Information processing device, method, and computer program for modifying a profile that converts color values ​​into ink amounts.

Abstract

We provide technology that can improve image quality without relying on the image itself. [Solution] The information processing device includes an optimization condition setting unit that sets optimization conditions including image quality index values ​​related to ink amount; a grid point selection unit that selects target grid points to be corrected from among a plurality of grid points included in a profile that converts color values ​​into ink amount; an ink amount correction unit that corrects the ink amount of the target grid points to a corrected ink amount by performing an optimization process to improve the image quality index value; and a profile correction unit that corrects the profile using the corrected ink amount. The grid point selection unit performs the selection of target grid points using at least one of a condition specification mode that selects target grid points by a selection process according to selection conditions specified by the user, and a position specification mode that selects grid points corresponding to positions specified by the user as target grid points using a position specification map.

Description

Technical Field

[0001] The present disclosure relates to an information processing apparatus, a method, and a computer program for modifying a profile that converts color values into ink amounts.

Background Art

[0002] When performing color printing with a printing apparatus, an ICC profile that converts color values into ink amounts is used. As color values, values in a device-independent color space such as the CIE-L*a*b* color space or the CIE-XYZ color space are used. In the present disclosure, the ICC profile is simply referred to as a "profile".

[0003] Since a plurality of color inks are used for color printing, there are a large number of combinations of ink amounts that represent the same color value. Therefore, it is desirable to adopt an ink amount with good image quality index values such as granularity as the ink amount registered in the profile.

[0004] Patent Document 1 discloses a method for determining a halftone condition for color-converting an input color signal into a device color signal. In this prior art, in order to optimize an image for each local region, the degree of influence of granularity given to a target pixel is estimated based on the ink usage amounts of the target pixel and surrounding pixels, and the ink usage amount at the target pixel is determined so as to improve granularity.

Prior Art Documents

Patent Documents

[0005]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0006] However, the conventional technology described above required performing image quality improvement processing every time the image changed. Therefore, a technology that can improve image quality independently of the image is desired. [Means for solving the problem]

[0007] According to a first embodiment of the present disclosure, an information processing device is provided for modifying a profile that converts color values ​​into ink amounts. This information processing device includes: an optimization condition setting unit that sets optimization conditions including image quality index values ​​related to the ink amount; a grid point selection unit that selects target grid points to be modified from among a plurality of grid points included in the profile; an ink amount modification unit that modifies the ink amount of the target grid points to a modified ink amount by performing an optimization process to improve the image quality index values; and a profile modification unit that modifies the profile using the modified ink amount. The grid point selection unit performs the selection of target grid points using at least one of a condition specification mode that selects the target grid points by a selection process according to selection conditions specified by the user, and a position specification mode that selects grid points corresponding to positions specified by the user as target grid points using a position specification map.

[0008] A second embodiment of the present disclosure provides a method for modifying a profile that converts color values ​​into ink amounts. The method includes (a) setting optimization conditions including image quality index values ​​relating to the ink amounts; (b) selecting target grid points to be modified from among a plurality of grid points included in the profile; (c) modifying the ink amounts of the target grid points to a modified ink amount by performing an optimization process to improve the image quality index values; and (d) modifying the profile using the modified ink amounts. Step (b) includes performing the selection of the target grid points using at least one of a condition specification mode in which the target grid points are selected by a selection process according to selection conditions specified by the user, and a position specification mode in which grid points corresponding to positions specified by the user are selected as the target grid points using a position specification map.

[0009] A third embodiment of the present disclosure provides a computer program for modifying a profile that converts color values ​​into ink amounts. The computer program causes the computer to perform the following: (a) setting optimization conditions including image quality index values ​​relating to the ink amount; (b) selecting target grid points to be modified from among a plurality of grid points included in the profile; (c) modifying the ink amount of the target grid points to a modified ink amount by performing an optimization process to improve the image quality index values; and (d) modifying the profile using the modified ink amount. Process (b) includes performing the selection of the target grid points using at least one of a condition specification mode in which the target grid points are selected by a selection process according to selection conditions specified by the user, and a position specification mode in which grid points corresponding to positions specified by the user are selected as the target grid points using a position specification map. [Brief explanation of the drawing]

[0010] [Figure 1] A diagram illustrating the configuration of the printing system. [Figure 2] An explanatory diagram showing the functions of an information processing device. [Figure 3] A flowchart illustrating the procedure for the profile correction process in the first embodiment. [Figure 4] An explanatory diagram showing an example of a window used to set optimization conditions. [Figure 5] A flowchart showing the processing procedure for step S30 in the first embodiment. [Figure 6] An explanatory diagram showing an example of a window used to adjust image quality index values ​​and the objective function. [Figure 7] An explanatory diagram showing an example of the first window used to set the selection criteria for target grid points. [Figure 8] An explanatory diagram showing an example of the second window used to set the selection criteria for target grid points. [Figure 9]Explanatory drawing showing an example of a window used for selection of a target lattice point. [Figure 10] Explanatory drawing showing another example of a window used for selection of a target lattice point. [Figure 11] Explanatory drawing showing an example of the relationship between an input color value and a target lattice point. [Figure 12] Explanatory drawing showing still another example of a window used for selection of a target lattice point. [Figure 13] Explanatory drawing showing still another example of a window used for selection of a target lattice point. [Figure 14] Explanatory drawing showing still another example of a window used for selection of a target lattice point. [Figure 15] Explanatory drawing showing still another example of a window used for selection of a target lattice point. [Figure 16] Explanatory drawing showing still another example of a window used for selection of a target lattice point. [Figure 17] Flowchart showing the processing procedure of step S30 in the second embodiment. [Figure 18] Explanatory drawing showing an example of an allowable range regarding the ink amount of a target lattice point. [Figure 19] Flowchart showing the procedure of profile correction processing in the third embodiment. [Figure 20] Explanatory drawing showing an example of a window used for setting a smoothing range. [Figure 21] Explanatory drawing showing an example of a smoothing range of an ink amount. [Figure 22] Flowchart showing the processing procedure of step S30 in the third embodiment. [Figure 23] Explanatory drawing showing an example of an allowable range regarding the ink amount of peripheral lattice points.

Mode for Carrying Out the Invention

[0011] A. First Embodiment: Figure 1 is an explanatory diagram showing the configuration of the printing system 500 according to the first embodiment. The printing system 500 comprises an information processing device 100, an input device 200, a display device 300, and a printing device 400. However, the printing device 400 is optional.

