Information processing apparatus, information processing method, and program

Abstract

To perform color mapping to a printing gamut so as to reduce the degree of color conversion occurring due to conversion of colors, even when printing of an image is executed during reception of the image.SOLUTION: An information processing apparatus receives divided images obtained by dividing an image from a device that sequentially transmits the divided images. In response to the reception of the divided images, the information processing apparatus acquires, from a first divided image, color information on a first color defined by a first color gamut, and color information on a second color defined by the first color gamut. The information processing apparatus performs first color conversion processing of converting the first color into a third color defined by a second color gamut different from the first color gamut, and converting the second color into a fourth color defined by the second color gamut. When the color difference between the third color and the fourth color becomes smaller than a predetermined threshold, the information processing apparatus corrects a conversion parameter in the first color conversion processing so as to increase the color difference between the fourth color and a fifth color obtained by converting the first color into a color defined by the second color gamut, compared to the color difference between the third color and the fourth color.SELECTED DRAWING: Figure 8

Description

Technical Field

[0001] The present invention relates to an information processing apparatus, an information processing method, and a program.

Background Art

[0002] There is known an information processing apparatus that receives a digital manuscript described in a predetermined color space, performs mapping of each color in the color space to a color gamut reproducible by a printer, and outputs the result. Patent Document 1 describes "Perceptual" mapping and "Absolute Colorimetric" mapping. Further, Patent Document 2 describes determination of the presence or absence of color space compression and the compression direction for an input color image signal.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Patent Document 2

Summary of the Invention

Problems to be Solved by the Invention

[0004] When performing the "Perceptual" mapping described in Patent Document 1, the saturation may decrease even for colors reproducible by the printer in the color space of the digital manuscript. Further, when performing "Absolute Colorimetric" mapping, color degradation may occur due to mapping between a plurality of colors outside the reproducible color gamut of the printer included in the digital manuscript. Further, in Patent Document 2, since unique compression is performed in the saturation direction on the input color image signal, there remains a concern about the effect of reducing the degree of color degradation. Further, since the conventional mapping is assumed to be performed on the entire image, there is a problem that it cannot be applied when printing is executed before receiving the entire image.

[0005] An object of the present invention is to enable color mapping to a printing color gamut such that the degree of color conversion caused by color conversion is reduced even when printing an image during reception of the image.

Means for Solving the Problems

[0006] To achieve the object of the present invention, for example, an information processing apparatus according to an embodiment includes the following configuration. That is, a receiving unit that receives a divided image from a device that sequentially transmits each divided image obtained by dividing an image, an acquisition unit that acquires, from a first divided image received by the receiving unit, color information of a first color defined in a first color gamut and color information of a second color defined in the first color gamut, a conversion unit that performs a first color conversion process of converting the first color into a third color defined in a second color gamut different from the first color gamut and converting the second color into a fourth color defined in the second color gamut, and a first correction unit that corrects conversion parameters in the first color conversion process such that a color difference between the fifth color obtained by converting the first color into a color defined in the second color gamut and the fourth color is larger than a color difference between the third color and the fourth color when the color difference between the third color and the fourth color is smaller than a predetermined threshold value. The acquisition unit, the conversion unit, and the first correction unit operate in response to the receiving unit receiving the divided image.

Advantages of the Invention

[0007] It is possible to perform color mapping to a printing color gamut such that the degree of color conversion caused by color conversion is reduced even when printing an image during reception of the image.

Brief Description of the Drawings

[0008]

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Embodiments for Carrying Out the Invention

[0009] Hereinafter, embodiments will be described in detail with reference to the accompanying drawings. It should be noted that the following embodiments do not limit the invention according to the claims. Although a plurality of features are described in the embodiments, not all of these plurality of features are essential to the invention, and the plurality of features may be arbitrarily combined. Further, in the accompanying drawings, the same or similar configurations are given the same reference numerals, and duplicate descriptions are omitted.

[0010] [Embodiment 1] The terms used in this specification are defined in advance as follows.

[0011] [Color Reproduction Region] The color reproduction region according to this embodiment refers to the range of reproducible colors in an arbitrary color space. Hereinafter, the color reproduction region is also referred to as a color reproduction range, a color gamut, or a gamut. As an index representing the size of this color reproduction region, there is a gamut volume. The gamut volume is the three-dimensional volume in an arbitrary color space.

[0012] It is conceivable that the chromaticity points constituting the color reproduction region are discrete. For example, it is conceivable that a specific color reproduction region is represented by 729 points on CIE-L*a*b*, and for the points in between, known interpolation operations such as tetrahedral interpolation or cubic interpolation are used to obtain them. In such a case, the corresponding gamut volume can use, corresponding to the interpolation operation method, the volume on CIE-L*a*b* such as a tetrahedron or a cube constituting the color reproduction region obtained and accumulated.

[0013] Regarding the color reproduction range and color gamut according to this embodiment, an example using the color reproduction range in the CIE-L*a*b* space will be described. However, it is not particularly limited to this as long as the same processing is possible, and different color reproduction ranges may be used. Similarly, the numerical values of the color reproduction range according to this embodiment indicate the volume when cumulatively calculated in the CIE-L*a*b* space on the premise of tetrahedral interpolation, but it is not particularly limited to this.

[0014] [Gamma Mapping] The gamma mapping according to this embodiment is a process of converting a color in a certain color gamut into a color in a different color gamut. For example, mapping a color in the input color gamut to the output color gamut is called gamma mapping, and conversion within the same color gamut is not called gamma mapping. In gamma mapping, maps such as Perceptual, Saturation, or Colorimetric of the ICC profile may be used. Hereinafter, when simply denoted as "mapping process", it shall refer to the mapping process in gamma mapping.

[0015] The mapping process may convert one 3DLUT (look-up table). Also, the mapping process may be performed after color space conversion to the standard color space. For example, when the input color space is sRGB, the input color may be converted into a color on the CIE-L*a*b* color space, and the mapping process may be performed on the CIE-L*a*b* color space to the output color gamut. This mapping process may be a 3DLUT process or a process using a conversion formula. Also, the mapping process and the conversion process from the input color space to the output color space at the time of output may be performed simultaneously. For example, at the time of input, it is the sRGB color space, and at the time of output, it may be converted into RGB values or CMYK values specific to the image forming apparatus.

[0016] [Original Data] The manuscript data according to this embodiment refers to the entire input digital data to be processed, and is assumed to be composed of one page to multiple pages. The single-page manuscript data may be held as image data or expressed as drawing commands. When the manuscript data is expressed as drawing commands, rendering may be performed, and the processing may be performed after being converted into image data. The image data is composed of a plurality of pixels arranged two-dimensionally. The pixel holds information representing a color in a color space. Examples of the information representing a color include RGB values, CMYK values, K values, CIE-L*a*b* values, HSV values, or HLS values.

[0017] [Color difference reduction, color degradation] In this embodiment, when performing gamut mapping on any two colors, the case where the distance between the colors after mapping in a predetermined color space is smaller than the distance between the colors before mapping is simply expressed as "color difference reduction". When color difference reduction occurs, it is conceivable that due to the reduction of the color difference after mapping, what was recognized as different colors before mapping is recognized as the same color after mapping. In the following, the case where color difference reduction occurs and the color difference after conversion is less than a predetermined threshold is referred to as "color degradation". The threshold used here will be described later.

[0018] Hereinafter, a specific example of color degradation will be given and described. Here, it is assumed that there are color A and color B in a digital manuscript, and by mapping these to the color gamut of a printer, color A is converted to color C and color B is converted to color D. In this case, the state where the distance between color C and color D is smaller than the distance between color A and color B and the color difference between color C and color D is less than a predetermined threshold is defined as color degradation. When color degradation occurs, colors that were recognized as different in the digital manuscript are recognized as the same color when printed. For example, when printing a graph that uses different colors to recognize different items, if different colors are recognized as the same color due to color degradation, there is a possibility of being misrecognized as the same item despite being different items.

[0019] In the present embodiment, any color space may be used as a predetermined color space for calculating the distance between colors. For example, an sRGB color space, an Adobe RGB color space, a CIE-L*a*b* color space, a CIE-LUV color space, an XYZ colorimetric system color space, an xyY colorimetric system color space, an HSV color space, or an HLS color space may be used when calculating the color difference.

[0020] [Information processing apparatus] FIG. 1 is a block diagram showing an example of the configuration of an information processing apparatus and an image forming apparatus according to the present embodiment. In the present embodiment, a PC, a tablet, a server, or an image forming apparatus can be used as the information processing apparatus 101. The information processing apparatus 101 includes a CPU 102, a RAM 103, a storage medium 104, an accelerator 105, and a transfer I / F 106.

[0021] The CPU 102 is a central processing unit, and executes various processes by reading a program stored in the storage medium 104 such as an HDD or a ROM into the RAM 103 as a work area. For example, the CPU 102 acquires a command based on a user input acquired via an HID (Human Interface Device) I / F (not shown). Then, the CPU 102 executes various processes according to the acquired command or a program stored in the storage medium 104. Further, the CPU 102 performs predetermined processing on the document data acquired via the transfer I / F 106 according to a program stored in the storage medium 104. Then, the CPU 102 displays the results of such processing and various information on a display (not shown) and transmits them to an external device via the transfer I / F 106.

[0022] The accelerator 105 is hardware capable of executing information processing at a higher speed than the CPU 102. The accelerator 105 is activated by the CPU 102 writing parameters and data necessary for information processing to a predetermined address in the RAM 103. After reading the above parameters and data, the accelerator 105 executes information processing on the data. The accelerator 105 according to the present embodiment is not an essential element, and the same processing may be executed by the CPU 102. Specifically, the accelerator is a GPU or a dedicated electrical circuit. The above parameters may be stored in the storage medium 104 or acquired from the outside via the transfer I / F 106.

[0023] The image forming apparatus 108 is an apparatus that forms an image on a print medium. The image forming apparatus 108 according to the present embodiment includes an accelerator 109, a transfer I / F 110, a CPU 111, a RAM 112, a storage medium 113, a recording head controller 114, and a recording head 115.

[0024] The CPU 111 is a central processing unit, and comprehensively controls the image forming apparatus 108 by reading and executing a program stored in the storage medium 113 into the RAM 112 as a work area. The accelerator 109 is hardware capable of executing information processing at a higher speed than the CPU 111. The accelerator 109 is activated by the CPU 111 writing parameters and data necessary for information processing to a predetermined address in the RAM 112. After reading the above parameters and data, the accelerator 109 executes information processing on the data. The accelerator 109 according to the present embodiment is not an essential element, and the same processing may be executed by the CPU 111. The above parameters may be stored in the storage medium 113 or may be stored in a storage (not shown) such as a flash memory or an HDD.

[0025] Here, the information processing performed by the CPU 111 or the accelerator 109 will be described. The information processing performed by the CPU 111 or the accelerator 109 according to the present embodiment is, for example, a process of generating data indicating the dot formation positions of ink in each scan by the recording head 115 based on the acquired print data.

[0026] In the present embodiment, the information processing apparatus 101 performs each process including the color conversion process and the quantization process described below, and the image forming apparatus 108 performs image forming processing based on the print data generated by those processes. However, as long as the same functions can be implemented, the processes performed by the information processing apparatus 101 and the image forming apparatus 108 are not particularly limited in this way, and part or all of each process described as being performed by the information processing apparatus 101 may be executed by the image forming apparatus 108. For example, the color conversion process and the quantization process may be performed by the image forming apparatus 108.

[0027] The information processing apparatus 101 according to the present embodiment converts a color represented in a first color gamut included in the input image data into a color represented in a second color gamut. Hereinafter, when simply referred to as "color conversion process", it refers to the color conversion process between color gamuts performed by such an information processing apparatus 101. In the present embodiment, by the color conversion process performed by the information processing apparatus 101, the input image data is converted into data (ink data) indicating the color and density of ink for each pixel to be printed by the image forming apparatus 108.

[0028] For example, the acquired print data includes image data indicating an image. When the image data is data indicating an image in a color space coordinate (here, sRGB) that is the display color of the monitor, the data indicating the image with the color coordinates (R, G, B) is converted into ink data (here, CMYK) handled by the image forming apparatus 108 by the color conversion process. The color conversion method according to the present embodiment is realized by a known conversion process such as matrix operation processing, three-dimensional LUT, or four-dimensional LUT.

[0029] The image forming apparatus 108 according to this embodiment uses, as an example, inks of black (K), cyan (C), magenta (M), and yellow (Y). Therefore, the image data of RGB signals is converted into image data composed of 8-bit color signals of K, C, M, and Y. The color signal of each color corresponds to the amount of application of each ink. Also, the case where the number of ink colors used is four colors of K, C, M, and Y will be described as an example. However, for the purpose of improving image quality, other ink colors such as light cyan (Lc), light magenta (Lm), or gray (Gy) inks with low density may be used. In that case, an ink signal corresponding to its color is generated.

[0030] After the color conversion process, the information processing apparatus 101 performs quantization processing on the ink data. The quantization processing according to this embodiment is a process of reducing the number of gradation levels of the ink data. The information processing apparatus 101 according to this embodiment performs quantization using a dither matrix in which thresholds for comparing with the values of the ink data are arranged for each pixel. Through the quantization process, finally, binary data indicating whether to form dots at each dot formation position is generated.

