CN107492365B - Method and device for obtaining color gamut mapping fitting function - Google Patents
Method and device for obtaining color gamut mapping fitting function Download PDFInfo
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- G09G5/00—Control arrangements or circuits for visual indicators common to cathode-ray tube indicators and other visual indicators
- G09G5/02—Control arrangements or circuits for visual indicators common to cathode-ray tube indicators and other visual indicators characterised by the way in which colour is displayed
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Abstract
The application discloses a method and a device for obtaining a color gamut mapping fitting function, wherein the method comprises the following steps: acquiring a plurality of first data of a standard color space corresponding to a plurality of known colors of a target color gamut respectively; mapping a plurality of first data respectively corresponding to the plurality of known color points into a plurality of second data of the standard color space of a source color gamut respectively; dividing the target color gamut and the source color gamut into a plurality of blocks corresponding to each other, and classifying the plurality of first data and the plurality of second data according to the blocks to obtain a plurality of first data and a plurality of second data in each block; and respectively obtaining the fitting function of each block through the plurality of first data and the plurality of second data in each block. By means of the method, the power of the fitting function can be effectively reduced, the accuracy can be improved, and the difficulty and the cost requirement can be reduced when the fitting function is implemented in software and hardware.
Description
Technical Field
The present application relates to the field of panel display technologies, and in particular, to a method and an apparatus for obtaining a gamut mapping fitting function.
Background
In cross-media reproduction of color images, gamut mapping is inevitable in many cases due to the different gamuts of different media. Gamut mapping, where a color image is converted from one color medium (display device) to another (another display device), necessarily results in some color distortion. It is generally necessary to map a specific color gamut through a color gamut mapping function so that the display panel presents a picture satisfying the display effect of the color gamut.
In the prior art, a common simple method can be to use a 24-color card to perform fitting of a gamut mapping function, and to obtain a more precise fitting result, the fitting function is usually fitted by using a function with a higher power, and the fitting function form of the gamut mapping is as follows:
the inventors of the present application found in a long-term development process: firstly, after a more accurate fitting function is obtained, a larger error of individual color points is easy to occur; second, assuming that there is no large error in the individual color points, the high power function has high difficulty and cost in the implementation of software and hardware.
Disclosure of Invention
The technical problem mainly solved by the application is to provide a method and a device for obtaining a color gamut mapping fitting function, which can effectively reduce the power of the fitting function and increase the accuracy, and can reduce the difficulty and the cost requirement when the fitting function is implemented in software and hardware.
In order to solve the technical problem, the application adopts a technical scheme that: there is provided a method of obtaining a gamut mapping fitting function, the method comprising: acquiring a plurality of first data of a standard color space corresponding to a plurality of known colors of a target color gamut respectively; mapping a plurality of first data respectively corresponding to the plurality of known color points into a plurality of second data of the standard color space of a source color gamut respectively; dividing the target color gamut and the source color gamut into a plurality of blocks corresponding to each other, and classifying the plurality of first data and the plurality of second data according to the blocks to obtain a plurality of first data and a plurality of second data in each block; and respectively obtaining the fitting function of each block through the plurality of first data and the plurality of second data in each block.
In order to solve the above technical problem, another technical solution adopted by the present application is: there is provided an apparatus for obtaining a gamut mapping fitting function, the apparatus comprising: the device comprises a processor, a memory and a communication circuit, wherein the processor is respectively coupled with the memory and the communication circuit, and the processor is used for controlling the communication circuit to acquire a plurality of first data of a standard color space corresponding to a plurality of known colors of a target color gamut and controlling the memory to store the first data; the processor is configured to map a plurality of first data corresponding to the plurality of known color points into a plurality of second data of the standard color space of a source color gamut, respectively; dividing the target color gamut and the source color gamut into a plurality of blocks corresponding to each other, and classifying the plurality of first data and the plurality of second data according to the blocks to obtain a plurality of first data and a plurality of second data in each block; and respectively obtaining the fitting function of each block through the plurality of first data and the plurality of second data in each block.