[0012] The information processing device 100 comprises a processor 101, a memory 102, an input / output interface 103, and an internal bus 104. The processor 101, memory 102, and input / output interface 103 are connected via the internal bus 104 to enable bidirectional communication. The memory 102 includes volatile memory, such as main memory and video memory, and non-volatile memory, such as a hard disk or SSD (Solid State Drive). The input device 200, display device 300, and printing device 400 are connected to the input / output interface 103 of the information processing device 100 by wired or wireless communication. The input device 200 is, for example, a keyboard or mouse, and the display device 300 is, for example, a liquid crystal display. The input device 200 and the display device 300 may be integrated as a touch panel. The printing device 400 is, for example, an inkjet printer that prints images on a printing medium PM using multiple types of ink.

[0013] As described below, the information processing device 100 performs a process to modify a profile that converts color values ​​into ink amounts. The profile to be modified is an ICC profile for the printing device 400. In this disclosure, the "ink amount" registered in the profile means a combination of ink usage amounts for multiple types of ink. For example, if the printing device 400 can use six types of ink, the "ink amount" is a combination of the usage amounts for the six types of ink. To clarify this meaning, the "ink amount" can also be called an "ink amount set." Furthermore, the ink usage amount for a single type of ink can be called an "individual ink amount."

[0014] Figure 2 is an explanatory diagram showing an example of the configuration of the information processing device 100. The information processing device 100 includes an optimization condition setting unit 110, a grid point selection unit 120, an image quality index value calculation unit 130, an ink amount correction unit 140, and a profile correction unit 150. The ink amount correction unit 140 includes an optimization processing unit 142 that performs optimization processing for image quality improvement, and a color prediction model 144 that converts the ink amount into color values. The functions of each of these units are realized in software by the processor 101 executing a computer program PG that is pre-stored in the memory 102. However, some of the functions of each unit may be realized by hardware circuits.

[0015] The optimization condition setting unit 110 sets the optimization condition OC, which includes the image quality index value QI related to the ink amount. The grid point selection unit 120 selects the target grid point TP from among the multiple grid points included in the profile PF to be corrected in terms of ink amount. The image quality index value calculation unit 130 calculates the image quality index value QI related to the ink amount of the target grid point TP. The ink amount correction unit 140 corrects the ink amount of the target grid point TP to the corrected ink amount CIA by performing an optimization process to improve the image quality index value QI. The profile correction unit 150 corrects the profile PF using the corrected ink amount CIA.

[0016] The color prediction model 144 has the function of converting ink quantity into color values. As the color prediction model 144, for example, it is possible to use a model that converts ink quantity into spectral reflectance using the spectral printing model converter described in Japanese Patent Publication No. 2007-511175, and calculates color values ​​by applying a color matching function to the spectral reflectance.

[0017] Figure 3 is a flowchart showing the procedure for the profile correction process in the first embodiment. In step S10, the optimization condition setting unit 110 sets the optimization condition OC, which includes the image quality index value QI related to the amount of ink.

[0018] Figure 4 is an explanatory diagram illustrating an example of a window used to set optimization conditions. This window W1 includes tool TL11 for setting the first objective function OF1 and tool TL12 for setting the second objective function OF2.

[0019] The first objective function OF1 is an objective function that includes the image quality index QI. In the example in Figure 4, it is possible to set the first objective function OF1 to include one or more of the granularity index GI, the color inconsistency index CII, the ink coverage index ICI, the ink count index INI, and the ink quantity index IAI.

[0020] The granularity index value GI is an index value that indicates the granularity of an image. For example, the granularity index described in Japanese Patent Publication No. 2007-281723 can be used as the granularity index value GI. A smaller granularity index value GI is preferable.

[0021] The Color Inconsistency Index (CII) is an index value that represents the difference in color when the color of a single object is observed under different observation conditions. For example, the CII (Color Inconsistency Index) described in Japanese Patent Publication No. 2007-511175 can be used as the Color Inconsistency Index (CII). A smaller Color Inconsistency Index (CII) is preferable.

[0022] The ink coverage index value ICI is an index value relating to the percentage of the area covered by ink. Ink coverage can be calculated, for example, using the Murray-Davis model described in Japanese Patent Publication No. 2007-281723. When multiple types of ink are ejected to the same pixel, the ink coverage can be calculated according to the total ejection amount. The ink coverage index value ICI is the ink coverage itself, calculated from the corrected ink amount CIA of the target grid point TP. A smaller ink coverage index value ICI is preferable.

[0023] The ink count index value INI is an index value related to the number of inks that make up the ink quantity. "Ink count" refers to the number of different ink types whose individual ink quantities are not zero. As the ink count increases, the color muddiness also increases, so the ink count can be considered an index value representing color muddiness. The ink count index value INI is, for example, the ink count in the correction ink quantity CIA of the target grid point TP. A smaller ink count index value INI is preferable.

[0024] The ink quantity index value IAI is an index value relating to the sum of the individual ink quantities for each ink type. For example, the ink quantity index value IAI is the sum of the individual ink quantities that make up the correction ink quantity CIA for the target grid point TP. A smaller ink quantity index value IAI is preferable.

[0025] The first objective function OF1 is given, for example, by the following equation: OF1 = K1×ΔGI + K2×ΔCII + K3×ΔICI + K4×ΔINI + K5×ΔIAI …(q1) Here, ΔGI is the difference between the target value of the granularity index and the granularity index related to the corrected ink amount. ΔCII is the difference between the target value of the color non-constancy index and the color non-constancy index related to the corrected ink amount. ΔICI is the difference between the target value of the ink coverage index and the corrected ink coverage index value for the corrected ink amount. ΔINI is the difference between the target value of the ink count index and the corrected ink count index for the amount of ink. ΔIAI is the difference between the target value of the ink volume index and the corrected ink volume index. K1 to K5 are coefficients of 0 or greater, and at least one of K1 to K5 is non-zero.

[0026] The first tool, TL11, includes input fields for setting weight coefficients K1 to K5 and target values ​​for each individual image quality index value QI.

[0027] The following equation may be used instead of the above equation (q1). OF1 = K1×GI_c + K2×CII_c + K3×ICI_c + K4×INI_c + K5×IAI_c …(q2) Here, GI_c is a granularity index value related to the amount of ink after correction. CII_c is a color inconsistency index value related to the amount of ink after correction. ICI_c is an ink coverage index value related to the corrected ink amount. INI_c is an ink count index value related to the corrected ink amount. IAI_c is an ink volume index value related to the corrected ink volume.

[0028] In the example shown in Figure 4, the weighting coefficient for the granularity index value GI is set to 1.0, while the weighting coefficients for the other image quality index values ​​are set to 0. Note that the first tool TL11 may be configured to allow selection of only one of several image quality index values.