[0031] After the binary data for printing is generated, the binary data is transferred to the recording head 115 by the recording head controller 114. At the same time, the CPU 111 performs print control to operate the carriage motor that operates the recording head 115 via the recording head controller 114, and further operates the conveyance motor that conveys the print medium. The recording head 115 scans the print medium and forms an image by discharging ink droplets onto the print medium at the same time.

[0032] The information processing apparatus 101 and the image forming apparatus 108 are connected via a communication line 107. In this embodiment, a local area network is used as the communication line 107, but it is not particularly limited as long as the information processing apparatus 101 and the image forming apparatus 108 can be communicably connected. The communication line 107 may be, for example, a USB hub, a wireless communication network using a wireless access point, or a connection using a Wi-Fi Direct (registered trademark) communication function.

[0033] Hereinafter, the recording head 115 will be described as having recording nozzle arrays for four colors of cyan (C), magenta (M), yellow (Y), and black (K). FIG. 19 is a diagram for explaining the recording head 115 according to this embodiment. In the image forming process according to this embodiment, an image is formed by performing N multiple scans on a unit area corresponding to one nozzle array.

[0034] The recording head 115 includes a carriage 116, nozzle arrays 115k, 115c, 115m, and 115y, and an optical sensor 118. The carriage 116 on which the four nozzle arrays 115k, 115c, 115m, and 115y and the optical sensor 118 are mounted can reciprocate along the X direction (main scanning direction) in the figure by the driving force of a carriage motor transmitted via a belt 117. As the carriage 116 moves relative to the print medium in the X direction, ink droplets are ejected from each nozzle of the nozzle array in the gravitational direction (the -Z direction in the figure) based on recording data. Thereby, an image for 1 / N of the main scan is formed on the print medium placed on the platen 119. When one main scan is completed, the print medium is conveyed along the conveyance direction (the -y direction in the figure) intersecting the main scanning direction by a distance corresponding to the width for 1 / N of the main scan. By repeating these operations alternately, an image having a width corresponding to one nozzle array is formed by performing N multiple scans. By repeating such main scanning and conveyance operations alternately, an image is gradually formed on the print medium. By doing so, it is possible to control to complete the image formation for a predetermined area.

[0035] Consider the case where printing is started before the reception of the entire original data is completed during the reception of the original data. In such a case, while one page of the original data is being received, for the received partial image, color conversion processing, quantization processing, and image formation processing are performed as described above. By performing such processing, it is possible to shorten the time required from the start of input of the original data to the end of printing compared to the case where processing is performed after one page of the original data has been completely received.

[0036] The information processing apparatus 101 according to the present embodiment receives a divided image from an apparatus that sequentially transmits each divided image obtained by dividing an image. Then, in response to receiving the divided image, from the received divided image, color information of a first color defined in a first color gamut and color information of a second color defined in the first color gamut are acquired, and a first color conversion process is performed to convert the first color into a third color defined in a second color gamut different from the first color gamut, and convert the second color into a fourth color defined in the second color gamut. Here, when the color difference between the third color and the fourth color becomes smaller than a threshold value, the information processing apparatus 101 corrects the conversion parameter in the first color conversion process so that the color difference between the fifth color obtained by converting the first color into a color defined in the second color gamut and the fourth color becomes larger than the color difference between the third color and the fourth color, and performs a color degradation correction process. A detailed description of the color degradation correction will be given later.

[0037] Here, the information processing apparatus 101 is a device built into the image forming apparatus 108 and receives a divided image from an external device of the image forming apparatus 108. However, it is not particularly limited to such a configuration as long as it can sequentially receive divided images and perform subsequent processes. For example, the information processing apparatus 101 may be a personal computer connected to the image forming apparatus 108 or a server to which the image forming apparatus 108 is connected, and may receive a divided image from an external device or server.

[0038] FIG. 2 is a flowchart showing an example of the overall processing performed by the information processing apparatus 101 according to the present embodiment. The information processing apparatus 101 according to the present embodiment can reduce the degree of color degradation by increasing the distance between colors in the color space after color conversion for a combination of colors that causes color degradation due to color conversion processing. The processing in FIG. 2 is realized, for example, by the CPU 102 reading out a program stored in the storage medium 104 to the RAM 103 and executing it. Further, the processing in FIG. 2 may be executed by the accelerator 105. The processing in FIG. 2 is assumed to be executed in response to the input of image data.

[0039] The information processing apparatus 101 according to the present embodiment sequentially receives divided images obtained by dividing an image, and generates conversion parameters for the received divided image in response to receiving the divided image. In FIG. 2, it is assumed that two divided images, a first divided image and a second divided image, are received as the divided images, and the processing for making the first divided image the processing target is performed in S101 to S105, and the processing for making the second divided image the processing target is performed in S106 to S110. In the following, the first divided image is assumed to be the divided image received earlier than the second divided image, and various processes will be described.

[0040] In S101, the CPU 102 acquires first document data as a first divided image obtained by dividing an image used for printing. In the present embodiment, it is assumed that an image stored in the storage medium 104 is acquired, but an image may be input from an external device via the transfer I / F 106. The CPU 102 according to the present embodiment acquires a value representing a color expressed in a predetermined color space included in the document data. As the value representing the color, for example, sRGB data, Adobe RGB data, CIE-L*a*b* data, CIE-LUV data, XYZ colorimetric system data, xyY colorimetric system data, HSV data, or HLS data is used.

[0041] Note that as the original manuscript data used here, an image including pixels containing color information of a first color and pixels containing color information of a second color is acquired, and color information of such an image is acquired. Hereinafter, such first and second colors are used in each process as unique colors (here, color 403 and color 404) described later with reference to FIG. 4 and the like, but the colors used in the process are not limited to these two, and three or more colors may be used.

[0042] In S102, the CPU 102 performs color conversion processing on the first original manuscript data using conversion parameters stored in the storage medium 104 in advance. The conversion parameters in the present embodiment are a gamma mapping table, and gamma mapping using the gamma mapping table is performed on the color information of each pixel of the first original manuscript data as the color conversion processing. The first original manuscript data after gamma mapping is stored in the RAM 103 or the storage medium 104.

[0043] The CPU 102 according to the present embodiment uses a three-dimensional look-up table as the gamma mapping table. The CPU 102 can calculate a combination of output pixel values (Rout, Gout, Bout) by gamma mapping for a combination of input pixel values (Rin, Gin, Bin) with reference to the gamma mapping table. When Rin, Gin, and Bin, which are input values, each have 256 gradations, as the gamma mapping table, a table Table1

[0256]

[0256]

[0256] [3] having a total of 16,777,216 sets of output values can be used. The color conversion processing may be realized, for example, by performing the processing shown in the following formulas (1) to (3) on each pixel of the image composed of the RGB pixel values of the image data input in S101. Rout = Table1[Rin][Gin][Bin][0] ··· (Formula 1) Gout = Table1[Rin][Gin][Bin][1] ··· (Formula 2) Bout = Table1[Rin][Gin][Bin][2] ··· (Formula 3)

[0044] Note that the number of grids in the gamma mapping table is not limited to 256 grids. For example, the number of grids may be reduced from 256 grids (e.g., to 16 grids) so that the table values of a plurality of grids are stored and the output value is determined. Known processes performed when using the LUT table, such as reducing the table size in this way, may be optionally additionally executed.

[0045] In S103, the CPU 102 creates a table after color fade correction based on the first original manuscript data input in S101, the image data after gamma mapping performed in S102, and the gamma mapping table. The format of the table after color fade correction is the same as the format of the gamma mapping table. The processing performed in S104 and the table after color fade correction will be described later with reference to FIGS. 3 and 4.

[0046] In S104, the CPU 102 generates image data after color fade correction in which color fade correction is performed using the table after color fade correction created in S103, with the image data input in S101 as the input. The generated image data after color fade correction is stored in the RAM 103 or the storage medium 104. In S105, the CPU 102 outputs the image data after color fade correction stored in S104 from the information processing apparatus 101 via the transfer I / F 106.

[0047] In S106, the CPU 102 acquires second original manuscript data as a second divided image obtained by dividing the image used for printing. Since S106 to S110 are performed in the same manner as S101 to S105 except that the divided image to be processed changes from the first original manuscript data to the second original manuscript data, detailed description here is omitted. When S110 ends, the processing of FIG. 1 ends.

[0048] In FIG. 2, the case of using two divided images of the first original data and the second original data has been described. However, the number of divided images is not limited in this way, and the images may be divided into three or more and processing may be performed on each of them. In that case, the same processing as in S101 to S105 is performed on each of the divided images.

[0049] Note that the color conversion process in the gamma mapping performed in S102 and S107 may be a mapping from the color in the sRGB color space to the color in the color reproduction gamut of printing by the image forming apparatus 108. According to such processing, it is possible to suppress a decrease in saturation and color difference due to gamma mapping within the color reproduction gamut of the image forming apparatus 108. Further, in gamma mapping, parameter selection emphasizing tone reproduction may be performed.

[0050] Hereinafter, with reference to FIG. 3, the table after color degradation correction created in S103 will be described. FIG. 3 is a flowchart showing an example of the process for creating the table after color degradation correction in S103. The process of FIG. 3 is realized, for example, by the CPU 102 reading out the program stored in the storage medium 104 into the RAM 103 and executing it. Further, the process of FIG. 3 may be executed by the accelerator 105. In the following, the first divided image (original data) and the second divided image are not distinguished, and may be referred to as image data, image, or original data. Also, although S103 will be described here, the same processing is performed in S108.

[0051] In S201, the CPU 102 detects all the unique colors of the image data input in S101. Here, the unique color refers to the color detected from the image data, and those with different pixel values are detected as different unique colors. Here, the detection result of the unique color is stored as a unique color list in the RAM 103 or the storage medium 104. It is assumed that the unique color is specified by components such as RGB. However, one unique color may have a range for each RGB component, and the content of the unique color may vary according to the color detection method. The unique color list is initialized at the start of S201. The CPU 102 repeats the detection process of the unique color for each pixel of the image data, and determines whether the color of each pixel is different from the unique colors detected so far for all the pixels included in the image data. Through such processing, the color determined to be a unique color is stored as a unique color in the unique color list.

[0052] When the input image data is sRGB, since it has 256 gradations respectively, there are unique colors among a total of 16,777,216 colors of 256×256×256. If all these colors are detected as unique colors and stored in the unique color list, the number of colors becomes enormous and the processing speed decreases. From such a perspective, the CPU 102 may perform the detection of unique colors discretely. For example, the CPU 102 may perform the detection of unique colors after reducing the 256 gradations to 16 gradations. In such a case, the CPU 102 may group 16 adjacent colors out of the 256 gradation colors into 16 gradations. According to such a color reduction process, it is possible to detect unique colors from a total of 4096 colors of 16x16x16, thereby making it possible to improve the processing speed.

[0053] In S202, based on the unique color list detected in S201, the CPU 102 detects a combination of colors in which color degradation occurs among the combinations of unique colors included in the image data. The process executed in S202 will be described using the schematic diagram of FIG. 4. In FIG. 4, on a plane using two axes of the L* axis and the C* axis in the CIE-L*a*b* color space, the color gamut of the input image data before color conversion processing is shown as color gamut 401, and the color gamut after being converted by gamut mapping is shown as color gamut 402. The input image data includes color 403 (the first color) and color 404 (the second color), which are shown on color gamut 401. Colors 405 and 406 are colors on color gamut 402. Color 405 is the color when gamut mapping is performed on color 403, and color 406 is the color when gamut mapping is performed on color 404.

[0054] The CPU 102 according to the present embodiment determines that color degradation has occurred when the color difference 408 between color 405 and color 406 is smaller than a predetermined threshold. Here, in addition to the color difference 408 between color 405 and color 406 being smaller than the predetermined threshold, it is assumed that color degradation is determined to have occurred when the color difference 408 is smaller than the color difference 407 between color 403 and color 404. The threshold used here can be arbitrarily set according to the conditions desired by the user. This threshold may be a fixed value or a value that varies depending on the combination of colors. For example, the CPU 102 may use the color difference before color conversion of the combined colors (here, the color difference 407 between color 403 and color 404) as the above-described predetermined threshold. The CPU 102 repeats such determination processing for all combinations of colors in the unique color list.

[0055] In this embodiment, the color difference between two colors is calculated as the Euclidean distance ΔE in the color space. Since the CIE-L*a*b* color space is a visually uniform color space, the Euclidean distance can be approximated as the amount of color change. Therefore, when the Euclidean distance on the CIE-L*a*b* color space becomes smaller, people tend to perceive that the colors are approaching, and when it becomes larger, people tend to perceive that the colors are separating. Hereinafter, the case of using the Euclidean distance (hereinafter referred to as color difference ΔE) in the CIE-L*a*b* color space as the color difference will be described. The color information in the CIE-L*a*b* color space is represented by a three-axis color space of L*, a*, and b* respectively. Color 403 is represented by L403, a403, and b403. Color 404 is represented by L404, a404, and b404. Color 405 is represented by L405, a405, and b405. Color 406 is represented by L406, a406, and b406. When the input image data is represented in another color space, it may be converted to the CIE-L*a*b* color space by a known color space conversion technique, or subsequent processing may be performed in that color space as it is. The calculation formulas for color difference ΔE407 and color difference ΔE408 are as follows.