In order to solve the above technical problem, the present application adopts another technical solution: there is provided a device having a storage function, on which program data are stored, which program data, when being executed by a processor, carry out the steps of the method as described above.
The beneficial effect of this application is: different from the prior art, the method and the device for obtaining the color gamut of the color gamut; mapping a plurality of first data respectively corresponding to the plurality of known color points into a plurality of second data of the standard color space of a source color gamut respectively; dividing the target color gamut and the source color gamut into a plurality of blocks, and classifying the plurality of first data and the plurality of second data according to the blocks to obtain a plurality of first data and a plurality of second data in each block; and respectively obtaining the fitting function of each block through the plurality of first data and the plurality of second data in each block. Dividing the target color gamut and the source color gamut into a plurality of blocks corresponding to each other, and classifying the plurality of first data and the plurality of second data according to the blocks to obtain a plurality of first data and a plurality of second data in each block; the fitting function of each block is obtained through the first data and the second data in each block, the color gamut of each block is smaller than that of the original block, the target and the pertinence are better achieved, the number of the first data and the number of the second data in each block are smaller than that of the original first data and the original second data, and the first data and the second data in each block are more targeted.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts. Wherein:
FIG. 1 is a diagram of a color gamut mapping for a specific target display panel using standard RGB as color space;
FIG. 2 is a graphical illustration of the fitting error versus the fitting power of the fitting function of the gamut mapping of FIG. 1;
FIG. 3 is a flow diagram of one embodiment of a method of obtaining a gamut mapping fitting function according to the present application;
FIG. 4 is a graphical representation of source and target gamut place values that have been derived and segmented;
FIG. 5 is a graph showing the fitting power of the fitting function versus the fitting error time for the three blocks of FIG. 4;
FIG. 6 is a schematic diagram illustrating an embodiment of an apparatus for obtaining a fitting function of gamut mapping according to the present application;
fig. 7 is a schematic structural diagram of an embodiment of the device with a storage function according to the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Before the present application is described in detail, concepts and prior art related to the present application will be described.
Each color reproduction device or medium or media exhibits a different color rendering range, that is, its color gamut, that is, the spectral range of colors that the device is capable of reproducing, due to the different structure and mechanism of rendering colors.
In color image reproduction, the source device gamut (original gamut) and the destination device gamut (destination gamut) are typically different. They have the following two relationships: firstly, the target device color gamut completely contains the source device color gamut, and only one-to-one color mapping is needed at the moment; secondly, the color gamut of the target device is smaller than the color gamut of the source device or the color gamuts of the source device and the source device are partially overlapped, and at this time, a reasonable color gamut mapping algorithm is needed to map the colors outside the color gamut of the target device in the source device into the color gamut of the target device.
Color space, also known as color model (also known as color space, color model, color system, etc.), is used to describe colors in a generally accepted manner under certain standards.
In essence, the color model is a description of the coordinate system and subspace. There is a single dot representation for each color located in the system. Most color models employed are either hardware-oriented or application-oriented. There are many kinds of color spaces, and RGB, CMY, HSV, HIS, Lab, etc. are commonly used.
RGB (red, green, blue) is a space defined by colors recognized by human eyes, and can represent most colors. It puts the three quantities of hue, brightness and saturation together to represent, and is difficult to separate. It is the most common hardware-oriented color model. The model is used for color monitors and a large class of color video cameras.
CMY is the color space used for industrial printing. It corresponds to RGB. A simple analog RGB source is that the object emits light, and CMY is based on reflected light. The specific application is as printer: four color cartridges, namely CMY plus black cartridges, are typically used.
Both HSV and HSI color spaces are proposed for better digitizing colors. There are many HSX color spaces where X may be either V or I, depending on the particular use for which X is meant. H is hue, S is saturation, and I is intensity.
