on the gradation conversion condition,
The generating step includes
A statistical value calculating step for obtaining a statistical value related to a brightness component of the image data;
A first control point setting step of setting a first control point of the gradation conversion condition so that the brightness of the statistical value is reproduced by the output device;
A second control point setting step for setting a second control point set according to the brightness range of the image and the density range of the output device;
An image processing method comprising: a generation step of generating the gradation conversion condition based on the first control point and the second control point. The generation step further includes an inclination setting step for setting an inclination according to a scene of an image indicated by the image data,
The image processing method according to claim 7, wherein the gradation conversion condition is generated based on the first control point, the second control point, and the inclination. Furthermore, it has a detection step of detecting an image area of a specific target from the image indicated by the image data,
8. The image processing method according to claim 7, wherein the statistical value calculating step obtains a statistical value related to a brightness component of the image data of the detected image area. 9. The image processing method according to claim 8, wherein the image area of the specific target is a face area, and the statistical value is an average value. A gradation conversion condition display step for displaying the gradation conversion condition;
An adjustment step of adjusting the gradation conversion condition according to a user instruction;
The image processing method according to claim 7, further comprising: a corrected image display step of displaying the image corrected by the correction step. A storage medium storing a control program for realizing the image processing method according to claim 7 by a computer. A control program for realizing the image processing method according to claim 7 by a computer.

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