Equation

[0056] The CPU 102 determines that color degradation occurs when the color difference ΔE408 is smaller than the threshold value. Based on the determination of the human color difference, if the converted color difference ΔE408 can be distinguished from different colors to a certain extent, it can be determined that color degradation has not occurred and there is no need to correct the color difference. From such a perspective, the threshold value used here can be, for example, 2.0. Also, as described above, this threshold value may be the same as ΔE407. Further, the CPU 102 may determine that color degradation occurs when the color difference ΔE408 is smaller than 2.0 and the color difference ΔE408 is smaller than the color difference ΔE407.

[0057] In S203, the CPU 102 determines whether the number of color combinations determined to cause color degradation in S202 is zero. If it is zero, the process proceeds to S204; otherwise, the process proceeds to S205. In S204, the CPU 102 determines that the input image data is an image that does not require color degradation correction, and ends the process of FIG. 2.

[0058] Here, it has been described that when the number of colors determined to cause color degradation is zero, it is determined that the image does not require color degradation correction. However, the processing is not particularly limited in this way. For example, the CPU 102 may determine whether the image does not require color degradation correction based on the number of color combinations that cause color degradation with respect to the total number of combinations of unique colors. In that case, the CPU 102 may determine that the image requires color degradation correction, for example, when the number of color combinations that cause color degradation is more than half of the total number of combinations of unique colors. According to such processing, it is possible to set so that the color degradation correction is executed only when it can be determined that the color degradation correction is more necessary.

[0059] In S205, the CPU 102 performs color degradation correction on the color combinations that cause color degradation based on the input image data and the table after degradation correction.

[0060] The color degradation correction performed by the CPU 102 according to this embodiment will be described in detail with reference to FIG. 4. In FIG. 4, it is determined that color degradation occurs in the color combination of color 403 and color 404. Therefore, the CPU 102 according to this embodiment corrects the conversion parameters used in the color conversion process so that the color difference after color conversion between color 403 and color 404 becomes larger. That is, the CPU 102 can correct the conversion parameters so as to increase the color distance on a predetermined color space after color conversion. By such correction, the degree of color degradation can be reduced. Here, the CPU 102 sets a color distance (discriminable color distance) that can be recognized as different colors based on human visual characteristics, and corrects the conversion parameters of the color conversion process so that the color difference after conversion of two colors becomes such a color distance.

[0061] Here, the CPU 102 sets the above-mentioned distinguishable color distance as a color distance with a color difference ΔE of 2.0 or more. Also, the conversion parameters may be corrected so that the color difference after conversion of two colors is approximately the same as the color difference Δ407 between the color 403 before conversion and the color 404 before conversion.

[0062] The color degradation correction process is repeated for all combinations of colors that cause color degradation. The results of the color degradation correction for the number of color combinations are stored in a table in association with the color information before correction and the color information after correction in S206 described later, and the table with the correspondence parameters corrected in this way is defined as the color degradation correction table. In the example shown in FIG. 4, the color information is represented by the color information in the CIE-L*a*b* color space. Therefore, the CPU 102 may convert the color information stored in the color degradation correction table into the color in the color space of the input image data and the image data at the time of output and then store it. In that case, the color information before correction is converted into the color information in the color space of the input image data, and the color information after correction is converted into the color information in the color space of the output image data, and then stored in the color degradation correction table.

[0063] Next, the process of such color degradation correction will be described in detail. The CPU 102 obtains a color difference correction amount 409 necessary for making the color difference ΔE408 after conversion a distinguishable color distance. In the present embodiment, the distinguishable color distance is set to a color difference ΔE of 2.0, and the difference between such a value 2.0 and the color difference ΔE408 is calculated as the color difference correction amount 409. Also, the CPU 102 may calculate the color difference correction amount 409 as the difference between the color difference ΔE407 and the color difference ΔE408.

[0064] In FIG. 4, a color obtained by correcting color 405 by a color difference correction amount 409 on the extension line from color 406 to color 405 in the CIE-L*a*b* color space is shown as color 410. In the present embodiment, thus, color 410 calculated by the color conversion process after the color degradation correction will be described as a color existing on the extension line from color 406 to color 405. However, if the color difference from color 406 to color 410 is equal to or greater than the total value of color difference ΔE408 and color difference correction amount 409, it is not particularly limited in this way. For example, color 410 may be a color at a position separated by a distance equal to the total value of color difference ΔE408 and color difference correction amount 409 in any direction of the lightness direction, the chroma direction, or the hue angle direction from color 406 in the CIE-L*a*b* color space. Also, color 410 may be a color separated by the total value of color difference ΔE408 from color 406 and color difference correction amount 409 in consideration of not only one direction but also the lightness direction, the chroma direction, and the hue angle direction respectively.

[0065] In the example of FIG. 4, the color conversion parameters were corrected so that the color after conversion of color 403 changed from color 405 to color 410. However, if the color difference between the two colors after conversion is the discriminable color distance as described above, for example, the color after conversion of color 404 may be made different from color 405, or the colors after conversion of both color 403 and color 404 may be made different from the colors before correction. In the example of FIG. 4, when trying to correct color 406 by the color difference correction amount 409 on the extension line from color 405 to color 406 in the CIE-L*a*b* color space, it would go outside the color gamut 402 and such correction could not be performed. Therefore, when changing the color after conversion of color 404 by correcting the conversion parameters, the color is set on the boundary surface of the color gamut 402 and the color distance from color 405 is the discriminable color distance. Here, if changing only the color after conversion of color 404 does not reach the discriminable color distance between the two colors after conversion, the shortage to the discriminable color distance may be compensated by correcting the conversion parameters so as to change the color after conversion of color 403.

[0066] In S206, the CPU 102 corrects the gamma mapping table using the result of the color fade correction in S205 to obtain a post-color fade correction table. Here, the gamma mapping table before correction is a table that converts the input color, color 403, to the output color, color 405, and the post-color fade correction table is a table that converts the input color, color 403, to the output color, color 410. From the result of S205, the output color of color 403 as the input color is changed to a table that converts to color 410. The correction of the gamma mapping table is repeatedly executed for all combinations of colors where color fade occurs. Through such processing, a post-color fade correction table is created.

[0067] According to the process shown in FIG. 3, after creating a post-color fade correction table and performing the conversion of the input image using such a table, in the unique color combinations of the input image, the color distance can be increased for the color combinations that will cause color fade after conversion. Therefore, the degree of color fade in the color combinations that cause color fade due to conversion can be reduced.

[0068] When the input image data is sRGB data, the gamma mapping table is created on the premise that the input image data has 16,777,216 colors. The gamma mapping table created under this premise is created considering color fade and saturation for all colors not included in the actual input image data. According to the process shown in this embodiment, by correcting the conversion parameters only for the colors detected in the input image data that will cause color fade after conversion, an adaptive post-fade correction table can be created for the input image data. Therefore, it is possible to execute a color conversion process with a reduced degree of color fade through gamma mapping suitable for the input image data.

[0069] Note that the processes described with reference to FIGS. 3 and 4 are executable for both the first manuscript data and the second manuscript data. In this embodiment, the description will be made assuming that the same processes are separately performed for the first manuscript data and the second manuscript data, respectively.

[0070] Note that in this embodiment, the process in the case where the input image data is a single-page image has been described, but the number of pages of the input image data is not particularly limited. When the input image data has multiple pages, the flow shown in FIG. 2 may be performed for all pages, or may be performed for each page. According to such a process, even when the input image data has multiple pages, when color degradation occurs during printing of the image, it is possible to reduce the degree of such color degradation.

[0071] Also, in this embodiment, a degenerate correction post table is created by correcting the gamma mapping table, but if the color difference after conversion is the same value, it is not particularly limited to such a process. For example, the gamma mapping table before color degradation correction may be directly used for the image data after gamma mapping, and further color conversion may be performed using a different gamma mapping table. In that case, in S205, a table for converting from the color information converted by the gamma mapping data before correction to the color information after color degradation correction is created as the gamma mapping post correction table. The gamma mapping post correction table generated here is a table for converting color 405 in FIG. 4 into color 410 as input. In this case, in S105, the color conversion process is executed by applying the gamma mapping post correction table to the image data after gamma mapping.

[0072] Also, in the present embodiment, the processes shown in FIGS. 2 and 3 are assumed to be started automatically in response to receiving input of image data, but may be configured to be executed based on a user instruction. For example, the CPU 102 may be configured to receive a user input as to whether to execute each information process according to the present embodiment on a UI screen as shown in FIG. 20 described later. On the UI screen of FIG. 20, a toggle button for selecting the type of color correction is displayed. Also, on the UI screen of FIG. 20, a toggle button for selecting whether to execute gamma mapping using an adaptive degenerate correction post table by ON and OFF is displayed. According to such a configuration, it is possible to switch whether to execute adaptive gamma mapping according to a user instruction. As a result, when the user wants to reduce the degree of color degradation, adaptive gamma mapping can be executed.

[0073] In the present embodiment, the description has been made assuming that a degenerate correction post table is created separately for the first original data and the second original data. However, when creating a degenerate correction post table for the second original data, information about the first original data may also be additionally used. For example, in S202, the CPU 102 may also use the unique colors detected in S201 for the first original data in addition to the unique colors detected in S201 for the second original data to detect combinations of colors that cause color degradation. By doing so, for the second original data, color degradation correction is performed in consideration of the colors used in the first original data, and the degree of color degradation can be reduced so that the overall original data does not appear unnatural in the finally formed image.

[0074] [Embodiment 2] [Correction of Repulsion Force within the Same Hue] The information processing apparatus 101 according to Embodiment 1 detected the number of color combinations that cause color degradation for all unique color combinations included in the image data, and performed color degradation correction processing for each of them. On the other hand, there may be cases where it is considered that color degradation does not occur even without determining whether color degradation occurs, such as color combinations with significantly different hues. Therefore, the information processing apparatus 101 according to Embodiment 2 groups a part corresponding to the hue range among the detected plurality of unique colors as one color group, and performs color degradation correction processing within the group. Hereinafter, when simply referred to as a "group", it refers to a group in which unique colors are grouped as one color group in this way. Also, in this embodiment, the first divided image (document data) and the second divided image are not distinguished, and may be referred to as image data, an image, or document data.

[0075] The information processing apparatus 101 according to this embodiment can group, for example, the detected unique colors for each predetermined hue angle, and perform the same color degradation correction processing as in Embodiment 1 within the group. By grouping a part rather than the entire detected unique colors as one color group and performing color degradation correction processing only for that part, it is possible to reduce the processing load and processing time by reducing the number of combinations to be calculated.

[0076] Also, in this embodiment, when performing color degradation correction, the color degradation correction may be performed so that the change due to the color degradation correction of the converted color occurs only in the lightness direction. By making the change in the color after color conversion by correcting the conversion parameters occur only in the lightness direction, it is possible to suppress the change in color tone due to the correction of the conversion parameters. In this embodiment, for example, as shown in FIG. 7 described later, based on the lightness of the input color, the lightness after the color conversion processing after correcting the conversion parameters is determined, and the correction of the conversion parameters may be performed so that the chroma does not change from before the correction.

[0077] When the color difference ΔE before gamma mapping is greater than the minimum distinguishable color difference, the color difference ΔE to be maintained only needs to be greater than the minimum distinguishable color difference. In such a case, in the color conversion by gamma mapping, it is conceivable to set the conversion parameters so that the color difference after conversion of the two colors approaches the color difference before conversion. From such a perspective, the information processing apparatus 101 according to the present embodiment may correct the conversion parameters so that the color after conversion is determined based on the color after conversion and the color difference before conversion of the combined colors. By the color degradation correction, the color difference after gamma mapping of the two colors becomes the color difference before gamma mapping, so that the ease of discrimination before gamma mapping can be reproduced even after the color conversion. Note that the color difference after gamma mapping after such color degradation correction may be greater than the color difference before gamma mapping. In this case, after the color conversion, the discrimination between the two colors can be made easier than before gamma mapping. Hereinafter, such correction processing of the conversion parameters will be described.

[0078] Hereinafter, with reference to FIG. 5, an example of the determination process of whether color degradation occurs, which is performed by the information processing apparatus 101 according to the present embodiment in S202, will be described. FIG. 5 is a diagram showing two axes of the a* axis and the b* axis in the CIE-L*a*b* color space as a plane, and plotting a plurality of unique colors. In the present embodiment, as described above, the unique colors within a predetermined hue angle are grouped as one color group. The hue range 501 represents a range in which a plurality of unique colors within a predetermined hue angle are regarded as one color group. In FIG. 5, the hue angle of 360 degrees is equally divided into six parts, and the hue range 501 represents a range from 0 degrees to 60 degrees. The hue range used for grouping is preferably a hue range that can be recognized as the same color and can be arbitrarily set by the user. For example, in the CIE-L*A*B* color space, the hue range grouped as one color group may be set in the range of 30 degrees to 60 degrees. When this angle is 60 degrees, it can be considered that the six color groups of red, green, blue, cyan, magenta, and yellow are grouped and separated. When this angle is 30 degrees, it can also be separated by the colors between the colors grouped at 60 degrees.