The Lab color space is used for computer tone adjustment and color correction. It is implemented independently of the color model of the device. This method is used to map the device to the model and color distribution quality changes of the model ontology.
Because different devices adopt different color spaces, in order to realize color gamut mapping, a uniform standard color space irrelevant to the devices needs to be selected first, and the device color space is converted into the standard color space to describe the device color gamut. Color spaces often used in color gamut mapping are CIERGB, CIELAB, CIEXYZ, CIELUV, and the like.
Referring to fig. 1, fig. 1 is a schematic diagram of a color gamut (sRGB) mapping a specific Target display panel (Target color gamut) with standard RGB as a color space. As can be seen from fig. 1, the color gamut denoted sRGB partially overlaps the color gamut denoted Target, and at this time, a reasonable gamut mapping algorithm needs to be used to map the colors outside the color gamut denoted Target in the color gamut denoted sRGB into the color gamut denoted Target.
In the prior art, a common simple method can be to use a 24-color card to perform fitting of a gamut mapping function, and to obtain a more precise fitting result, the fitting function is usually fitted by using a function with a higher power, and the fitting function form of the gamut mapping is as follows:
the relation graph of the fitting error of the fitting function of the color gamut mapping and the fitting power can be seen in fig. 2, and it can be known from the graph that the fitting error is within an acceptable range when the fitting frequency reaches 7 times.
The above approach has several disadvantages: firstly, after a more accurate fitting function is obtained, a larger error of individual color points is easy to occur; second, assuming that there is no large error in the individual color points, the high power function has high difficulty and cost in the implementation of software and hardware.
According to the method, the target color gamut and the source color gamut are divided into a plurality of blocks corresponding to each other, and a plurality of first data and a plurality of second data are classified according to the blocks to obtain a plurality of first data and a plurality of second data in each block; the fitting function of each block is obtained through the first data and the second data in each block, the color gamut of each block is smaller than that of the original block, the target and the pertinence are better achieved, the number of the first data and the number of the second data in each block are smaller than that of the original first data and the original second data, and the first data and the second data in each block are more targeted.
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application.
Referring to fig. 3, fig. 3 is a flowchart of an embodiment of a method for obtaining a gamut mapping fitting function according to the present application, the method including:
step S101: a plurality of first data of a standard color space corresponding to a plurality of known colors of a target color gamut, respectively, are acquired.
The target color gamut is the color gamut of the target panel, and the plurality of known colors are used for calibrating the main or key colors, and the requirement can represent the color gamut range.
Knowing the number of colors, i.e. how many color points are mutually limiting in the accuracy and computational load after gamut conversion. The more the number of the selected known colors is, the higher the accuracy after the color gamut conversion is, the larger the corresponding calculation amount is, and the higher the requirements on hardware and equipment are; the number of the selected known colors is small, the accuracy of the color gamut conversion is low, the corresponding calculation amount is small, and the requirements on hardware and equipment are low. In practical applications, the number of known colors needs to be determined with a trade-off between accuracy and computational effort.
In one embodiment, the plurality of known colors are the colors of a 24 color card. Of course, the plurality of known colors may be standard RGB trichromatic colors, or other representative known colors.
Color space, also known as color model (also known as color space, color model, color system, etc.), is used to describe colors in a generally accepted manner under certain standards. In essence, the color model is a description of the coordinate system and subspace. There is a single dot representation for each color located in the system. Most color models employed are either hardware-oriented or application-oriented. There are many kinds of color spaces, and RGB, CMY, HSV, HIS, Lab, etc. are commonly used.
Because different devices adopt different color spaces, in order to realize color gamut mapping, a uniform standard color space irrelevant to the devices needs to be selected first, and the device color space is converted into the standard color space to describe the device color gamut. Color spaces often used in color gamut mapping are CIERGB, CIELAB, CIEXYZ, CIELUV, and the like.