[0029] The second objective function OF2 relates to the color difference ΔE. The "color difference ΔE" is the color difference between the original color value (Lab value) of the target grid point TP and the color value reproduced by the correction ink amount CIA. This color difference ΔE can be calculated, for example, by the following procedure. (a1) The ink amount correction unit 140 performs optimization using objective functions OF1 and OF2 to correct the ink amount of the target grid point TP to the corrected ink amount CIA. (a2) The ink amount correction unit converts the corrected ink amount CIA into a color value using the color prediction model 144. (a3) Calculate the color difference ΔE between the converted color value and the original color value of the target grid point TP.

[0030] It is preferable that the color values ​​reproduced by the correction ink amount CIA closely match the original color values. That is, it is preferable that the target value of color difference ΔE be a small value close to zero. The target value of color difference ΔE is also called the "acceptable color difference". In the example in Figure 4, there is no field for inputting the target value of color difference ΔE, and a pre-set target value is used. Alternatively, the user may be allowed to input the target value of color difference ΔE.

[0031] In the second tool, TL12, it is specified that the first objective function OF1, which relates to the image quality index QI, should be prioritized over the second objective function OF2, which relates to the color difference Δ. "Prioritizing" means that if the optimization process fails to find a corrected ink amount CIA that satisfies the target value of the first objective function OF1, which objective function, OF1 or OF2, should be prioritized when correcting the ink amount.

[0032] Depending on the "priority" selection, the weights in the multi-objective optimization weighting method may be set accordingly. For example, if it is specified that the first objective function OF1 should be prioritized over the second objective function OF2, the weight of the first objective function OF1 will be set to a larger value than the weight of the second objective function OF2. The "multi-objective optimization weighting method" is a technique that creates a single evaluation function by weighting multiple objective functions and then finds the optimal solution as a single-objective optimization.

[0033] In the weighted method of multi-objective optimization, the evaluation function EF given by the following equation is used. EF = C1 × OF1 + C2 × OF2 …(q3) Here, C1 and C2 are weighting coefficients of 0 or greater, and at least one of C1 and C2 is non-zero. The weight coefficients C1 and C2 of the objective functions OF1 and OF2 use pre-set values ​​depending on the settings of the tool TL12. Alternatively, the user may set the weight coefficients C1 and C2 of the objective functions OF1 and OF2.

[0034] Instead of weighted optimization, Pareto optimization may be performed. When Pareto optimization is performed, the single solution with the best value for the preferred objective function OF is selected from among multiple Pareto optimal solutions. When using Pareto optimization, it is also possible to perform Pareto optimization using multiple image quality index values ​​as separate objective functions. In this case, the user may be able to specify the priority of the multiple image quality index values ​​as an optimization condition.

[0035] In step S20 of Figure 3, the grid point selection unit 120 selects one or more target grid points TP from among multiple grid points of the profile PF to be modified in terms of ink amount. An example of the selection of target grid points TP will be described later.

[0036] In step S30, the ink amount correction unit 140 performs an optimization process to determine the corrected ink amount CIA for the target grid point TP.

[0037] Figure 5 is a flowchart showing the processing procedure in step S30. In step S31, the ink amount correction unit 140 reads the grid point information of the target grid point TP from the profile PF. The grid point information includes the index of the grid point, the color value of the grid point, and the ink amount of the grid point. The index of the grid point is a number used to identify the grid point.

[0038] In step S32, the optimization processing unit 142 calculates the image quality index value QI and objective functions OF1 and OF2 for the target grid point TP. The image quality index value QI is calculated by the image quality index value calculation unit 130 and notified to the optimization processing unit 142. When using the weighting method for multi-objective optimization, the evaluation function EF is calculated according to the above equation (q3). In step S32, the user may adjust the image quality index value QI and objective functions OF1 and OF2.

[0039] Figure 6 is an explanatory diagram showing an example of a window used for adjusting the image quality index value QI and objective functions OF1 and OF2. This window W2 is a modified version of window W1 shown in Figure 4, where the setting tool TL11 was used for setting optimization conditions, and the adjustment tool TL21 was used instead. The adjustment tool TL21 displays the original value in addition to the weight coefficient and target value for each image quality index value. The "original value" is the image quality index value calculated from the amount of ink at the target grid point TP before correction. The user can adjust the weight coefficient and target value by looking at the original value. Furthermore, it is possible to reset whether to prioritize the image quality index value or the color difference using the tool TL12 for the second objective function OF2.

[0040] In step S33 of Figure 5, the ink quantity correction unit 140 determines whether the optimization termination conditions are met. For example, the optimization termination conditions are met when either the first condition, "the objective function OF1, OF2 or the evaluation function EF is less than or equal to a preset target value," or the second condition, "the number of times the optimization process is executed has reached a preset upper limit," is met. If the optimization termination conditions are not met, the process proceeds to step S34, where the optimization processing unit 142 corrects the ink quantity according to the optimization algorithm and returns to step S32.

[0041] On the other hand, if the optimization completion conditions are met, the process proceeds to step S35, where the ink quantity correction unit 140 obtains the optimized corrected ink quantity CIA. This corrected ink quantity CIA is then communicated to the profile correction unit 150.

[0042] In step S36, the ink amount correction unit 140 determines whether processing has been completed for all target grid points TP. If processing is not completed, the process returns to step S31, and steps S31 to S36 are executed for the next target grid point TP. If processing is completed, the process shown in Figure 5 is terminated.

[0043] In step S40 of Figure 3, the profile correction unit 150 corrects the profile PF using the corrected ink amount CIA. Specifically, in the grid point information of the target grid point TP included in the B2A table of the profile PF, the original ink amount is replaced with the corrected ink amount CIA. By doing so, a profile PF with improved image quality index values ​​can be obtained.

[0044] <Selection of target grid points> The selection of the target grid point TP in step S20 can be performed using at least one of the following two modes. (a) A condition specification mode in which the target grid point TP is selected by a selection process according to selection conditions specified by the user. (b) A location selection mode in which a grid point corresponding to a location specified by the user is selected as the target grid point TP using a location selection map. The following sections will explain each of these two modes.

[0045] Figure 7 is an explanatory diagram showing an example of the first window used to set the selection conditions for the target grid point TP in condition specification mode. This first window WS1 contains the following four tools: (1) Tool TS11 is a tool for selecting one of the following options: selecting all grid points included in profile PF, selecting grid points on the surface of the gamut composed of all grid points included in profile PF, or setting detailed conditions such as hue. (2) Tool TS12 is a tool for selecting a specific hue when setting detailed conditions. In the example in Figure 7, Tool TS12 includes multiple hue names as options. Instead of hue names, a hue wheel or color palette may be included as options. (3) Tool TS13 is a tool for selecting a specific brightness when setting detailed conditions. (4) Tool TS14 is a tool for selecting a specific saturation when setting detailed conditions.