[0079] Note that, as shown in FIG. 5, a hue range grouped at a fixed angle may be set, or a hue range may be set according to the unique colors included in the image data. For example, the range of hue angles may be determined respectively within a range set so as to visually appear evenly (the same color), and unique colors may be grouped respectively within the range of hue angles set in this way.

[0080] Also, in the present embodiment, the description will be made assuming that the color degradation correction process is performed using the unique colors within one group grouped using the hue angle. However, the calculation process of the number of combinations in which color degradation occurs hereinafter may be performed using the unique colors included in two adjacent groups whose hue angle ranges are adjacent. By detecting such combinations across adjacent hue ranges, it is possible to suppress a sharp change in the number of color combinations in which color degradation occurs when the region for detecting combinations is shifted by one. In this case, if the range that is easily recognized as the same color is 30 degrees in the CIE-L*A*B* color space, by setting the hue angle range for one grouping to 15 degrees, the hue angle becomes 30 degrees when two hue ranges are combined. Therefore, it is possible to detect combinations from within the hue angle range that is easily recognized as the same color.

[0081] The CPU 102 calculates the number of color combinations that cause color degeneracy for unique color combinations within the hue range 501. In FIG. 5, colors 504, 505, 506, and 507 are shown as the colors included within the hue range 501. The CPU 102 according to the present embodiment determines whether color degeneracy occurs by color conversion processing for all combinations of the four colors 504, 505, 506, and 507. Such determination processing is repeated for all hue ranges. By such processing, it is possible to detect color combinations that cause color degeneracy for each hue range and calculate the number of such combinations. In FIG. 5, there are a total of six color combinations within the hue range 501. Detection of color combinations that cause color degeneracy can be performed in the same manner as in Embodiment 1. In the following, when explaining color combinations (two colors), it is assumed that the explanation is for combinations within one hue range unless otherwise specified.

[0082] The CPU 102 according to this embodiment selects a reference color (reference color) from among the unique colors included in the grouped color groups, and corrects the conversion parameters in the color conversion process so that the color after conversion of the other colors is determined based on the color difference between the other colors and the reference color. Further, the CPU 102 according to this embodiment can generate a function (brightness conversion function) for calculating the brightness of the color output from the brightness of the input color in the color conversion process after correction of the conversion parameters, based on the brightness of such a reference color and the brightness of a color different from the reference color (hereinafter referred to as a scale color). In this embodiment, two scale colors, one with a higher brightness and one with a lower brightness, are set for the reference color, and the above-mentioned brightness conversion function is generated based on the reference color and the two scale colors. The brightness conversion function will be described later as Equation (8). Here, the color 603 (and its converted color 607) in FIG. 6 to be described later is the reference color, the color 601 (and its converted color 605) is the scale color, and based on the color difference between the colors 605, 607, and the colors 603 and 601, the converted color 612 (or color 614) of the color 601 by the degenerate correction gamma mapping is calculated, and such processing will also be described later.

[0083] Hereinafter, with reference to FIG. 6, an example of the color degenerate correction process performed by the information processing apparatus 101 according to this embodiment in S205 will be described. In FIG. 6, on a plane using two axes, the L* axis and the C* axis in the CIE-L*a*b* color space, the color gamut of the input image data before the color conversion process is shown as the color gamut 617, and the color gamut after conversion by gamma mapping is shown as the color gamut 616. L* represents brightness and C* represents chroma. Further, the colors 504 to 507 included in the hue range 501 before the color conversion process are plotted in the color gamut 617 as the colors 601 to 604, respectively. Also, the colors 605 to 607 are the colors on the color gamut 616 after converting the colors 601 to 603 by gamma mapping, respectively. Here, it is assumed that the color 604 is the same color even after color conversion by gamma mapping.

[0084] The CPU 102 according to this embodiment can calculate a correction rate, which is the reflection rate of the correction of the conversion parameter in the color degradation correction, based on the ratio (proportion) of the number of color combinations in which color degradation occurs to the number of color combinations included in the group. For example, the CPU 102 according to this embodiment calculates the correction rate R in a certain group as follows. R = the number of color combinations in which color degradation occurs / the number of color combinations included in the group

[0085] The above correction rate R becomes smaller as the proportion of the color combinations in which color degradation occurs within the group becomes smaller, and becomes larger as it becomes larger. For example, in the examples of FIGS. 5 and 6, the number of color combinations within the group is 6, and when it is determined that color degradation occurs in 4 of those combinations, the correction rate R is calculated as 0.667. By performing the correction of the conversion parameter using such a correction rate, the degree of correction of color degradation can be strengthened as the proportion of the color combinations in which color degradation occurs within the group becomes larger.

[0086] The CPU 102 according to this embodiment can set the above-described reference color from among the unique colors included in the group. In this embodiment, among the unique colors included in the group, the color with the highest chroma (maximum chroma color) is set as the reference color. Further, the CPU 102 sets the color with the highest lightness (maximum lightness color) and the color with the lowest lightness (minimum lightness color) as scale colors with respect to the reference color. In the example of FIG. 6, color 601 is the maximum lightness color, color 602 is the minimum lightness color, and color 603 is the maximum chroma color.

[0087] In the color degradation correction, the CPU 102 according to this embodiment generates corresponding lightness conversion functions for the unique colors (light color group) whose lightness is equal to or higher than the lightness of the maximum chroma color and the unique colors (dark color group) whose lightness is lower than the maximum chroma color, respectively. Hereinafter, the calculation process of the correction amount based on the correction rate R, the maximum lightness color, the minimum lightness color, and the maximum chroma color performed by the CPU 102 according to this embodiment will be described.

[0088] The CPU 102 separately calculates the correction amount Mh in the light color group and the correction amount Ml in the dark color group (details regarding the use of these correction amounts will be described later). In the following, the color 601, which is the maximum brightness color, is represented by L601, a601, and b601. Also, the color 602, which is the minimum brightness color, is represented by L602, a602, and b602. Further, the color 603, which is the maximum chroma color, is represented by L603, a603, and b603. Here, the CPU 102 may use, for example, a value obtained by multiplying the color difference ΔE between the maximum brightness color and the maximum chroma color by the correction rate R as the correction amount Mh. Also, the CPU 102 may use a value obtained by multiplying the color difference ΔE between the maximum chroma color and the minimum brightness color by the correction rate R as the correction amount Ml. An example of the calculation formulas for the correction amount Mh and the correction amount Ml is shown as the following formulas (6) and (7).

Equation

[0089] In FIG. 6, the color difference between the color 601 and the color 603 is indicated by the color difference ΔE608, and the color difference between the color 602 and the color 603 is indicated by the color difference ΔE609. Therefore, the correction amount Mh and the correction amount Ml are values obtained by multiplying the such color differences ΔE608 and ΔE609 by R, respectively.

[0090] The CPU 102 according to the present embodiment generates a brightness conversion table for each hue range. The brightness conversion table according to the present embodiment is a table showing the brightness of the output pixel (converted brightness) by gamma mapping after color degradation correction with respect to the brightness of the input pixel. Hereinafter, a method for creating such a brightness correction table will be described.

[0091] The brightness conversion table according to this embodiment is a 1D LUT. Such a 1D LUT has a smaller dosage compared to a 3D LUT with a large number of dynamic items, and a reduction in the processing time required for transfer is expected. The brightness after conversion stored in the brightness conversion table is based on the brightness of the reference color, the brightness of the input color, and the brightness of the maximum brightness color (or minimum brightness color), and the brightness and correction amount of the color obtained by gamma mapping the reference color. (In this embodiment, it is calculated separately for the light color group and the dark color group). In the following, the input color will be described as a color in the light color group, but when using a color in the dark color group, the same process can be performed using the minimum brightness color instead of the maximum brightness color.

[0092] Figure 7 is a graph showing an example of the components of the brightness conversion table according to this embodiment. In Figure 7, the horizontal axis represents the brightness of the input color in the brightness conversion table, and the vertical axis represents the output brightness. L605 to L611 in Figure 7 correspond to the brightnesses of 605 to 611 in Figure 6. That is, in Figure 7, the brightnesses after conversion of the maximum brightness color, the reference color, and the minimum brightness color by gamma mapping are shown as L605, L607, and L606, respectively. In the following, only the brightness L607 to L605 in the brightness range of the brightness group will be described in the graph of Figure 7.

[0093] L610 is the value output when L605 is input to the brightness conversion table, and is the value obtained by adding the correction amount Mh to L607. As shown in Figure 6, the color obtained by moving the color 607 by the correction amount Mh in the brightness direction is shown as color 610.

[0094] First, the color 610, and the colors 612 and 614 set based on the color 610 will be described. Such a color 610 is a color that has the color difference between the color 603 and the color 601 as the color difference from the color 607 in the lightness direction. The color 612 is the color obtained by moving the color 605 after conversion of the color 601 in the lightness direction so as to have such a lightness L610. By performing color degradation correction so that the color after color conversion becomes the color 612, the change in the color after color conversion is only in the lightness direction, and the change in hue due to correction of the conversion parameters can be suppressed. Also, due to the high sensitivity of the lightness difference in visual characteristics, by converting the color difference including the saturation into the lightness difference, it is possible to provide a color that is likely to feel that a larger color difference is added after conversion even with a small lightness difference in visual characteristics. Also, due to the relationship between the sRGB color gamut and the color gamut of the image forming apparatus, the lightness difference is likely to be smaller than the saturation difference. Therefore, by converting the color difference including saturation into the lightness difference again, it becomes possible to effectively utilize a narrow color gamut.

[0095] On the other hand, as illustrated in FIG. 7, it is also conceivable that the color 612 thus converted goes out of the color gamut 616. In such a case, the color 612 may be moved by color difference minimum mapping to become the color 614 within the color gamut 616, and such a color 614 may be set to be the color after conversion of the color 601 after color degradation correction. Color difference minimum mapping will be described later with reference to Expressions (10) to (14).

[0096] In the present embodiment, as shown in FIG. 7, the output value obtained by inputting the L607 of the reference color into the lightness conversion table remains L607. Also, as described above, L610 is the output value when the lightness L605 of the color after conversion of the maximum lightness color is input into the lightness conversion table. In the present embodiment, the value when a lightness value greater than L607 and smaller than L605 is input into the lightness conversion table is calculated based on L607 and L610. For example, as shown in the graph of FIG. 7, the output value L2 when the lightness L1 greater than L607 and smaller than L605 is input into the lightness conversion table can be calculated by the following Expression (8) which is a lightness conversion function. L2 = L607+(L610 - L607)×(L1 - L607) / (L605 - L607) Equation (8)

[0097] A table that outputs such a value L2 with L1 as the input is calculated as the lightness conversion table in the light color group. For each color after conversion by gamma mapping, its lightness is converted by the lightness conversion table, and for a color that needs to be moved, such as color 614 relative to color 612, the moved color becomes the color after conversion by gamma mapping with color shrinkage correction in this embodiment.

[0098] Here, it is assumed that the lightness conversion function is generated as in Equation (8) based on two points, but it is not particularly limited as long as the corresponding lightness output is calculated. For example, assuming that the lightness conversion function is a quadratic function, the parameters of the lightness conversion function may be calculated from three points.

[0099] In this embodiment, as described above, the L607 of the reference color does not change due to the input to the lightness conversion table. By such processing, for the color with the highest chroma, the color difference can be corrected while maintaining the chroma by maintaining the converted color. Also, when an input value greater than L605 or less than L606 in lightness is input to the lightness conversion table, the output value is undefined here because it is not included in the input image data, but in that case, Equation (8) may be applied for calculation or the like.

[0100] FIG. 8 is a diagram for explaining the entire image including the first original data and the second original data according to this embodiment. The divided image 810 is the first original data, the divided image 820 is the second original data, and the image 800 is the entire image combining those original data. The boundary 801 is the boundary line between the original data. Here, the following description is made assuming that the information processing apparatus 101 first receives the divided image 810 and then receives the divided image 820.

[0101] The divided image 810 includes objects of colors 811, 813, 814, and 812 in descending order of lightness as colors, and each is displayed as a rectangular pattern. Further, the divided image 810 includes objects of colors 821, 823, 824, and 822 in descending order of lightness as colors, and each is displayed as a rectangular pattern. Here, it is assumed that color 811 and color 821 are the same color. Also, each color included in FIG. 8 is included in the hue range 501 of FIG. 5. Here, it is assumed that color 821 corresponds to color 601 of FIG. 6. Here, the color degenerate correction post-table for the divided image 810 is performed as described with reference to FIGS. 6 and 7.

[0102] FIG. 9 is a diagram for explaining the lightness difference correction performed by the information processing apparatus 101 for the divided image 820 according to the present embodiment. In FIG. 9, similar to FIG. 6, on a plane using two axes of the L* axis and the C* axis in the CIE-L*a*b* color space, the color gamut of the input image data before the color conversion process is shown as color gamut 617, and the color gamut after being converted by gamut mapping is shown as color gamut 616.