In one embodiment, the standard color space is an RGB color space, and the first data is RGB data. RGB is a color representing three channels of red, green and blue, and this standard includes almost all colors that can be perceived by human vision, and is one of the most widely used color systems at present.
Step S102: and mapping a plurality of first data respectively corresponding to the plurality of known color points into a plurality of second data of the standard color space of the source color gamut respectively.
The source gamut refers to the gamut of the source panel. In the embodiments of the present application, the gamut mapping requires mapping the colors of the source gamut to the colors of the target gamut. In this step, the plurality of first data are corresponding to the plurality of known colors in the target color gamut, and the plurality of first data corresponding to the plurality of known color points are respectively mapped to the plurality of second data of the standard color space of the source color gamut, that is to say: a plurality of known colors in the target color gamut are mapped to corresponding colors in the source color gamut.
In the present embodiment, if the first data is RGB data, the second data is also RGB data.
In an embodiment, step S102 may specifically be: and mapping a plurality of first data respectively corresponding to a plurality of known color points into a plurality of second data of the source color gamut by the conversion matrix.
If T is a linear transformation that maps Rn to Rm and x is a column vector having n elements, then Matrix A of m × n is referred to as the transformation Matrix of T.
Step S103: the target color gamut and the source color gamut are divided into a plurality of blocks corresponding to each other, and the plurality of first data and the plurality of second data are classified according to the blocks to obtain the plurality of first data and the plurality of second data in each block.
Gamut refers to the spectral range of colors that a device or medium or media can reproduce, and patch refers to the spectral range of colors that can be reproduced smaller than the target and source gamuts. The target color gamut and the source color gamut are divided into a plurality of mutually corresponding blocks, that is, the target color gamut and the source color gamut are divided into a plurality of mutually corresponding smaller range color spectral ranges. After the blocks are classified, it is clear to which block each of the first data belongs, and it is clear to which block each of the second data belongs.
In one embodiment, the dividing the target color gamut and the source color gamut into a plurality of blocks in step S103 may specifically include: the target color gamut and the source color gamut are triangulated into three blocks.
The above-described triangulation method is an example, and other shape division methods may be used in actual practice. Of course, the division into 3 blocks is merely an example, and the division into other numbers may be performed in actual operation. In one embodiment, the division is performed by vertex division, and may be performed by any point in actual operation.
For example: referring to fig. 4, fig. 4 shows the source gamut value (i.e. the second data and RGB data) and the target gamut value (i.e. the first data and RGB data) that have been obtained and divided. The target color gamut and the source color gamut are divided into three corresponding blocks, the source color gamut numerical value and the target color gamut numerical value with the serial numbers of 1-8 are positioned in the 1 st block, the source color gamut numerical value and the target color gamut numerical value with the serial numbers of 9-16 are positioned in the 2 nd block, and the source color gamut numerical value and the target color gamut numerical value with the serial numbers of 17-24 are positioned in the 3 rd block.
Step S104: and respectively obtaining the fitting function of each block through the plurality of first data and the plurality of second data in each block.
The fitting function of each block is obtained through the first data and the second data in each block, the color gamut of each block is smaller than that of the original block, the target and the pertinence are better achieved, the number of the first data and the number of the second data in each block are smaller than that of the original first data and the original second data, and the first data and the second data in each block are more targeted.
With continued reference to fig. 4, the corresponding fitting functions in the three blocks are obtained by:
referring to fig. 5 in combination, color gamut a and color gamut B are a target color gamut and a source color gamut, respectively, and are divided by three vertices, and the color gamut a and the color gamut B are divided into three corresponding blocks, referring to fig. 4 in combination, fitting powers of fitting functions of the three blocks are n, respectively1、n2、n3As can be seen from the figure, n1、n2、n3Smaller numerical values can be effectively obtained, the operation requirement is reduced, the fitting error is reduced, and higher fitting accuracy is provided.