[0046] The user can use these tools TS11 to TS14 to set the first selection condition SC1 for selecting the target grid point TP. Note that some of the tools and options included in the first window WS1 may be omitted as appropriate. Alternatively, window WS1 may be configured to include other tools and options.

[0047] Figure 8 is an explanatory diagram showing an example of a second window used to set the selection criteria for target grid points TP. This second window WS2 is a user interface for further narrowing down and selecting multiple grid points that meet the first selection criteria SC1 set in the first window WS1 in Figure 7, and includes the following four tools. Note that the example in Figure 8 illustrates the case where a granularity index value is used as the image quality index value. (1) Tool TS21 is a tool for selecting grid points TP as target grid points, in order of the worst granularity index value, based on a selection ratio specified by the user. (2) Tool TS22 is a tool for selecting a user-specified number of grid points as target grid points TP, in order of decreasing granularity index value. (3) Tool TS23 is a tool for selecting grid points TP as target grid points whose granularity index value is less than or equal to a selection threshold specified by the user. (4) Tool TS24 is a tool for selecting grid points with poor granularity index values ​​as target grid points TP according to preset conditions. In this example, two preset conditions are included as options: "Good Granularity" and "Automatic Granularity". "Good Granularity" is an option that limits the selection to fewer grid points than "Automatic Granularity". The grid point selection unit 120 has specific conditions such as the selection ratio, the number of selections, and the selection threshold set in advance according to these preset conditions.

[0048] The user can use these tools TS21-TS24 to set a second selection condition SC2 for selecting the target grid point TP. Note that some of the tools and options included in the second window WS2 may be omitted as appropriate. Alternatively, the second window WS2 may be configured to include other tools and options.

[0049] At the bottom of the second window WS2, the number of grid points Nsc1 that satisfy the first selection condition SC1 and the number of target grid points TP selected by the second selection condition SC2 are displayed. The user can modify the selection conditions SC1 and SC2 as needed while viewing these numbers Nsc1 and Nsc2.

[0050] Figure 9 is an explanatory diagram showing an example of a window used to select a target grid point TP in position specification mode. This window WS3_a includes a tool TS31_a for the user to specify the position of the target grid point TP in the color value space, and a tool TS32_a for adjusting the position of the target grid point TP. In this embodiment, the color value space is the Lab space.

[0051] Tool TS31_a displays a gamut composed of multiple grid points included in profile PF as a heatmap HM_gamut corresponding to the image quality index value of each grid point. The grid points of the gamut coincide with the grid points of profile PF. Tool TS31_a allows selective display of either "all grid points" or "grid points on the gamut surface." It may also be possible to selectively display grid points within the gamut. In the example in Figure 9, the granularity index value GI selected in Figure 4 by the first objective function OF1 is used as the image quality index value. The user can view this heatmap HM_gamut and specify grid points whose image quality index value should be improved as target grid points TP. This heatmap HM_gamut corresponds to the "location specification map" in this disclosure. The user can use pointer PO to specify a grid point in the heatmap HM_gamut as a target grid point TP. The specified target grid point TP is highlighted so that it can be identified from other grid points. Alternatively, the value of the first objective function OF1 may be displayed instead of the image quality index value.

[0052] The adjustment tool TS32_a displays the color value of the specified target grid point TP using a slider bar. Users can adjust the position of the target grid point TP by adjusting its color value using the slider bar. When the color value of the target grid point TP is adjusted using the adjustment tool TS32_a, it is preferable that the position of the target grid point TP in the heatmap HM also changes accordingly.

[0053] Figure 10 is an explanatory diagram showing another example of the window used to select the target grid point TP. This window WS3_b has a tool TS32_b for directly inputting the color value of the target grid point TP, instead of the adjustment tool TS32_a shown in Figure 9. The user can set the position of the target grid point TP by specifying the color value using this tool TS32_b. When the color value of the target grid point TP is specified using tool TS32_b, the position of the target grid point TP in the heatmap HM_gamut is highlighted accordingly.

[0054] In some cases, the input color values ​​set using the adjustment tool TS32_a shown in Figure 9 or the input tool TS32_b shown in Figure 10 may not correspond to any of the grid points included in the profile PF. In such cases, it is preferable that, as described below, multiple grid points located near the position represented by the input color value in the color value space are automatically selected as target grid points TP.

[0055] Figure 11 is an explanatory diagram illustrating an example of the relationship between the input color value and the target grid point TP. In this example, the input point IP, represented by the input color value, is located at a position offset from the grid points of the profile PF. In this case, the grid point selection unit 120 automatically selects the eight grid points closest to the input point IP as the target grid point TP. If the input point IP is on the grid plane, it is preferable to automatically select the four grid points closest to the input point IP as the target grid point TP. Furthermore, if the input point IP is on the grid line, it is preferable to automatically select the two grid points closest to the input point IP as the target grid point TP.

[0056] Figure 12 is an explanatory diagram showing yet another example of the window used for selecting target grid points. This window WS3_c is the same as window WS3_a shown in Figure 9, but with the addition of the tool TS33 for selecting additional target grid points. This tool TS33 includes a checkbox to specify whether or not to automatically select additional target grid points, and sliders for setting the automatic selection range and selection threshold used in automatic selection. The "automatic selection range" refers to the range around the target grid point TP selected according to the settings using tools TS31_a and TS32_b when searching for additional target grid points. The "selection threshold" refers to the threshold of the image quality index value for selecting an additional target grid point. That is, among the grid points within the automatic selection range, grid points whose image quality index value is equal to or greater than the selection threshold are selected as additional target grid points. The additional target grid point TP_add is highlighted in the heatmap HM_gamut displayed in tool TS31_a. By selecting the additional grid point TP_add in this way, the image quality index value can be improved not only for the target grid point TP but also for the additional grid points TP_add that are located around it.

[0057] Figure 13 is an explanatory diagram showing yet another example of a window used for selecting target grid points. This window WS3_d contains multiple heatmaps for multiple types of image quality index values. In this example, the heatmap HM_gi for the granularity index value GI and the heatmap HM_cii for the color inconsistency index value CII are displayed. The user can easily select target grid points TP that require image quality improvement by observing the multiple heatmaps HM_gi and HM_cii. It is preferable that the target grid points TP specified using one of the multiple heatmaps HM_gi and HM_cii are simultaneously highlighted in all heatmaps. Alternatively, instead of displaying separate heatmaps for each image quality index value, a single heatmap for an integrated image quality index value, which combines multiple image quality index values, may be displayed. For example, the first objective function OF1 described above can be used as the integrated image quality index value.