[0103] Here, in the divided image 820, the explanation will be given assuming that color degenerate occurs only between color 821 and color 822. In the example of FIG. 9, color 821 is plotted as color 601 and color 822 is plotted as color 901 within the color gamut 617. Also, color 605 and color 902 are colors on the color gamut 616 after converting color 601 and color 901 by gamut mapping, respectively. Here, it is assumed that color 601 is the maximum chroma color and the maximum lightness color is 901. Therefore, the correction amount Mh is the value obtained by multiplying the color difference ΔE903 between color 601 and color 901 by R, and the correction amount Ml is 0.

[0104] Also, as in FIG. 7, an example of components when a lightness conversion table is created for the divided image 820 is shown in FIG. 10. In the example of FIG. 9, the color obtained by moving the color 905 by the correction amount Mh in the lightness direction is shown as the color 904, and the lightness L904 thereof is the value output when the lightness L902 of the color 902 is input to the lightness conversion table shown in FIG. 10. Also, for the lightness conversion table shown in FIG. 10, the output value when the lightness L605 is input is L605. Also, the colors 905 and 906 in FIG. 9 are colors set based on the colors 902 and 904 in the same manner as the colors 612 and 614 in FIG. 6, respectively.

[0105] According to such processing, even when the divided images are sequentially received, color fade correction is performed on each of them as soon as they are received, and color mapping to the print color gamut can be performed so that the degree of color conversion caused by color conversion becomes small.

[0106] Also, when the lightness value output by conversion using the lightness conversion table for the maximum lightness color exceeds the maximum lightness of the color gamut 616 after gamma mapping, the CPU 102 may perform maximum value clipping processing. The maximum value clipping processing according to the present embodiment is a process of subtracting the difference between such an output lightness value and the maximum lightness of the color gamut 616 after gamma mapping from the entire output of the lightness conversion table. In this case, the lightness of the maximum chroma color after gamma mapping also changes to the low lightness side. According to such processing, even when the unique colors of the input image data are biased toward the high lightness side, overall correction can be performed so as to use the lightness gradation on the low lightness side as well. Also, for the minimum lightness color, when the minimum lightness after correction is lower than the minimum lightness of the color gamut after gamma mapping, the same processing can be performed when the lightness value output by conversion using the lightness conversion table exceeds the minimum lightness of the color gamut 616 after gamma mapping.

[0107] The CPU 102 according to this embodiment creates a degenerate correction table for each hue range by correcting the gamma mapping table using the values of the brightness conversion table calculated in this way. Here, for each corresponding input, the degenerate correction table is created by correcting the brightness value of the output of the gamma mapping table to the value of the output of the brightness conversion table.

[0108] In this embodiment, a brightness conversion table is created for each hue range. However, when performing processing using different tables for each such hue range, it is conceivable that a sharp change may occur in the output value depending on whether or not the boundary of the hue range is crossed. From such a perspective, when performing gamma mapping of a color in a certain hue range, the CPU 102 may additionally use the brightness conversion table of one adjacent hue range to perform color conversion processing. The CPU 102 may calculate the brightness after gamma mapping of a color by weighted-summing the brightness converted by the brightness conversion table in the hue range and the brightness converted by the brightness conversion table in the hue range. For example, when performing color conversion of a color C located at a hue angle of Hn degrees (here, assumed to be an angle within the hue range 501 in FIG. 5), the value Lc of the brightness after color conversion can be calculated as shown in the following formula (9).

Equation

[0109] Here, H 501 is the intermediate hue angle of the hue range 501, and H 502 is the intermediate hue angle of the hue range 502. Also, Lc 501 is the value obtained by converting the brightness of color C using the brightness conversion table in the hue range 501, and Lc 502 is the value obtained by converting the brightness of color C using the brightness conversion table in the hue range 502. According to such processing, by performing brightness conversion taking into account the brightness conversion tables of adjacent hue ranges, a sharp change at the boundary of the hue range of the output value due to gamma mapping can be suppressed.

[0110] Also, as described above, for the CPU 102 according to the present embodiment, for a color that goes outside the color gamut 616 in the color degradation correction using the output brightness of the brightness conversion table as it is, such as color 612, the value after such conversion is converted to a value within the color gamut by color difference minimum mapping. In the example of FIG. 6, as described above, color 612 is converted to color 614 by color difference minimum mapping. Hereinafter, such color difference minimum mapping will be described.

[0111] For example, the CPU 102 can convert color 612 to the color closest to color 612 among the colors within the color gamut 616 located in a predetermined direction from color 612 by color difference minimum mapping. The relationship between the weight for setting such a predetermined direction and the distance ΔEw from color 612 to the color after conversion (here 614) at that time can be expressed by the following formulas (10) to (14).

Equation

[0112] Here, the color before conversion by color difference minimum mapping is represented as (Ls, as, bs), and the color after conversion is represented as (Lt, at, bt). Also, as the weight for setting the above-described predetermined direction, the weight in the brightness direction is represented as Wl, the weight in the chroma direction is represented as Wc, and the weight of the hue angle is represented as Wh (Wh + Wl + Wc = 1). By searching for (Lt, at, bt) that satisfies formula (14), the color of the conversion destination by color difference minimum mapping is determined.

[0113] Here, the values of Wl, Wc, and Wh can be arbitrarily set by the user. In Embodiment 2, since the degenerate correction table is created such that the change due to the color degenerate correction of the converted color is only in the lightness direction, if one wants to maintain such an effect as much as possible, it is conceivable to make the weight in the lightness direction larger than the other weights. Also, since the hue has a great influence on the color tone, by making the weight of the hue angle larger (for example, than the weights in the lightness direction and the saturation direction), the change in the color tone before and after the color degenerate correction can be suppressed. For example, the relationship of these weights can be set as Wh>Wl>Wc to perform minimum color difference mapping.

[0114] Note that in the minimum color difference mapping, the description was given assuming that color 614 is searched from among the colors located in a predetermined direction from color 612. However, the process of converting a color that is located outside the color gamut after the degenerate correction, such as color 612, into the color gamut is not particularly limited in this way. For example, color 612 may be moved into the color gamut 616 with the minimum moving distance while maintaining the distance from color 607, and the resulting color may be used as color 614 so as to be the converted color of color 601 after the color degenerate correction.

[0115] In this embodiment, an example of performing color degenerate correction was described such that the change due to the color degenerate correction of the converted color is only in the lightness direction. Here, as a visual characteristic, the sensitivity to the lightness difference varies depending on the saturation. For example, the lightness difference between low-saturation colors is more likely to have a higher sensitivity than the lightness difference between higher-saturation colors of such colors. From such a viewpoint, the CPU 102 according to this embodiment may perform control such that the amount of change in the lightness direction of the color after the color degenerate correction further varies depending on the saturation value. Here, the colors are classified into low-saturation colors and high-saturation colors, and for high-saturation colors, the process is performed as described with reference to FIG. 6 and the like, and for low-saturation colors, the process is performed such that the amount of change in the lightness direction of the converted color becomes smaller. In the following, an explanation will be given of the color degenerate correction performed such that the amount of change in the lightness direction becomes smaller for the colors determined to be such low-saturation colors.

[0116] When the CPU 102 corrects the brightness value of the output of the gamma mapping table to the value of the output of the brightness conversion table, it uses the chroma correction rate S to internally divide the brightness value Ln before such correction and the brightness value Lc after correction to obtain Lc’, and sets Lc’ as the brightness value of the output of the table after degeneracy correction. The chroma correction rate S is calculated by the following formula (15) using the chroma value Sn of the output value of gamma mapping and the maximum chroma value Sm of the color gamut after gamma mapping at the hue angle of the output value of gamma mapping. Also, Lc’ is calculated by the following formula (16). S = Sn / Sm Formula (15) Lc’ = S × Lc + (1 - S) × Ln Formula (16)

[0117] Here, the conditions for classifying colors into low-chroma and high-chroma are not particularly limited and can be arbitrarily set according to the user or the environment. For example, a predetermined threshold may be set for chroma, and chroma above the threshold may be defined as high-chroma, and chroma below the threshold may be defined as low-chroma. Also, for example, the lower half of the detected chroma may be defined as low-chroma and the rest as high-chroma. Further, the CPU 102 may perform color degeneracy correction so that the change amount of the color after conversion becomes zero for low-chroma colors.

[0118] According to such processing, color degeneracy correction can be performed in accordance with visual sensitivity, and a state where the degree of correction is too strong can be suppressed. For example, for colors on the gray axis, etc., changes due to color degeneracy correction can be suppressed.

[0119] [Embodiment 3] [Hue Repulsion] Even for colors existing within different hue ranges, when the brightness difference becomes small after gamma mapping, it may become difficult to distinguish them. From such a perspective, when the brightness difference between the gamma mappings of two colors decreases below a predetermined threshold (color difference ΔE), the information processing apparatus 101 according to this embodiment can perform color degeneracy correction so that such a brightness difference increases.

[0120] The information processing apparatus 101 according to the present embodiment can perform the same color fading correction process as in Embodiment 1. Hereinafter, the differences in the color fading correction process performed by the information processing apparatus 101 between the present embodiment and Embodiment 1 will be described. Note that the color fading correction process described below can be similarly performed for both the first divided image and the second divided image.

[0121] Hereinafter, with reference to FIG. 11, an example of the determination process of whether or not brightness fading occurs, which is performed by the information processing apparatus 101 according to the present embodiment in S202, will be described. In the present embodiment, as described above, the case where the brightness difference after the gamma mapping of two colors decreases to a predetermined color difference ΔE or less is referred to as brightness fading. Further, the CPU 102 according to the present embodiment determines that color fading has occurred when brightness fading has occurred.

[0122] In S202, the CPU 102 detects a combination of colors in which brightness fading occurs from the combinations of unique colors included in the image data based on the unique color list detected in S201. In FIG. 11, on a plane using two axes of the L* axis and the C* axis in the CIE-L*a*b* color space, the color gamut of the input image data before the color conversion process is shown as color gamut 1101, and the color gamut after being converted by gamma mapping is shown as color gamut 1102. The input image data includes color 1103 (first color) and color 1104 (second color), which are shown on color gamut 1101. Colors 1105 and 1106 are colors on color gamut 1102. Color 1105 is the color when gamma mapping is performed on color 1103, and color 1106 is the color when gamma mapping is performed on color 1104. The process described below is repeated for all combinations of unique colors included in the image data.

[0123] Here, when the brightness difference 1108 between color 1105 and color 1106 is smaller than the brightness difference 1107 between color 1103 and color 1104, the CPU 102 determines that the brightness difference has decreased. Here, it is assumed that the brightness difference in the CIE-L*a*b* color space is calculated. The color information in the CIE-L*a*b* color space is represented by a three-axis color space of L*, a*, and b* respectively. Color 1103 is represented by L1103, a1103, and b1103. Color 1104 is represented by L1104, a1104, and b1104. Color 1105 is represented by L1105, a1105, and b1105. Color 1106 is represented by L1106, a1106, and b1106. When the input image data is represented in another color space, it may be converted to the CIE-L*a*b* color space by known color space conversion techniques, or subsequent processing may be performed in that color space as it is. The brightness difference ΔL1107 and the brightness difference ΔL1108 are calculated by, for example, the following equations (17) and (18). [Number]

[0124] When the brightness difference ΔL1108 is smaller than the brightness difference ΔE1107, the CPU 102 determines that the brightness difference has decreased. Further, when the brightness difference ΔL1108 is less than or equal to a predetermined threshold value, the CPU 102 determines that there is not enough difference to distinguish those colors and that brightness degradation has occurred.

[0125] If the brightness difference between color 1105 and color 1106 is large enough to be distinguishable as different colors in terms of human visual characteristics, it can be determined that there is no need to correct the brightness difference. From this perspective, the threshold value used here can be, for example, 0.5. The CPU 102 may determine that brightness degradation has occurred when the brightness difference ΔL1108 is smaller than the brightness difference ΔL1107 and the brightness difference ΔL1108 is smaller than 0.5.

[0126] Next, the color degradation correction process performed in S205 according to this embodiment will be described with reference to FIG. 11.

[0127] The CPU 102 according to this embodiment can calculate a correction rate T, which is the reflection rate of the correction of the conversion parameter in color degradation correction, based on the ratio of the number of color combinations that cause lightness degradation to the total number of color combinations in the unique color list. For example, the CPU 102 related to this embodiment calculates the correction rate T as follows. T = (Number of color combinations that cause lightness degradation) / (Total number of color combinations in the unique color list)

[0128] The above correction rate T decreases as the ratio of the color combinations that cause lightness degradation in the unique color list decreases, and increases as the ratio increases. By performing the correction of the conversion parameter using such a correction rate, it is possible to strengthen the degree of correction of color degradation as the ratio of the color combinations that cause lightness degradation increases.