Referring to fig. 6, fig. 6 is a schematic structural diagram of an embodiment of the apparatus for obtaining a color gamut mapping fitting function according to the present application, where the apparatus of the present embodiment may be a display panel, or may be an intermediate device connected to the display panel; the device can execute the steps of the method, and the detailed description of the related contents refers to the method part and is not repeated redundantly.
The device includes: a processor 1, a memory 2 and a communication circuit 3, the processor 1 being coupled to the memory 2 and the communication circuit 3, respectively, wherein:
the processor 1 is configured to control the communication circuit 3 to obtain a plurality of first data of a standard color space corresponding to a plurality of known colors of the target color gamut, and control the memory 2 to store the first data; the processor 1 is configured to map a plurality of first data corresponding to a plurality of known color points into a plurality of second data of a standard color space of a source color gamut, respectively; dividing the target color gamut and the source color gamut into a plurality of blocks corresponding to each other, and classifying the plurality of first data and the plurality of second data according to the blocks to obtain a plurality of first data and a plurality of second data in each block; and respectively obtaining the fitting function of each block through the plurality of first data and the plurality of second data in each block.
The standard color space is an RGB color space, and the first data and the second data are both RGB data.
Wherein the plurality of known colors are the colors of a 24 color card.
The processor 1 is further configured to map, by using the transformation matrix, a plurality of first data corresponding to a plurality of known color points into a plurality of second data of the source color gamut, respectively.
The processor 1 is further configured to divide the target color gamut and the source color gamut into three blocks by triangulation.
Referring to fig. 7, fig. 7 is a schematic structural diagram of an embodiment of the apparatus with storage function according to the present application, where the apparatus 50 stores program data 501, and the program data 501 is executed by a processor to implement the steps in the method according to any one of the above. For further details, reference is made to the above method section, which is not described in detail here.
The method includes the steps that a plurality of first data of a standard color space corresponding to a plurality of known colors of a target color gamut are obtained; mapping a plurality of first data respectively corresponding to the plurality of known color points into a plurality of second data of the standard color space of a source color gamut respectively; dividing the target color gamut and the source color gamut into a plurality of blocks, and classifying the plurality of first data and the plurality of second data according to the blocks to obtain a plurality of first data and a plurality of second data in each block; and respectively obtaining the fitting function of each block through the plurality of first data and the plurality of second data in each block. Dividing the target color gamut and the source color gamut into a plurality of blocks corresponding to each other, and classifying the plurality of first data and the plurality of second data according to the blocks to obtain a plurality of first data and a plurality of second data in each block; the fitting function of each block is obtained through the first data and the second data in each block, the color gamut of each block is smaller than that of the original block, the target and the pertinence are better achieved, the number of the first data and the number of the second data in each block are smaller than that of the original first data and the original second data, and the first data and the second data in each block are more targeted.
The above description is only for the purpose of illustrating embodiments of the present application and is not intended to limit the scope of the present application, and all modifications of equivalent structures and equivalent processes, which are made by the contents of the specification and the drawings of the present application or are directly or indirectly applied to other related technical fields, are also included in the scope of the present application.
Claims (7)
1. A method of obtaining a gamut mapping fitting function, the method comprising:
acquiring a plurality of first data of a standard color space corresponding to a plurality of known colors of a target color gamut respectively;
mapping the first data corresponding to the known color points into second data of the standard color space of the source color gamut;
dividing the target color gamut and the source color gamut into a plurality of blocks corresponding to each other, and classifying the plurality of first data and the plurality of second data according to the blocks to obtain a plurality of first data and a plurality of second data in each block;
obtaining a fitting function of each block through a plurality of first data and a plurality of second data in each block respectively;
the mapping, to a plurality of second data of a source color gamut, a plurality of first data corresponding to the plurality of known color points, respectively, includes:
mapping a plurality of first data respectively corresponding to the plurality of known color points into a plurality of second data of a source color gamut through a conversion matrix;
the dividing the target color gamut and the source color gamut into a plurality of blocks comprises:
the target color gamut and the source color gamut are triangulated into three blocks.