[0058] Figure 14 is an explanatory diagram illustrating yet another example of a window used to select target grid points in position selection mode. This window WS4_a includes an input image IM and a heatmap HM_image that shows image quality index values ​​at each pixel position of the input image IM. This heatmap HM_image is also a type of “position selection map” in this disclosure.

[0059] When a user specifies a pixel position within the heatmap HM_image using a pointer PO, the grid point selection unit 120 selects the grid point in the profile PF corresponding to the specified pixel position TPX as the target grid point TP. That is, the grid point selection unit 120 converts the input pixel value of the specified pixel position TPX into a color value using an input profile that converts the input color space of the input image IM into a color value, and selects the grid point in the profile PF corresponding to that color value as the target grid point TP. In this way, if there is a pixel in the input image IM that should be improved in terms of image quality, the grid point in the profile PF corresponding to that pixel can be easily specified as the target grid point TP.

[0060] Figure 15 is an explanatory diagram showing yet another example of a window used for selecting target grid points. This window WS4_b is the same as window WS4_a shown in Figure 14, with the addition of tool TS41, similar to tool TS21 shown in Figure 8. This tool TS41 is for selecting grid points as target grid points TP in order of the worst granularity index value, according to a selection ratio specified by the user. Window WS4_b may also be configured to include tools similar to the other tools TS22~TS24 shown in Figure 8. The process of selecting target grid points TP using this window WS4_b corresponds to a condition specification mode in which target grid points TP are selected according to selection conditions specified by the user.

[0061] Figure 16 is an explanatory diagram showing yet another example of a window used for selecting target grid points. This window WS4_c is the same as window WS4_a shown in Figure 14, but with the addition of tool TS43, similar to tool TS33 shown in Figure 12. This tool TS43 includes a checkbox to specify whether or not to automatically select additional target grid points, and sliders to set the automatic selection range and selection threshold used in automatic selection, respectively.

[0062] The various windows and tools described in Figures 7 to 16 above can be used in appropriate combinations to select one or more target grid points. Furthermore, the grid point selection unit 120 may be configured to select target grid points TP using only one of the condition specification mode and position specification mode, or it may be configured to select target grid points TP using both.

[0063] Furthermore, instead of the grid point selection unit 120 performing the selection of target grid points TP according to the user's specifications regarding selection conditions and position, it may be configured to automatically select grid points as target grid points TP in which the image quality index value QI or objective function OF1 does not reach the target value, i.e., grid points that are worse than the target value.

[0064] As described above, in the first embodiment, the profile PF is modified to improve the image quality index value QI, so that image quality can be improved regardless of the image. Furthermore, since the target grid point is selected using at least one of the condition specification mode and the position specification mode, the target grid point can be flexibly selected according to the user's requirements.

[0065] B. Second Embodiment: Figure 17 is a flowchart showing the processing procedure for step S30 in the second embodiment. The apparatus configuration and the overall processing procedure shown in Figure 3 are the same as in the first embodiment. The second embodiment differs from the first embodiment in that steps S41 and S42 are inserted between steps S31 and S32 in the detailed procedure of step S30; otherwise, it is almost the same as the first embodiment.

[0066] In step S41, the ink amount correction unit 140 reads the grid point information of the surrounding grid points that exist around the target grid point TP from the profile PF. In step S42, the ink amount correction unit 140 sets the tolerance range for the ink amount of the target grid point.

[0067] Figure 18 is an explanatory diagram illustrating an example of an acceptable range for the ink amount at a target grid point. Here, hatching is applied to the four target grid points PA, PB, PC, and PD, and the surrounding grid points P1 to P8. It is assumed that the corrected ink amount CIA is determined in this order for the four target grid points PA, PB, PC, and PD. The surrounding grid points P1 to P8 used to determine the acceptable range are determined according to a predetermined rule. Alternatively, the optimization condition setting unit 110 may be configured to accept user specifications regarding the surrounding grid points.

[0068] In the example in Figure 18, the peripheral grid points P1 to P8 used to determine the tolerance range are adjacent grid points to any of the target grid points PA, PB, PC, or PD. However, grid points further from the target grid point than the adjacent grid points may also be used as peripheral grid points to determine the tolerance range for the ink amount of the target grid point. Below, we will explain examples of tolerance ranges for the ink amount of two target grid points PA and PB.

[0069] The correction ink amount CIA_PA for the first target grid point PA is constrained to a tolerance range set around the average value of the ink amounts IA_P1, IA_P2, IA_PB, and IA_PC of the grid points P1, P2, PB, and PC adjacent to the target grid point PA. This tolerance range is set to 100±α%, for example, when the average value Ave(IA_P1, IA_P2, IA_PB, IA_PC) is set to 100% and α is set to a positive specified value less than 100. The specified value α is set to a value in the range of 10 to 30, for example.

[0070] In the color value space, there are six adjacent grid points to the first target grid point PA. It is preferable to determine the tolerance range for the correction ink amount CIA_PA of the target grid point PA using all six of these adjacent grid points; however, in Figure 18, two adjacent grid points located along the b-axis of the color value space are omitted from the illustration.

[0071] The correction ink amount CIA_PB for the second target grid point PB is set to 100±α%, where Ave(CIA_PA, IA_P3, IA_P4, IA_PD), which is the average value of the ink amounts CIA_PA, IA_P3, IA_P4, IA_PD of the grid points PA, P3, P4, PD adjacent to the target grid point PB, is set to 100%. It is preferable to determine the tolerance range for the correction ink amount CIA_PB of the target grid point PB using all six adjacent grid points. Note that since the target grid point PA has undergone optimization processing before the target grid point PB, the ink amount CIA_PA used to determine the tolerance range for the correction ink amount CIA_PB of the target grid point PB is the ink amount after optimization.

[0072] As can be seen from the example in Figure 18, the tolerance range for the ink amount at the target grid point TP is determined by the ink amounts of the surrounding grid points. By performing an optimization process for the corrected ink amount CIA at the target grid point TP with this tolerance range as a constraint, it is possible to prevent abrupt fluctuations in the ink amount at adjacent grid points. In other words, this has the advantage of making the ink amount gradation smoother.

[0073] The constraints on the correction ink amount CIA for the target grid point TP are applied to each ink type. For example, if a set of ink amounts consists of six types of ink, an acceptable range is set and applied to each of the six ink types. The process of limiting the correction ink amount CIA to stay within the set acceptable range can be called "smoothing."