[0129] Next, the CPU 102 performs lightness difference correction based on the correction rate T and the lightness before gamma mapping. The lightness Lc after the lightness difference correction can be calculated, for example, by the following formula (19), as the value obtained by interpolating between the lightness Lm before gamma mapping and the lightness Ln after gamma mapping with the correction rate T. Lc = T × (Lm - Ln) + Ln (Formula (19))

[0130] Such lightness difference correction is repeated for all unique colors in the input image data. In FIG. 11, the lightness L1105 of color 1105 is subjected to lightness difference correction using the correction rate T, and the result of the correction is shown as color 1109. In the example of FIG. 11, since color 1109 is outside the color gamut 1102 after gamma mapping, it is mapped to the color gamut 1102 and becomes color 1110. The same process is performed for color 1104. According to such a process, it is possible to perform gamma mapping with an increased lightness difference for the colors included in the image data, and when lightness degradation occurs, the degree thereof can be reduced. Therefore, by suppressing the state where the lightness difference after gamma mapping becomes too small, it is possible to reduce the decrease in discriminability.

[0131] Note that the reduction process for brightness degradation according to this embodiment may be performed simultaneously with the process according to Embodiment 2. In that case, the brightness difference correction process is performed with respect to the reference color of the color degradation correction process. Along with correcting the brightness difference of the reference color, the brightness difference correction of other colors can also be processed. According to such a configuration, when performing color degradation correction, it is possible to reduce not only the degree of color degradation but also the degree of brightness degradation.

[0132] [Embodiment 4] [Referencing Processed Correction Values] In Embodiments 1 to 3, an example of generating a color degradation correction table separately for the first divided image and the second divided image has been described. However, if a color degradation correction table is generated independently for each divided image, even if the colors are common between the divided images, they may appear as different colors after each color conversion process.

[0133] Hereinafter, a case will be described in which the same color appears as different colors as a result of performing color degradation correction independently between divided images. FIG. 12 is a diagram for explaining an example of a brightness conversion table for each divided image when color degradation correction is performed such that the same color appears as different colors between the divided images due to color degradation correction.

[0134] In FIG. 12, the brightness conversion table (the first brightness conversion table) described in FIG. 7 of Embodiment 2 and the brightness conversion table (the second brightness conversion table) described in FIG. 10 are displayed. Here, the first brightness conversion table is for the first divided image, and the second brightness conversion table is for the second divided image.

[0135] Here, when L605 is input to the first brightness conversion table, L610 is output, and when L605 is input to the second brightness conversion table, L903 is output. Therefore, for example, when an image 800 including a first divided image 810 and a second divided image 820 shown in FIG. 8 is input, the brightness of the color after conversion of the same color, i.e., color 811 and color 821, will be different across the boundary 801. In particular, when objects of color 811 and objects of color 821 are continuous on the original manuscript as in the image 800, such differences in the color after conversion are likely to be recognized.

[0136] To reduce such a sense of incongruity, the information processing apparatus 101 according to the present embodiment uses, for a part of the conversion parameter that becomes the value of the color degradation correction table in the second divided image received subsequent to the first divided image, the conversion parameter set for the first divided image.

[0137] For example, consider a case where a common color (a third color) is included in the first divided image and the second divided image, and the third color is converted to a fourth color by the color degradation correction table in the first divided image. In such a case, when the information processing apparatus 101 performs color degradation correction processing on the second image, the conversion parameter (color degradation correction table) is corrected so that the third color is converted to the fourth color.

[0138] The information processing apparatus 101 according to the present embodiment sets a color commonly included in the first divided image and the second divided image as a fixed color. For the color set as the fixed color, the information processing apparatus 101 corrects the conversion parameter so that it is converted to the same color by the color degradation correction table (the first table) in the first divided image and the color degradation correction table (the second table) in the second divided image. Here, it is assumed that the color commonly included in the first divided image and the second divided image is set as the fixed color. However, for example, on the image when the entire image is output, the color of an object continuous across the boundary between the first divided image and the second divided image may be set as the fixed color.

[0139] FIG. 13 is a flowchart showing an example of the overall processing performed by the information processing apparatus 101 according to the present embodiment. The processing shown in FIG. 13 repeats the loop processing of S302 to S309 for the divided images obtained by dividing the entire image into bands (unit printing areas). Here, the entire image is divided into M divided images with band numbers N = 1 to M, and the following description will be given assuming that the divided images are received by the information processing apparatus in ascending order of the band numbers. The processing shown in FIG. 13 is assumed to start in response to receiving a divided image. Also, the description of the processing performed in the same manner as in FIG. 2 in the processing of FIG. 13 will be omitted.

[0140] In S301, the CPU 102 sets the initial value of the band number N to be processed to 1. The loop processing of S302 to S309 performs different processing depending on whether N = 1 or not. First, the processing executed when N = 1 will be described.

[0141] In S302, the CPU 102 acquires the divided image of the band number to be processed. Here, the CPU 102 acquires the image data in the same manner as in S101.

[0142] In S303, the CPU 102 sets, as a fixed color, a color that is continuous (or commonly included) across the boundary between the divided image of the currently processed band number N and the divided image of the band number N - 1. This processing is not performed when N = 1.

[0143] In S304, the CPU 102 performs color conversion processing on the divided image to be processed. S304 is performed in the same manner as S102. In step S305, the CPU 102 creates a table after color fade correction in the divided image to be processed. S305 is performed in the same manner as S103 when N = 1. The processing in S305 when N ≠ 1 will be described later.

[0144] In S306, the CPU 102 uses the color degradation correction table created in S305 with the divided image acquired in S302 as the input to generate color degradation corrected image data after color degradation correction is performed. S306 is performed in the same manner as S104. In S307, the CPU 102 outputs the color degradation corrected image data stored in S306 from the information processing apparatus 101 via the transfer I / F 106.

[0145] In S308, the CPU 102 increments by 1 the band number N to be processed. In S309, the CPU 102 determines whether all band numbers have been processed. Here, if all band numbers have been processed, the process proceeds to S310, and the bundle loop process of S302 to S309 ends and the process of FIG. 13 ends. If all band numbers have not been processed, the process returns to S302.

[0146] Hereinafter, the processing of S303 to S305 when N is 2 or more (the second and subsequent loops of the band processing) will be described. In S303, the CPU 102 sets the color commonly included in the second divided image and the first divided image as the fixed color. In the example of FIG. 8, since color 811 and color 821 are continuous across the boundary 801, this color is set as the fixed color. S304 is performed in the same manner as S102 even when N is 2 or more.

[0147] In S305, for the second divided image, the CPU 102 creates the second table so that the color after conversion of the fixed color is the same as the color after conversion by the first table. Here, the second table is generated by the process described with reference to FIG. 3, in which the color after conversion of the fixed color is fixed to the color after conversion by the first table and the colors after conversion of other colors are changed, and the color degradation correction table after generation is the second table.

[0148] FIG. 14 is a diagram for explaining the creation process of the color degradation correction table when the color set to the fixed color is included in the second divided image. In FIG. 14, similar to FIG. 6, on the plane using the two axes of the L* axis and the C* axis in the CIE-L*a*b* color space, the color gamut of the input image data before the color conversion process is shown as color gamut 617, and the color gamut after being converted by gamut mapping is shown as color gamut 616. Also, colors 601 and 1401 included in the second divided image are plotted within color gamut 617. Further, color 1402 is the color on color gamut 606 after converting color 1401 by gamut mapping. In FIG. 14, color 601 is shown as the fixed color. Also, for the first divided image, a color degradation correction table for performing the conversion as shown in FIG. 6 is created. Therefore, in FIG. 14, the final conversion destination of color 601 is the same color 614 as in FIG. 6.

[0149] Also, in FIG. 14, it is assumed that color 601 is the maximum chroma color and the maximum lightness color is 1401. Therefore, the correction amount Mh is the value obtained by multiplying the color difference ΔE1401 between color 601 and color 1401 by R, and the correction amount Ml is 0.

[0150] Also in FIG. 14, as described with reference to FIGS. 6 and 7, a lightness conversion function is generated, and the color after conversion using the second table for each color including color 1401 is determined. FIG. 15 is a graph showing an example of components when a lightness conversion table is created for the second divided image shown in FIG. 14. In FIG. 15, the lightness conversion table for the second divided image is shown by a broken line, and the lightness conversion table for the first divided image is shown by the same solid line as that shown in FIG. 6. Also in FIG. 15, the lightness of the input color in the lightness conversion table is shown on the horizontal axis, and the output lightness is shown on the vertical axis. The slope of the lightness conversion function is calculated such that L610 is output when the lightness L605 is input, and L1404 is output when the lightness L1402 of color 1402 is input.

[0151] Here, the lightness L1404 of color 1405 is the value output when L1402 is input into the lightness conversion table, and it is the value obtained by adding the correction amount Mh to L614. In FIG. 14, the color obtained by moving color 614 by the correction amount Mh in the lightness direction is shown as color 1404, and the color obtained by moving the color 1402 after conversion of color 1401 in the lightness direction so as to have such lightness L1404 is color 1405. Further, since color 1405 has gone outside the color gamut 616 here, by the same process as moving color 612 to color 614 in FIG. 6, color 1405 is moved to color 1406 within the color gamut, and the second table is created so that such color 1406 becomes the color after conversion of color 1401 after color shrinkage correction.

[0152] Also, here, the lightness component in the first table is shown in FIG. 6, and the lightness component in the second table is shown in FIG. 15. In either case, the value output when L605 is input is L610, and when divided images having a common color are input respectively, the color will be output as the same color.

[0153] According to such processing, when the first divided image and the second divided image including a common color are input, for such a common color, the value in the first divided image can be diverted to the value in the table after color shrinkage correction in the second divided image. Therefore, it is possible to reduce the occurrence of discomfort caused by the converted colors being different for the common color in the first divided image and the second divided image. Also, even when performing the lightness difference correction processing described in Embodiment 3, by setting the correction rate T to 0 for the fixed color, it is possible to reduce the degree of color compression while maintaining the fixed color.

[0154] Here, an example in which only one color is set as the fixed color has been described. However, two or more fixed colors may be set. In this case, considering that it becomes difficult to perform the color degenerate correction itself as the number of fixed colors increases, for example, the number of fixed colors may be set to a predetermined threshold. Also, when the number of colors satisfying the fixed color condition exceeds a predetermined threshold, the fixed color may be selected from such colors in a order that satisfies a predetermined condition such as "in the order of decreasing number of pixels in the divided image" or "in the order of decreasing number of pixels in the entire pixels including the previously processed divided image". Further, the information processing apparatus 101 may select a fixed color from among the colors included in the divided image and having a predetermined number of pixels or more. By such processing, it is possible to reduce the occurrence of discomfort between divided images by using a plurality of fixed colors.

[0155] [Embodiment 5] [Consideration of Unprocessed Correction Value] When there is a common color between the first divided image and the second divided image, the information processing apparatus 101 according to Embodiment 4 sets that color as the fixed color and creates the second table. On the other hand, the brightness conversion function of the second table indicated by the broken line in FIG. 15 has a smaller slope (that is, a lower color degenerate correction intensity) than the brightness conversion function of the first table indicated by the solid line. Also, the value after conversion by the second table is overall brighter and has a higher brightness than the value after conversion by the first table. This is because at the time of the first table, L605 is brightly corrected to L610, and as a result, it is necessary to further correct it more brightly when reflected in the second table. In particular, this occurs because the first table is created independently of the second table with a color not present in the second divided image as the reference color.

[0156] From such a perspective, the information processing apparatus 101 according to the present embodiment estimates a color (common color) that is also commonly included in the second divided image among the colors included in the first divided image, and creates a post-color-degradation correction table in the first divided image using such a commonly included color as a reference color. The information processing apparatus 101 can estimate, for example, the color of a boundary portion of the first divided image that is adjacent to a second divided image received continuously with the first divided image as such a common color. Here, it is assumed that the second divided image is a divided image received subsequent to the first divided image as in the above-described embodiment, but the second divided image may be a divided image received immediately before the first divided image. Further, when a reference color is set in the first divided image, a post-color-degradation correction table may be created using the same color as the reference color also in the second divided image received subsequent to the first divided image.

[0157] Further, the information processing apparatus 101 may estimate, as such a common color, a color included in the color of a boundary portion of the first divided image that is adjacent to a subsequently received second divided image and that is included in the color of a boundary portion continuing from a third divided image received immediately before the first divided image. Here, the color of a boundary portion adjacent to another divided image refers to the color of a line with a width of one pixel at the outermost edge, but this boundary portion may have a width of two or more pixels.

[0158] FIG. 16 is a flowchart showing an example of the overall processing performed by the information processing apparatus 101 according to the present embodiment. The processing shown in FIG. 16 is performed in the same manner as that shown in FIG. 13 except that S303 is S401, and thus overlapping explanations are omitted.

[0159] In S401, the CPU 102 sets, as a reference color, the color of the boundary portion of the divided image to be processed that is adjacent to the divided image received continuously with the divided image. Here, the CPU 102 sets, as the reference color, the color that is the color of the boundary portion between the divided image of band number N and the divided image of band number N - 1 and is also the color of the boundary portion with band number N + 1. Also, when N = 1, the color of the boundary portion between the divided image of band number N and the divided image of band number N + 1 is set as the reference color. When there are a plurality of colors that satisfy such conditions, for example, the color with the highest chroma among them may be used as the reference color. Also, in order to prevent the background color from being selected as the reference color, a predetermined range of colors determined to be the background color may be set, and the reference color may be set from the colors excluding such a predetermined range.