2. The method of claim 1, wherein the standard color space is an RGB color space, and the first data and the second data are both RGB data.
3. The method of claim 1, wherein the plurality of known colors are colors of a 24-color chart.
4. An apparatus for obtaining a gamut mapping fitting function, the apparatus comprising: a processor, a memory, and communication circuitry, the processor coupled with the memory and the communication circuitry, respectively, wherein,
the processor is used for controlling the communication circuit to acquire a plurality of first data of a standard color space corresponding to a plurality of known colors of a target color gamut respectively and controlling the memory to store the first data;
the processor is configured to map the plurality of first data corresponding to the plurality of known color points into a plurality of second data of the standard color space of the source color gamut, respectively; dividing the target color gamut and the source color gamut into a plurality of blocks corresponding to each other, and classifying the plurality of first data and the plurality of second data according to the blocks to obtain a plurality of first data and a plurality of second data in each block; obtaining a fitting function of each block through a plurality of first data and a plurality of second data in each block respectively;
the processor is further configured to map, by using a transformation matrix, a plurality of first data corresponding to the plurality of known color points into a plurality of second data of a source color gamut, respectively; the processor is also configured to triangulate the target color gamut and the source color gamut into three blocks.
5. The apparatus of claim 4, wherein the standard color space is an RGB color space, and the first data and the second data are both RGB data.
6. The apparatus of claim 4, wherein the plurality of known colors are colors of a 24-color card.
7. An apparatus having a storage function, on which program data are stored, characterized in that the program data realize the steps in the method of any of claims 1-3 when executed by a processor.
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| CN201710893594.7A CN107492365B (en) | 2017-09-27 | 2017-09-27 | Method and device for obtaining color gamut mapping fitting function |
| PCT/CN2017/107128 WO2019061600A1 (en) | 2017-09-27 | 2017-10-20 | Method and device for acquiring mapping fitting functions of color gamut |
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| CN100576067C (en) * | 2008-05-20 | 2009-12-30 | 中国人民解放军信息工程大学 | Colorful picture six color separation printing method |
| CN102044230A (en) * | 2010-12-31 | 2011-05-04 | 昆山龙腾光电有限公司 | Liquid crystal display device, color gamut conversion method thereof and color gamut conversion circuit |
| CN102682724B (en) * | 2011-06-10 | 2014-10-08 | 京东方科技集团股份有限公司 | Red, green, blue and white (RGBW) display method and RGBW display device |
| CN102932579B (en) * | 2012-10-17 | 2015-05-20 | 山东轻工业学院 | Method for judging hypercolor gamut during digital image output |
| CN103020639A (en) * | 2012-11-27 | 2013-04-03 | 河海大学 | Method for automatically identifying and counting white blood cells |
| US20150213626A1 (en) * | 2014-01-28 | 2015-07-30 | Innolux Corporation | Gamut mapping |
| US9466260B2 (en) * | 2014-03-26 | 2016-10-11 | Samsung Display Co., Ltd. | Conversion between color spaces |
| CN104103043B (en) * | 2014-07-04 | 2017-02-15 | 上海理工大学 | Spatial gamut mapping method |
| CN106454300B (en) * | 2016-09-19 | 2018-11-02 | 深圳Tcl数字技术有限公司 | Color domain expanding system and method |
| CN106486074B (en) * | 2016-11-01 | 2019-04-02 | 深圳市华星光电技术有限公司 | The display methods of multiple bases graphene display |
| CN106530361A (en) * | 2016-11-16 | 2017-03-22 | 上海市东方医院 | Color correction method for color face image |
| CN106934835B (en) * | 2017-01-12 | 2020-03-03 | 浙江大学 | Color gamut mapping method for textile inkjet printing and dyeing based on spatial network |
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