[0074] As described above, in the second embodiment, the optimization process is performed under the constraint that the correction ink amount CIA of the target grid point TP falls within an acceptable range determined from the ink amounts at multiple surrounding grid points located around the target grid point TP. As a result, it is possible to prevent the correction ink amount CIA of the target grid point TP from fluctuating abruptly from the ink amounts at the surrounding grid points.

[0075] C. Third Embodiment: Figure 19 is a flowchart showing the procedure for the profile correction process in the third embodiment. The apparatus configuration of the third embodiment is the same as that of the first embodiment. The third embodiment differs from the first embodiment in that step S15 is inserted between steps S10 and S20, and the detailed procedure of step S30 is different. Otherwise, it is almost the same as the first embodiment.

[0076] In step S15, the optimization condition setting unit 110 sets the ink amount smoothing range. The ink amount smoothing range is the range within which the surrounding grid points that exist around the target grid point TP are to be corrected so that the ink amount does not fluctuate too rapidly from the surrounding grid points.

[0077] Figure 20 is an explanatory diagram illustrating an example of a window used to set the smoothing range of the ink amount. This window W4 contains a tool TL41 for the user to set the width of the smoothing range Rs. In the example in Figure 20, tool TL41 is a slider bar. Alternatively, the smoothing range Rs may be determined according to a predefined rule without the user having to set the smoothing range Rs.

[0078] Figure 21 is an explanatory diagram illustrating an example of the ink amount smoothing range Rs. In this example, the peripheral grid points PP located within a sphere of radius Rs centered on the central point CP of the four target grid points PA, PB, PC, and PD are given a grainy hatching. For these peripheral grid points PP, the ink amount of each is modified so that it falls within an acceptable range determined by the ink amounts of multiple grid points adjacent to the peripheral grid point PP. Note that the smoothing range Rs is not limited to a sphere; it may also be set for other three-dimensional shapes such as cubes.

[0079] Figure 22 is a flowchart showing the processing procedure for step S30 in the third embodiment. The detailed procedure for step S30 in the third embodiment differs from the first embodiment in that step S51 is inserted between steps S31 and S32, and steps S52 and S53 are added after step S36; otherwise, it is almost the same as the first embodiment.

[0080] In step S51, the ink amount correction unit 140 reads the grid point information of the surrounding grid points located within the smoothing range Rs from the profile PF. In step S52, the ink amount correction unit 140 sets an acceptable range for the ink amount of the surrounding grid points. In step S53, the ink amount correction unit 140 performs a smoothing process to correct the ink amount of the surrounding grid points to within the acceptable range. This smoothing process is preferably performed after the optimization process has been completed for all target grid points TP that are subject to image quality improvement.

[0081] Figure 23 is an explanatory diagram illustrating an example of the acceptable range for ink amount at peripheral grid points within the smoothing range. Grid points PA to PD are the target grid points for image quality improvement, grid points Pa to Pd are peripheral grid points within the smoothing range, and grid points P1 to P3 are grid points outside the smoothing range. It is assumed that the ink amount correction by optimization processing has been completed for the target grid points PA to PD, and that the ink amount smoothing processing is performed in this order for the two peripheral grid points Pa and Pc. The acceptable range for ink amount at each peripheral grid point is determined by the ink amounts at multiple grid points adjacent to the peripheral grid point.

[0082] The grid points used to determine the tolerance range for the ink amount IA_Pa of the first peripheral grid point Pa are all grid points adjacent to the peripheral grid point Pa. The ink amount IA_Pa of the first peripheral grid point Pa is limited to a tolerance range set centered on the average value of the ink amounts IA_P1, IA_P2, IA_Pb, and IA_Pc of the adjacent grid points P1, P2, Pb, and Pc. This tolerance range is set to 100±β%, for example, when the average value Ave(IA_P1, IA_P2, IA_Pb, IA_Pc) is set to 100% and β is set to a positive specified value less than 100. The specified value β is set to a value in the range of 10 to 30, for example.

[0083] The grid points used to determine the tolerance range for the ink amount IA_Pc of the second peripheral grid point Pc are all grid points adjacent to the peripheral grid point Pc. The tolerance range for the ink amount IA_Pc of the second peripheral grid point Pc is set to 100±β%, where the average value Ave(IA_P3, CIA_Pa, CIA_PA, IA_Pd) of the ink amounts IA_P3, CIA_Pa, CIA_PA, IA_Pd of adjacent grid points P3, Pa, PA, Pd is set to 100%. The ink amount CIA_Pa of the first peripheral grid point Pa used here is the ink amount after smoothing for the first peripheral grid point Pa. The ink amount CIA_PA of the target grid point PA is the corrected ink amount after optimization.

[0084] As can be seen from the example in Figure 23, the tolerance used in the smoothing process for the ink amount at peripheral grid points is determined by the ink amounts at multiple grid points adjacent to the peripheral grid point. By adjusting the ink amount at peripheral grid points to fall within this tolerance, it is possible to prevent abrupt fluctuations in the ink amount at adjacent grid points. In other words, this has the advantage of making the ink amount gradation smoother.

[0085] The smoothing process for the ink amount at the surrounding grid points, as described above, is applied to each ink type. For example, if a set of ink amounts consists of six different inks, an acceptable range is set and applied to each of the six ink types.

[0086] In the smoothing process for peripheral grid points, it is preferable to determine the corrected ink amount such that the color value reproduced with the corrected ink amount does not substantially change from the original color value. That is, it is preferable to determine the corrected ink amount such that the color difference between the color value reproduced with the corrected ink amount and the original color value stored in the peripheral grid points is less than or equal to a minute tolerance color difference. Such a smoothing process can be performed by the procedure shown below. (b1) The initial value of the ink amount after smoothing is determined from the original color values ​​stored in the surrounding grid points using the inverse transform of the color prediction model 144. (b2) Using initial values ​​for the ink amount, the ink amount after smoothing is determined by performing an optimization process so that the color values ​​reproduced from the ink amount after smoothing substantially match the original color values, under the constraint that the ink amount at the surrounding grid points falls within an acceptable range. In this case, the color values ​​reproduced from the ink amount after smoothing can be calculated using the color prediction model 144.

[0087] As described above, in the third embodiment, the amount of ink in the surrounding grid points around the target grid point TP is modified so that it falls within an acceptable range determined by the amount of ink in multiple grid points adjacent to the surrounding grid point. As a result, it is possible to prevent the amount of ink in the surrounding grid points around the target grid point TP from fluctuating rapidly.