[0160] In the example of FIG. 8, the divided image 810 is the first divided image and the divided image 820 is the second divided image. And, since the pixel color of the object existing at the boundary 801, which is the boundary portion adjacent to the divided image 820 in the divided image 810, is only the color 811, the color 811 is set as the reference color.

[0161] FIG. 17 is a diagram for explaining the creation process of the color degradation correction table when the color of the boundary portion with an adjacent divided image is used as the reference color for the divided image. In FIG. 17, the same colors 601 to 604 as those shown in FIG. 6 are plotted on a plane using two axes, the L* axis and the C* axis, in the CIE-L*a*b* color space. In the example of FIG. 17, different from the example described with reference to FIG. 6, the color 601 is set as the reference color. In this example, the correction amount Mh is the value obtained by multiplying the color difference ΔE608 between the color 601 and the color 603 by R, and the correction amount Ml is the value obtained by multiplying the color difference ΔE609 between the color 603 and the color 502 by R.

[0162] Also in FIG. 17, as described with reference to FIGS. 6 and 7, a lightness conversion function is generated, and the color after conversion using the color fade correction table is determined. FIG. 18 is a graph showing an example of components when a lightness conversion table is created for the divided image shown in FIG. 17 with color 601 as a reference point, with the solid line. In FIG. 18, the lightness of the input color in the lightness conversion table is shown on the horizontal axis, and the output lightness is shown on the vertical axis.

[0163] In the examples of FIGS. 6, 9, and 14, the lightness L after correction of the maximum lightness color becomes the lightness L + Mh of the maximum chroma color before correction (the lightness L after correction of the minimum lightness color becomes the lightness L - Ml of the maximum chroma color before correction so that the lightness conversion function is created. However, in FIG. 17, since color 601, which is the maximum lightness color, is used as the reference color, the lightness L after correction of the maximum chroma color becomes the lightness L - Mh of the maximum lightness color before correction, and the lightness conversion function is created so that the lightness L after correction of the minimum lightness color becomes the lightness L - Mh - Ml of the maximum lightness color before correction.

[0164] Also, when color 602, which is the minimum lightness color, is used as the reference color, the lightness conversion function shall be created so that the lightness L after correction of the maximum chroma color becomes the lightness L + Mh of the minimum lightness color before correction, and the lightness L after correction of the maximum lightness color becomes the lightness L + Mh + Ml of the minimum lightness color before correction. Regardless of whether the reference color is color 601, color 602, or any other color, the lightness L after correction of the maximum lightness color becomes the lightness L + Ml of the maximum chroma color after correction, and the lightness L after correction of the minimum lightness color becomes the lightness L - Ml of the maximum chroma color after correction.

[0165] Also, when the reference color is a color with a lightness between the maximum (minimum) lightness color and the maximum chroma color, lightness conversion functions may be generated separately for the lightness range from the maximum (minimum) lightness color to the reference color and the lightness range from the reference color to the maximum chroma color.

[0166] In FIG. 18, for inputs of L607 or less, when L606 is input, the output is L1702, and when L607 is input, the slope of the brightness conversion function is calculated such that the output is L1701. Also, for inputs of L607 or more, when L607 is input, the output is L1701, and when L605 is input, the slope of the brightness conversion function is calculated such that the output is L605. Further, components of the brightness conversion table created for the second divided image with color 601 as the reference color are indicated by a dashed line in FIG. 18.

[0167] As shown in FIG. 18, for color 601 which was converted to L605 before color fade correction in the first divided image and the second divided image, after color fade correction, the brightness after conversion is common at L605. Further, when compared with the example shown in FIG. 15, for the brightness conversion function in the first divided image and the brightness conversion function in the second divided image, the slope values are closer, and the difference in the overall brightness change is also smaller. Thus, by estimating a common color included in the second divided image from the colors included in the first divided image and creating a table after color fade correction with such a common color as the reference color, it is possible to reduce the difference in color fade correction between the first divided image and the second divided image and reduce the discomfort after conversion.

[0168] Also in this case, when performing the brightness difference correction process described in Embodiment 3, by setting the correction rate T to 0 with respect to the reference color, it is possible to reduce the degree of color compression while maintaining the fixed color.

[0169] Note that the common color estimation process is not particularly limited in this way as long as it estimates, as common colors, colors that are likely to be included in consecutive divided images. For example, the information processing apparatus 101 may start the process of creating a color degradation correction table for the first divided image after acquiring the second divided image, so as to acquire the color information included in the second divided image and then select a common color between the first divided image and the second divided image. Also, for example, when there is a color that indicates pixels at a predetermined ratio (e.g., 80%) or more with respect to the total number of pixels in the first divided image, the information processing apparatus 101 may estimate such a color as a common color.

[0170] [Embodiment 6] When there is a common color between the first divided image and the second divided image, the information processing apparatus 101 according to Embodiment 4 sets that color as a fixed color and creates a second table. For example, when performing such a fixed color setting, while the fixed color is converted to a common color between the divided images, different conversions are performed for colors that are not fixed colors, and as a result, there is a possibility that a sense of discomfort may occur.

[0171] From such a viewpoint, the information processing apparatus 101 according to the present embodiment generates a third parameter to be used in the color conversion process in the second divided image based on a parameter (hereinafter, the first parameter) included in the color degradation correction table created based on the color information in the first divided image and a parameter (hereinafter, the second parameter) included in the color degradation correction table created based on the color information in the second divided image.

[0172] For example, the information processing apparatus 101 may generate a third conversion parameter such that the color after conversion using the third parameter is determined based on the color after conversion using the first conversion parameter and the color after conversion using the second conversion parameter. In particular, the information processing apparatus 101 converts the sixth color at the first pixel position (position in raster units) of the second divided image based on the third parameter, and the seventh color obtained by the conversion is the eighth color obtained by converting the sixth color using the first conversion parameter and the ninth color obtained by converting the sixth color using the second conversion parameter. The third parameter can be generated so that the color after conversion is the color obtained by adding the weighted sum using the weight set for each pixel position of the second divided image. Based on this, the third conversion parameter can be generated. Hereinafter, such processing will be described with reference to FIG. 21.

[0173] FIG. 21 is a flowchart showing an example of the overall processing performed by the information processing apparatus 101 according to the present embodiment. The processing shown in FIG. 21 is executed in the same manner as that shown in FIG. 2 of Embodiment 1 except that S501 to S506 are performed following S108, so redundant explanations are omitted. In the present embodiment, the color degradation correction table based on the color information of the first divided image created in S103 is referred to as the first table, and the color degradation correction table based on the color information of the second divided image created in S108 is referred to as the second table. The following description will be made based on this assumption.

[0174] In S501, the CPU 102 starts the loop processing of S502 to S504 with one pixel position of the second divided image as the processing target. Here, it is assumed that the image at the upper left end of the second divided image is set as the processing target.

[0175] In S502, the CPU 102 generates a conversion parameter at the pixel position to be processed based on the first parameter and the second parameter. Here, taking each color as an input, the CPU 102 outputs the sum of the color after conversion by the first parameter and the color after conversion by the second parameter for each color, weighted by a weight set for each pixel position. A conversion table for each position (the third parameter) is generated by the CPU 102. Such a conversion table can be created by the following equation (20), for example, when the total number of raster lines of the second divided image is NR and the pixel position of the current raster to be processed is CR. Equation TableCR[Rin][Gin][Bin]=((NR - CR) × Table1[Rin][Gin][Bin] + CR × Table2[Rin][Gin][Bin]) ÷ NR Equation (20)

[0176] Here, the pixel position CR is counted with the top - left pixel as 1, incremented by 1 as it moves to the right, and when it reaches the right end, the next pixel position is the left end of the next row below. Also, here it is assumed that the divided images are a group of images arranged continuously from top to bottom.

[0177] According to such a table, for each pixel position of the second divided image, the weight for the ninth color in the weighted sum using the eighth color (Table1[Rin][Gin][Bin]) and the ninth color (Table2[Rin][Gin][Bin]) can be set so that the weight for the ninth color increases as the distance from the boundary between the first divided image and the second divided image increases.

[0178] By performing the conversion using such conversion parameters for each pixel position, a conversion result close to the conversion result using the first parameter is obtained at the upper end (the boundary with the first divided image) of the second divided image, a conversion result close to the conversion result using the second parameter is obtained at the lower end of the second divided image, and at the intermediate portion between them, a conversion result affected by both the first conversion parameter and the second conversion parameter can be obtained. As a result, it is possible to prevent a sharp change in the color after conversion between adjacent pixel positions, and it is possible to perform a conversion that is less likely to cause a sense of discomfort to the human eye.

[0179] In S503, the CPU 102 converts the pixel value of the pixel position to be processed in the second divided image based on the conversion parameter generated in S502. The converted pixel value generated here is stored in the RAM 103 or the storage medium 104 together with the information of the pixel position.

[0180] In S504, the CPU 102 determines whether or not all the pixel positions of the second divided image have been processed. If the CPU 102 has processed all the pixel positions, the process proceeds to S505. Otherwise, the process returns to S502 with the next pixel position as the processing target (CR is incremented by 1).

[0181] In S505, the CPU 102 reproduces the second divided image after conversion from the pixel values of each pixel position stored in S503 and outputs it from the information processing apparatus 101 via the transfer I / F 106.

[0182] According to such processing, it is possible to generate, for each pixel position, a conversion parameter for use in converting the second divided image using a conversion parameter based on the color information of the first divided image and a conversion parameter based on the color information of the second divided image, and to perform the conversion of the second divided image. Therefore, it is possible to perform color conversion on the second divided image more naturally with respect to the first divided image.

[0183] Here, the description has been given assuming that the third parameter is calculated by the weighted sum using the weights set for each pixel position. However, if the color after conversion of the second divided image is calculated based on the above-described eighth color and ninth color, it is not particularly limited to the above-described processing. Further, for example, conversion parameters may be generated for each element of RGB so that the RGB values after conversion become the following Rout, Gout, and Bout, respectively. R1 = Table1[Rin][Gin][Bin][0] G1 = Table1[Rin][Gin][Bin][1] B1 = Table1[Rin][Gin][Bin][2] R2 = Table2[Rin][Gin][Bin][0] G2 = Table2[Rin][Gin][Bin][1] B2 = Table2[Rin][Gin][Bin][2] Rout = ((NR - CR) × R1 + CR × R1) ÷ NR Gout = ((NR - CR) × G1 + CR × G1) ÷ NR Bout = ((NR - CR) × B1 + CR × B1) ÷ NR

[0184] Even by such processing, it is possible to gradually obtain conversion parameters for each position in the second divided image and obtain a conversion result that is less likely to cause a sense of discomfort to the human eye.

[0185] Here, the generation of the conversion parameters by Equation (20) has been performed for all pixel positions in the second divided image. However, for example, a case may be considered where there is a frame portion in the second divided image and no natural color change as described above is required for positions below a certain height. From such a viewpoint, for example, at pixel positions where CR is within a predetermined range, color conversion may be performed using the conversion parameters calculated by Equation (20), and at pixel positions where this is not the case, color conversion using the second table may be performed.

