JP-2024159143-A5 -

Dates

Publication Date

20260511

Application Date

20230428

Description

A block diagram showing an example of the system configuration.A flowchart of the overall processing of the image processing device 101.A flowchart showing the details of the process in step S103.A schematic diagram illustrating the process in step S202.A schematic diagram explaining the color degradation judgment process.A schematic diagram illustrating the color degradation correction process.A diagram showing a correction table that expands brightness in the brightness direction.A schematic diagram illustrating the process in step S202.A flowchart illustrating a series of processes that involve defining areas on a single page and then applying color degradation correction to each area.A diagram illustrating an example of a page of input image data entered in step S101.A flowchart showing the process of performing the area setting process in step S103 on a tile-by-tile basis.A diagram illustrating the page tile layout.A diagram showing each unit tile after the area setting process has been completed.A diagram illustrating the recording head 115.A diagram showing an example of GUI display.This diagram shows the state of the original document data before applying color degradation correction to each page.This figure shows the results of applying color degradation correction to each page.A flowchart representing the gamut mapping flow.A flowchart showing the details of the process in step S 903 .A diagram showing an example of a list of information obtained page by page in step S601.A flowchart showing the overall processing of the image processing device when performing color correction using a color degradation correction TBL.A flowchart showing the details of the process in step S702.Flowchart of gamut mapping processA flowchart for gamut mapping processing.A flowchart showing the details of the process in step S1001.A diagram illustrating an example of the process in step S1103.A flowchart for gamut mapping processing.A flowchart showing the details of the process in step S1201. The recording device 108 of this embodiment uses, as an example, black (K), cyan (C), magenta (M), and yellow (Y) inks. Therefore, RGB image data is converted into image data having 8 bits of color information for each of K, C, M, and Y. The color information for each color corresponds to the amount of each ink applied. Although four colors, C , M, Y, and K, have been given as an example of the number of ink colors, other ink colors such as light cyan (Lc), light magenta (Lm), and gray (Gy) inks with lower densities may be used to improve image quality. In that case, an ink signal corresponding to those colors will be generated. Objects 1601 and 1603 share a common input color. Input color 1607 is equal to input color 1610, input color 1608 is equal to input color 1611, and input color 1609 is equal to input color 1612. However, object 1603 has an input color 1613 that object 1601 does not have. The results of applying color degradation correction to objects 1601 and 1603 are shown in Figure 17, specifically in the pie charts on pages 1700 and 1702 of the original manuscript, as shown in Object 1701 and Object 1703 of the pie chart. In object 1601, input color 1607 is corrected to output color 1707, input color 1608 to output color 1708, and input color 1609 to output color 1709. Furthermore, in object 1603, input color 1610 is corrected to output color 1710, input color 1611 to output color 1711, input color 1612 to output color 1712, and input color 1613 to output color 1713. Here, the amount of correction is determined by the distribution of input colors. For example, suppose input color 1613, which exists only in object 1603, is close to input color 1612, and input color 1612 becomes the target of color degeneracy correction. On the other hand, suppose that in object 1601, input color 1609, which is the same input color, is not the target of color degeneracy correction. In this case, input colors 1609 and 1612 were the same color before correction, but the corrected output colors 1709 and 1712 are different colors. As a result, when objects 1701 and 1703 are viewed individually, they are corrected to values appropriate from the standpoint of identifiability. However, if, for example, a user sets input color 1609 and input color 1612 to be the same color with the intention of representing the same data in different graphs, then for output color 1709 and output color 1712, being the same color is considered more important than distinguishability from other colors. Thus, the discrepancy between the user's expectations and the results due to the correction process becomes a problem. This is not limited to input color 1609 and input color 1612, but is also true for input color 1607 and input color 1610, and input color 1608 and input color 1611. Furthermore, even if the data is not exactly the same color, but there are colors in different regions with a difference of ΔE 2.0 or less, which is considered indistinguishable to the nak