[0088] Furthermore, the smoothing process for peripheral grid points in the third embodiment may be applied to the second embodiment. In this case, the default value α used to set the first allowable range for the ink amount of the target grid point TP described in the second embodiment and the default value β used to set the second allowable range for the ink amount of peripheral grid points described in the third embodiment may be set to different values. Alternatively, the default values ​​α and β may be set to the same value.

[0089] Other forms: This disclosure is not limited to the embodiments described above, and can be implemented in various forms without departing from its spirit. For example, this disclosure can also be implemented in the following forms. The technical features in the embodiments described below that correspond to the technical features in each of the forms described below can be replaced or combined as appropriate in order to solve some or all of the problems of this disclosure, or to achieve some or all of the effects of this disclosure. Furthermore, if such technical features are not described as essential in this specification, they can be deleted as appropriate.

[0090] (1) According to a first embodiment of the present disclosure, an information processing device is provided for modifying a profile that converts color values ​​into ink amounts. The information processing device includes: an optimization condition setting unit that sets optimization conditions including image quality index values ​​relating to the ink amount; a grid point selection unit that selects target grid points to be modified from among a plurality of grid points included in the profile; an ink amount modification unit that modifies the ink amount of the target grid points to a modified ink amount by performing an optimization process to improve the image quality index values; and a profile modification unit that modifies the profile using the modified ink amount. The grid point selection unit performs the selection of target grid points using at least one of a condition specification mode that selects the target grid points by a selection process according to selection conditions specified by the user, and a position specification mode that selects grid points corresponding to positions specified by the user as target grid points using a position specification map. This information processing device modifies the profile to improve image quality index values, thus enabling image quality improvement regardless of the image. Furthermore, since target grid points are selected using at least one of the condition specification mode and position specification mode, target grid points can be flexibly selected according to the user's requirements.

[0091] (2) In the above-mentioned information processing device, the condition specification mode may be configured to present one or more of the following to the graphical user interface: a first selection condition for selecting all grid points included in the profile as target grid points; a second selection condition for selecting some of the grid points from all the grid points that are located at specific positions in the gamut composed of all the grid points as target grid points; and a third selection condition for selecting the target grid points from all the grid points according to one or more color characteristics among hue, lightness, and saturation. This information processing device allows for the selection of target grid points according to various selection criteria.

[0092] (3) In the above-mentioned information processing device, the selection condition in the condition specification mode may include one of the following: a first condition in which some of the grid points included in the profile are selected as target grid points in order of the worst image quality index value; and a second condition in which grid points in which the image quality index value is less than or equal to the target value are selected as target grid points. According to this information processing device, it is possible to select certain grid points with poor image quality index values ​​as target grid points.

[0093] (4) In the above-mentioned information processing device, the position specification mode may be configured to display a heat map showing the image quality index value at each grid point for the gamut corresponding to the profile as the position specification map in the graphical user interface. According to this information processing device, users can select target grid points while viewing a heatmap of image quality index values.

[0094] (5) In the above-mentioned information processing device, the position specification mode may be configured to select a specified grid point specified by the user in the heatmap as the target grid point, and to select grid points located around the specified grid point as additional target grid points. According to this information processing device, image quality index values ​​can be improved not only for the target grid point specified by the user, but also for additional target grid points in the surrounding area.

[0095] (6) In the above-mentioned information processing device, the position specification mode may be configured to display a heat map showing the image quality index value at each pixel position of the input image as the position specification map on the graphical user interface, and to select the grid point of the profile corresponding to the specified pixel position specified by the user in the heat map as the target grid point. According to this information processing device, users can select pixel positions within an image while viewing a heatmap of image quality index values, and then select the grid points corresponding to the selected pixel positions as target grid points.

[0096] (7) In the above-mentioned information processing device, the position specification mode may be configured to select the grid point corresponding to the specified pixel position as the target grid point, and to select the grid points located around the target grid point in the gamut composed of all the grid points of the profile as additional target grid points. This information processing device can improve image quality index values ​​not only for the target grid point corresponding to the specified pixel position, but also for additional target grid points in the surrounding area.

[0097] (8) In the above-mentioned information processing device, the optimization process may include a constraint that the amount of correction ink at the target grid point falls within a first acceptable range determined from the amount of ink at a plurality of surrounding grid points located around the target grid point. This information processing device prevents the amount of correction ink at a target grid point from fluctuating abruptly from the amount of ink at surrounding grid points.

[0098] (9) In the above-mentioned information processing device, the ink amount correction unit may correct the ink amount of the surrounding grid points that are located around the target grid point so that the ink amount of the surrounding grid points falls within a second allowable range determined from the ink amounts of a plurality of grid points adjacent to the surrounding grid point. This information processing device makes it possible to prevent sudden fluctuations in the amount of ink in surrounding grid points located around the target grid point.

[0099] (10) In the above-mentioned information processing device, the optimization condition setting unit may be configured to accept user specifications regarding the range of the surrounding grid points. This information processing device allows you to arbitrarily set the range of surrounding grid points that are subject to ink quantity correction.

[0100] (11) In the above-mentioned information processing device, the optimization process may be a multi-objective optimization process using a first objective function relating to the image quality index value and a second objective function relating to the color difference between the color value of the target grid point and the color value obtained by inversely transforming from the correction ink amount using the profile. According to this information processing device, the profile can be modified so that the image quality index values ​​are good and the color values ​​corresponding to the amount of correction ink do not fluctuate excessively.

[0101] (12) In the above-mentioned information processing device, the image quality index value may include one or more of the following: a granularity index value, a color inconsistency index value, an ink coverage index value, an ink count index value, and an ink quantity index value. According to this information processing device, the profile can be modified to improve one or more image quality indicator values.

[0102] (13) In the above-mentioned information processing device, the optimization conditions may include a target value for the image quality index value, and the grid point selection unit may automatically select a grid point as the target grid point in which the image quality index value before correction of the ink amount does not reach the target value. According to this information processing device, the target grid points for which the ink amount will be corrected can be automatically selected without the user having to specify the target grid points.

[0103] (14) A second embodiment of the present disclosure provides a method for modifying a profile that converts color values ​​into ink amounts. The method includes (a) setting optimization conditions including image quality index values ​​relating to the ink amounts; (b) selecting target grid points to be modified from among a plurality of grid points included in the profile; (c) modifying the ink amounts of the target grid points to a modified ink amount by performing an optimization process to improve the image quality index values; and (d) modifying the profile using the modified ink amounts. Step (b) includes performing the selection of the target grid points using at least one of a condition specification mode in which the target grid points are selected by a selection process according to selection conditions specified by a user, and a position specification mode in which grid points corresponding to positions specified by the user are selected as the target grid points using a position specification map.