[0186] The disclosure of this specification includes the following information processing apparatus, information processing method, and program. (Item 1) Receiving means for receiving a divided image from a device that sequentially transmits each divided image obtained by dividing an image; Obtaining means for obtaining color information of a first color defined in a first color gamut and color information of a second color defined in the first color gamut from a first divided image received by the receiving means; Conversion means for performing a first color conversion process of converting the first color into a third color defined in a second color gamut different from the first color gamut and converting the second color into a fourth color defined in the second color gamut; First correction means for correcting conversion parameters in the first color conversion process so that a color difference between a fifth color obtained by converting the first color into a color defined in the second color gamut and the fourth color becomes larger than a color difference between the third color and the fourth color when the color difference between the third color and the fourth color is smaller than a predetermined threshold; comprising The information processing apparatus, wherein the obtaining means, the conversion means, and the first correction means operate in response to the receiving means receiving the divided image. (Item 2) The information processing apparatus according to Item 1, wherein the predetermined threshold is smaller than a color difference between the first color and the second color. (Item 3) The information processing apparatus according to Item 1 or 2, wherein the predetermined threshold is 2.0 in terms of Euclidean distance ΔE. (Item 4) The information processing apparatus according to Item 2 or 3, wherein the first color and the second color are colors expressed in any one of color spaces of CIE-L*a*b*, RGB, HLS, and HSV. (Item 5) The information processing apparatus according to any one of Items 1 to 3, wherein the second color gamut is a color reproduction gamut for printing by an image forming apparatus. (Item 6) The information processing apparatus according to any one of items 1 to 5, wherein the fifth color is a color calculated based on the third color, the fourth color, and the color difference between the first color and the second color. (Item 7) The information processing apparatus according to item 6, wherein the fifth color is a color obtained by correcting the lightness of the third color based on the color difference between the first color and the second color. (Item 8) The information processing apparatus according to item 7, wherein the fifth color is a color obtained by setting the lightness of the third color to a value obtained by adding the color difference between the first color and the second color to the lightness of the fourth color. (Item 9) The information processing apparatus according to item 6, wherein the fifth color is a color obtained by mapping, within the second color gamut, a color obtained by setting the lightness of the third color to a value obtained by adding the color difference between the first color and the second color to the lightness of the fourth color. (Item 10) The first correction means corrects the conversion parameter so as to convert a sixth color, which is different from the first color and the second color and is included in the first divided image, into a seventh color defined in the second color gamut. The information processing apparatus according to any one of items 6 to 9, wherein the seventh color is a color calculated based on the third color, the fourth color, and an eighth color which is the color when the sixth color is converted by the first color conversion process before correcting the conversion parameter. (Item 11) The information processing apparatus according to any one of items 6 to 10, wherein the second color is the color with the highest saturation among the colors included in the first divided image. (Item 12) The information processing apparatus according to item 11, wherein the first color is the color with the highest lightness or the lowest lightness among the colors included in the first divided image. (Item 13) The apparatus further comprises estimating means for estimating a color included in a second divided image received continuously with the first divided image among the colors included in the first divided image. The information processing apparatus according to any one of items 6 to 10, wherein the second color is a color estimated as a color included in the second divided image. (Item 14) The information processing apparatus according to item 13, wherein the second color is a color included in a boundary portion of the first divided image adjacent to the second divided image. (Item 15) The second divided image is a divided image received subsequent to the first divided image, The information processing apparatus according to item 14, wherein the second color is a color included in a boundary portion of the first divided image adjacent to the second divided image and included in a boundary portion of the first divided image adjacent to a third divided image received immediately before the first divided image. (Item 16) The information processing apparatus further includes grouping means for grouping colors included in the divided image according to a hue range, The information processing apparatus according to any one of items 1 to 15, wherein the color information of the first color and the color information of the second color are color information within a hue range grouped by the grouping means. (Item 17) The information processing apparatus further includes second determination means for determining whether or not two colors are recognized as the same color based on a hue range, The information processing apparatus according to item 16, wherein the grouping means groups colors determined to be the same color by the second determination means. (Item 18) The information processing apparatus according to item 17, wherein the second determination means recognizes colors having a hue range from 30 degrees to 60 degrees as the same color. (Item 19) Based on the ratio between the total number of color combinations included in the first divided image and the number of color combinations included in the first divided image, where the color difference after conversion by the first color conversion process is smaller than the predetermined threshold value, a second correction means for correcting the correction amount of the conversion parameter by the first correction means is further provided. The information processing apparatus according to any one of items 1 to 18, characterized in that. (Item 20) The receiving means receives a second divided image transmitted subsequent to the first divided image. The obtaining means obtains, from the second divided image, color information of the first color and color information of a ninth color defined in the first color gamut, which is different from the second color. The conversion means performs a first color conversion process of converting the first color into a third color defined in a second color gamut different from the first color gamut and converting the ninth color into a tenth color defined in the second color gamut. When the color difference between the third color and the tenth color is smaller than the threshold value, the first correction means corrects the conversion parameter in the first color conversion process so that the color difference between the color obtained by converting the ninth color into a color defined in the second color gamut and the third color is larger than the color difference between the third color and the tenth color. The information processing apparatus according to any one of items 1 to 19, characterized in that. (Item 21) The information processing apparatus according to item 20, characterized in that the first color is a color commonly included in the first divided image and the second divided image. (Item 22) The information processing apparatus according to item 21, characterized in that the first color is a color of an object that is continuous across a boundary portion between the first divided image and the second divided image. (Item 23) The receiving means receives a second divided image transmitted subsequent to the first divided image. A first conversion parameter which is the conversion parameter corrected by the first correction means based on the color information in the first divided image, and a second conversion parameter which is the conversion parameter corrected by the first correction means based on the color information in the second divided image, and further comprising generation means for generating a third conversion parameter to be used in the first color conversion process in the second divided image based on the above, the information processing apparatus according to any one of items 1 to 22. (Item 24) The generation means generates the third conversion parameter such that the color after conversion using the third conversion parameter is determined based on the color after conversion using the first conversion parameter and the color after conversion using the second conversion parameter, the information processing apparatus according to item 23. (Item 25) The generation means converts the 11th color at the first pixel position of the second divided image using the third conversion parameter to obtain the 12th color, and the 13th color obtained by converting the 11th color using the first conversion parameter and the 14th color obtained by converting the 11th color using the second conversion parameter are added by a weighted sum using weights set for each pixel position of the second divided image, and the third conversion parameter is generated so as to be the resulting color, the information processing apparatus according to item 24. (Item 26) The weight is set such that for each pixel position of the second divided image, the weight for the 14th color in the weighted sum increases as the distance from the boundary between the first divided image and the second divided image increases, the information processing apparatus according to item 25. (Item 27) A receiving step of receiving a divided image from a device that sequentially transmits each divided image obtained by dividing an image; An obtaining step of obtaining color information of a first color defined in a first color gamut and color information of a second color defined in the first color gamut from the first divided image received in the receiving step; Perform a first color conversion process of converting the first color into a third color defined in a second color gamut different from the first color gamut, and converting the second color into a fourth color defined in the second color gamut, and a conversion step; When the color difference between the third color and the fourth color becomes smaller than a predetermined threshold value, correct the conversion parameters in the first color conversion process so that the color difference between a fifth color obtained by converting the first color into a color defined in the second color gamut and the fourth color becomes larger than the color difference between the third color and the fourth color. A first correction step; Comprising; The acquisition step, the conversion step, and the first correction step are executed in response to the reception step receiving the divided image, and an information processing method. (Item 28) A program for causing a computer to function as each means of the information processing apparatus according to any one of Items 1 to 26.

[0187] (Other embodiments) The present invention can also be realized by supplying a program that realizes one or more functions of the above-described embodiment to a system or device via a network or a storage medium, and causing one or more processors in a computer of the system or device to read and execute the program. Further, it can also be realized by a circuit (for example, ASIC) that realizes one or more functions.

[0188] The invention is not limited to the above-described embodiment, and various changes and modifications can be made without departing from the spirit and scope of the invention. Therefore, claims are attached to disclose the scope of the invention.

Description of reference numerals

[0189] 101: Information processing apparatus, 108: Image forming apparatus

Claims

1. Receiving means for receiving a divided image from a device that sequentially transmits each divided image obtained by dividing an image; Obtaining means for obtaining color information of a first color defined in a first color gamut and color information of a second color defined in the first color gamut from a first divided image received by the receiving means; Conversion means for performing a first color conversion process of converting the first color into a third color defined in a second color gamut different from the first color gamut and converting the second color into a fourth color defined in the second color gamut; First correction means for correcting a conversion parameter in the first color conversion process so that a color difference between a fifth color obtained by converting the first color into a color defined in the second color gamut and the fourth color is greater than a color difference between the third color and the fourth color when the color difference between the third color and the fourth color is smaller than a predetermined threshold; Comprising: The information processing apparatus, wherein the obtaining means, the conversion means, and the first correction means operate in response to the receiving means receiving the divided image.

2. The information processing apparatus according to claim 1, wherein the predetermined threshold is smaller than a color difference between the first color and the second color.

3. The information processing apparatus according to claim 1, wherein the predetermined threshold is 2.0 in terms of Euclidean distance ΔE.

4. The information processing apparatus according to claim 2, wherein the first color and the second color are colors represented in any one of color spaces of CIE-L*a*b*, RGB, HLS, and HSV.

5. The information processing apparatus according to claim 1, wherein the second color gamut is a color reproduction gamut for printing by an image forming apparatus.

6. The information processing apparatus according to claim 1, wherein the fifth color is a color calculated based on the third color, the fourth color, and a color difference between the first color and the second color.

7. The information processing apparatus according to claim 6, wherein the fifth color is a color obtained by correcting the lightness of the third color based on a color difference between the first color and the second color.

8. The information processing apparatus according to claim 7, wherein the fifth color is a color obtained by setting the lightness of the third color to a value obtained by adding a color difference between the first color and the second color to the lightness of the fourth color.

9. The information processing apparatus according to claim 6, wherein the fifth color is a color obtained by mapping, within the second color gamut, a color obtained by setting the lightness of the third color to a value obtained by adding the color difference between the first color and the second color to the lightness of the fourth color.

10. The first correction means corrects the conversion parameter so as to convert a sixth color, which is different from the first color and the second color and is included in the first divided image, into a seventh color defined in the second color gamut. The information processing apparatus according to claim 6, wherein the seventh color is a color calculated based on the third color and an eighth color, which is a color obtained when the sixth color is converted by the first color conversion process before correcting the conversion parameter.

11. The information processing apparatus according to claim 6, wherein the second color is the color having the highest chroma among the colors included in the first divided image.

12. The information processing apparatus according to claim 11, wherein the first color is the color having the highest lightness or the lowest lightness among the colors included in the first divided image.

13. The information processing apparatus further includes an estimation means for estimating a color included in a second divided image that is received continuously with the first divided image, among the colors included in the first divided image. The information processing apparatus according to claim 6, wherein the second color is a color estimated as a color included in the second divided image.

14. The information processing apparatus according to claim 13, wherein the second color is a color included in a boundary portion of the first divided image that is adjacent to the second divided image.

15. The second divided image is a divided image received subsequent to the first divided image. The information processing apparatus according to claim 14, wherein the second color is a color included in a boundary portion of the first divided image that is adjacent to the second divided image, and is a color included in a boundary portion of the first divided image that is adjacent to a third divided image received immediately before the first divided image.

16. The information processing apparatus further includes a grouping means for grouping the colors included in the divided image according to a hue range. The information processing apparatus according to claim 1, wherein the color information of the first color and the color information of the second color are color information within a hue range grouped by the grouping means.

17. It further includes a second determination means for determining whether or not two colors are recognized as the same color based on a hue range. The information processing apparatus according to claim 16, wherein the grouping means groups colors determined to be the same color by the second determination means.

18. The information processing apparatus according to claim 17, wherein the second determination means recognizes colors with a hue range from 30 degrees to 60 degrees as the same color.

19. It further includes a second correction means for correcting the correction amount of the conversion parameter by the first correction means based on the ratio between the total number of color combinations included in the first divided image and the number of color combinations included in the first divided image, in which the color difference after conversion by the first color conversion process is smaller than the predetermined threshold value. The information processing apparatus according to claim 1.

20. The receiving means receives a second divided image transmitted subsequent to the first divided image. The obtaining means obtains, from the second divided image, color information of the first color and color information of a ninth color defined in the first color gamut, which is different from the second color. The conversion means performs a first color conversion process of converting the first color into a third color defined in a second color gamut different from the first color gamut, and converting the ninth color into a tenth color defined in the second color gamut. The information processing apparatus according to claim 1, wherein when the color difference between the third color and the tenth color is smaller than a threshold value, the first correction means corrects the conversion parameter in the first color conversion process so that the color difference between the color obtained by converting the ninth color into a color defined in the second color gamut and the third color is larger than the color difference between the third color and the tenth color.

21. The information processing apparatus according to claim 20, wherein the first color is a color commonly included in the first divided image and the second divided image.

22. The information processing apparatus according to claim 21, wherein the first color is the color of an object that is continuous across a boundary portion between the first divided image and the second divided image.

23. The receiving means receives a second divided image transmitted subsequent to the first divided image. A first conversion parameter which is the conversion parameter corrected by the first correction means based on the color information in the first divided image, and a second conversion parameter which is the conversion parameter corrected by the first correction means based on the color information in the second divided image, and based on these, the information processing apparatus according to claim 1, further comprising generation means for generating a third conversion parameter to be used in the first color conversion process in the second divided image.

24. The information processing apparatus according to claim 23, wherein the generation means generates the third conversion parameter such that the color after conversion using the third conversion parameter is determined based on the color after conversion using the first conversion parameter and the color after conversion using the second conversion parameter.

25. The information processing apparatus according to claim 24, wherein the generation means generates the third conversion parameter such that the twelfth color obtained by converting the eleventh color at the first pixel position of the second divided image using the third conversion parameter is a color obtained by adding, by weighted sum using weights set for each pixel position of the second divided image, the thirteenth color obtained by converting the eleventh color using the first conversion parameter and the fourteenth color obtained by converting the eleventh color using the second conversion parameter.

26. The information processing apparatus according to claim 25, wherein the weight is set such that, for each pixel position of the second divided image, the weight for the fourteenth color in the weighted sum increases as the distance from the boundary between the first divided image and the second divided image increases.

27. A receiving step of receiving a divided image from a device that sequentially transmits each divided image obtained by dividing an image; An obtaining step of obtaining color information of a first color defined in a first color gamut and color information of a second color defined in the first color gamut from the first divided image received in the receiving step; A conversion step of performing a first color conversion process of converting the first color into a third color defined in a second color gamut different from the first color gamut and converting the second color into a fourth color defined in the second color gamut. When the color difference between the third color and the fourth color is smaller than a predetermined threshold value, a first correction step of correcting conversion parameters in the first color conversion process so that the color difference between a fifth color obtained by converting the first color into a color defined in the second color gamut and the fourth color is larger than the color difference between the third color and the fourth color comprising The acquisition step, the conversion step, and the first correction step are executed in response to the reception step receiving the divided image, the information processing method being characterized thereby. **Claim 28** A program for causing a computer to function as each means of the information processing apparatus according to any one of claims 1 to 26.

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