[0104] (15) According to a third embodiment of the present disclosure, a computer program is provided for modifying a profile that converts color values ​​into ink amounts. The computer program causes the computer to perform the following: (a) setting optimization conditions including image quality index values ​​relating to the ink amounts; (b) selecting target grid points to be modified from among a plurality of grid points included in the profile; (c) modifying the ink amounts of the target grid points to modified ink amounts by performing an optimization process to improve the image quality index values; and (d) modifying the profile using the modified ink amounts. Process (b) includes performing the selection of the target grid points using at least one of a condition specification mode in which the target grid points are selected by a selection process according to selection conditions specified by the user, and a position specification mode in which grid points corresponding to positions specified by the user are selected as the target grid points using a position specification map.

[0105] This disclosure can also be implemented in various forms other than information processing devices, methods, and computer programs. For example, it can be implemented in the form of an image processing method or a non-transitory storage medium on which a computer program is recorded. [Explanation of Symbols]

[0106] 100...Information processing device, 101...Processor, 102...Memory, 103...Input / Output interface, 104...Internal bus, 110...Optimization condition setting unit, 120...Grid point selection unit, 130...Image quality index value calculation unit, 140...Ink amount correction unit, 142...Optimization processing unit, 144...Color prediction model, 150...Profile correction unit, 200...Input device, 300...Display device, 400...Printing device, 500...Printing system

Claims

1. An information processing device for modifying a profile that converts color values ​​into ink volume, An optimization condition setting unit that sets optimization conditions including image quality index values ​​related to the amount of ink, A grid point selection unit selects a target grid point to be modified from among a plurality of grid points included in the aforementioned profile, An ink amount correction unit that corrects the amount of ink at the target grid point to a corrected ink amount by performing an optimization process to improve the aforementioned image quality index value, A profile correction unit that corrects the profile using the amount of correction ink, Equipped with, The aforementioned grid point selection unit is A condition specification mode for selecting the target grid points by a selection process according to selection conditions specified by the user, A location specification mode in which a grid point corresponding to the location specified by the user is selected as the target grid point using a location specification map, An information processing device that performs the selection of the target grid point using at least one of the following.

2. An information processing apparatus according to claim 1, The aforementioned condition specification mode is, A first selection condition is to select all grid points included in the profile as the target grid points, A second selection condition is to select a portion of the aforementioned grid points that are located at specific positions in the gamut composed of all the aforementioned grid points as the target grid points, A third selection condition for selecting the target grid point from among all the grid points according to one or more color characteristics among hue, lightness, and saturation, An information processing device configured to present one or more of the following in a graphical user interface.

3. An information processing apparatus according to claim 1, The selection conditions in the aforementioned condition specification mode are: A first condition is to select some of the grid points from all the grid points included in the profile as target grid points, in order of the worst image quality index value, A second condition is to select, from all the aforementioned grid points, grid points whose image quality index value is less than or equal to the target value as the target grid points, An information processing device that includes one of the following.

4. An information processing apparatus according to claim 1, The position selection mode is configured to display a heatmap showing the image quality index value at each grid point for the gamut corresponding to the profile, as the position selection map, on a graphical user interface.

5. An information processing apparatus according to claim 4, The position specification mode is configured to select a specified grid point specified by the user in the heatmap as the target grid point, and to select grid points located around the specified grid point as additional target grid points, in the information processing device.

6. An information processing apparatus according to claim 1, The position specification mode is configured to display a heat map showing the image quality index value at each pixel position of an input image as the position specification map in a graphical user interface, and to select the grid point of the profile corresponding to the specified pixel position specified by the user in the heat map as the target grid point.

7. An information processing apparatus according to claim 6, The position specification mode is configured to select the grid point corresponding to the specified pixel position as the target grid point, and to select grid points located around the target grid point in the gamut composed of all grid points of the profile as additional target grid points.

8. An information processing apparatus according to claim 1, The optimization process includes a constraint that the amount of correction ink at the target grid point falls within a first acceptable range determined from the amounts of ink at a plurality of surrounding grid points located around the target grid point.

9. An information processing apparatus according to claim 1, The ink amount correction unit corrects the ink amount of the surrounding grid points so that the ink amount of the surrounding grid points located around the target grid point falls within a second allowable range determined from the ink amounts of a plurality of grid points adjacent to the surrounding grid point.

10. An information processing apparatus according to claim 9, The optimization condition setting unit is configured to accept user specifications regarding the range of the surrounding grid points, and is an information processing device.

11. An information processing apparatus according to claim 1, The optimization process is a multi-objective optimization process using a first objective function relating to the image quality index value and a second objective function relating to the color difference between the color value of the target grid point and the color value obtained by inversely transforming the correction ink amount using the profile, in an information processing device.

12. An information processing apparatus according to claim 1, The image quality index value includes one or more of the following: a granularity index value, a color inconsistency index value, an ink coverage index value, an ink count index value, and an ink quantity index value.

13. An information processing apparatus according to claim 1, The optimization conditions include the target value of the image quality index value, The grid point selection unit is an information processing device that automatically selects as the target grid point a grid point the image quality index value does not reach before the correction of the ink amount of the grid point.

14. A method for modifying a profile that converts color values ​​into ink amounts, (a) A step of setting optimization conditions including image quality index values ​​related to the amount of ink, (b) A step of selecting a target grid point to be modified from among a plurality of grid points included in the profile, (c) A step of correcting the amount of ink at the target grid point to a corrected amount of ink by performing an optimization process to improve the image quality index value, (d) A step of correcting the profile using the amount of correction ink, Includes, The above step (b) is, A condition specification mode for selecting the target grid points by a selection process according to selection conditions specified by the user, A location specification mode in which a grid point corresponding to the location specified by the user is selected as the target grid point using a location specification map, A method comprising the step of performing the selection of the target grid point using at least one of the following.

15. A computer program for modifying a profile that converts color values ​​into ink amounts, (a) A process for setting optimization conditions including image quality index values ​​related to the amount of ink, (b) A process of selecting target grid points to be modified from among the multiple grid points included in the profile, (c) A process to correct the amount of ink at the target grid point to a corrected amount by performing an optimization process to improve the image quality index value, (d) A process of correcting the profile using the amount of correction ink, Have the computer run it, The process (b) is as follows: A condition specification mode for selecting the target grid points by a selection process according to selection conditions specified by the user, A location specification mode in which a grid point corresponding to the location specified by the user is selected as the target grid point using a location specification map, A computer program that includes a process for selecting the target grid point using at least one of the following.

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