A color gamut conversion method, device and display device

Abstract

The application discloses a color gamut conversion method and device and a display device. The method comprises the following steps: obtaining initial gray scale values of each sampling pixel in an original color gamut, and calculating color space coordinates of the sampling pixel; obtaining first target gray scale values of the sampling pixel in a target color gamut through a color analyzer according to the color space coordinates; calculating an optimal color gamut conversion matrix of a color gamut conversion model according to the initial gray scale values and the first target gray scale values; and performing color gamut conversion on an input gray scale image according to the calculated optimal color gamut conversion matrix. The color gamut conversion method, device and display device provided by the application can improve the color performance accuracy of a display panel and realize the color unification among multiple display devices.

Description

Technical Field

[0001] This application relates to the field of image display, and in particular to a color gamut conversion method, apparatus and display device. Background Technology

[0002] In recent years, with the increasing popularity of AMOLED display panels, users have higher and higher requirements for display picture quality. People hope that display panels can reproduce the most vibrant colors in nature as accurately as possible. The color gamut of display panels has also expanded from the standard Red Green Blue (sRGB) color gamut space to the Digital Cinema Initiatives (DCI)-P3 wide color gamut space. However, during the production process, limited by processing technology and manufacturing costs, it is difficult to guarantee that every display panel will achieve the same color accuracy. To ensure the uniformity of the original color gamut of display panels, color gamut conversion is necessary to achieve unified color management.

[0003] Currently, mainstream color gamut conversion methods correct the four colors R (red), G (green), B (blue), and W (white). The resulting color gamut conversion matrix has relatively small JNCD values ​​for R, G, B, and W (JNCD is an indicator of color difference; a smaller JNCD value indicates a smaller color difference). However, the JNCD performance for other colors within the color gamut is not ideal. Therefore, it is necessary to provide improved technical solutions to increase the overall JNCD value within the color gamut. Summary of the Invention

[0004] In view of the above problems, the purpose of this application is to provide a color gamut conversion method, apparatus and display device, which can improve the color accuracy of the display panel and achieve color uniformity among multiple display devices.

[0005] This application provides a color gamut conversion method, including the following steps:

[0006] Obtain the initial grayscale value of each sampled pixel in the original color gamut, and calculate the color space coordinates of the sampled pixel;

[0007] Based on the color space coordinates, the first target grayscale value of the sampled pixel in the target color gamut is obtained by a color analyzer.

[0008] The optimal color gamut conversion matrix of the color gamut conversion model is calculated based on the initial grayscale value and the first target grayscale value;

[0009] The input grayscale image is subjected to color gamut conversion based on the calculated optimal color gamut conversion matrix.

[0010] Further, the step of calculating the optimal color gamut conversion matrix of the color gamut conversion model based on the initial grayscale value and the first target grayscale value includes:

[0011] The loss function corresponding to the color gamut conversion model is preset to be:

[0012]

[0013] Based on the initial grayscale value and the first target grayscale value, the optimal color gamut conversion matrix of the color gamut conversion model is solved according to the loss function:

[0014] [R * T * ] = min(E(R, T));

[0015] Among them, [R * T * ] is the optimal color gamut conversion matrix, R is the first prediction reference conversion matrix, and T is the second prediction reference conversion matrix; Gr r Gr g Gr b These are the initial grayscale values ​​for the red, green, and blue sub-pixels, respectively; Gr′ b Gr′ g Gr′ b The first target grayscale values ​​of the red, green, and blue sub-pixels are respectively, and n is the number of samples of the sampled pixels.

[0016] Further, the step of solving for the optimal color gamut conversion matrix of the color gamut conversion model based on the loss function includes:

[0017] The initial grayscale value and the first target grayscale value of the sampled pixel are mapped in three-dimensional space to obtain the initial coordinate set corresponding to the initial grayscale value and the target coordinate set corresponding to the first target grayscale value;

[0018] The initial coordinate set is denoted as: X = {x1, x2, x3, ..., x...} n};

[0019] The target coordinate set is denoted as: Y = {y1, y2, y3, ..., y...} n};

[0020] Transform the initial coordinate set and the target coordinate set into a form with zero mean and unit variance:

[0021]

[0022] The target loss function is obtained based on the preset loss function:

[0023]

[0024] Further, the step of performing color gamut conversion on the input grayscale image based on the calculated optimal color gamut conversion matrix includes:

[0025] Based on the calculated optimal color gamut conversion matrix, the initial grayscale value of the pixel in the original color gamut is converted into the second target grayscale value corresponding to the pixel in the target color gamut;

[0026] Based on the initial grayscale value and the second target grayscale value, a display lookup table is established;

[0027] The color gamut of the input grayscale image is converted using the aforementioned display lookup table.

[0028] Further, the step of converting the initial grayscale value of the pixel in the original color gamut into the second target grayscale value corresponding to the pixel in the target color gamut includes:

[0029] Perform color gamut conversion on the initial grayscale value of the pixel according to the following color gamut conversion model:

[0030]

[0031] Among them, Gr″ r Gr″ g Gr″ b These are the second target grayscale values ​​of the red, green, and blue sub-pixels of the pixel, respectively.

[0032] Furthermore, the color space coordinates of the sampled pixels are standard CIE-XYZ color space coordinates.

[0033] This application also provides a color gamut conversion device, including:

[0034] The first acquisition module is used to acquire the initial grayscale value of each sampled pixel in the original color gamut and calculate the color space coordinates of the sampled pixel;

[0035] The second acquisition module is used to acquire the first target grayscale value of the sampled pixel in the target color gamut by means of a color analyzer based on the color space coordinates.

[0036] The calculation module is used to calculate the optimal color gamut conversion matrix of the color gamut conversion model based on the initial grayscale value and the first target grayscale value;

[0037] The color gamut conversion module is used to perform color gamut conversion on the input grayscale image based on the calculated optimal color gamut conversion matrix.

[0038] Furthermore, the computing module is also used for:

[0039] The loss function corresponding to the color gamut conversion model is preset to be:

[0040]

[0041] Based on the initial grayscale value and the first target grayscale value, the optimal color gamut conversion matrix of the color gamut conversion model is solved according to the loss function:

[0042] [R * T * ] = min(E(R, T));

[0043] Among them, [R * T * ] is the optimal color gamut conversion matrix, R is the first prediction reference conversion matrix, and T is the second prediction reference conversion matrix; Gr r Gr g Gr b These are the initial grayscale values ​​for the red, green, and blue sub-pixels, respectively; Gr′ b Gr′ g Gr′ b The first target grayscale values ​​of the red, green, and blue sub-pixels are respectively, and n is the number of samples of the sampled pixels.

[0044] Furthermore, the color gamut conversion module is also used to convert the initial grayscale value of the pixel in the original color gamut into the second target grayscale value of the pixel in the target color gamut according to the calculated optimal color gamut conversion matrix; establish a display lookup table based on the initial grayscale value and the second target grayscale value; and perform color gamut conversion on the input grayscale image using the display lookup table.

[0045] This application also provides a display device, including the color gamut conversion device described above.

[0046] The color gamut conversion method, apparatus, and display device provided in this application obtain the initial grayscale value of the sampled pixel in the original color gamut and the first target grayscale value in the target color gamut, perform optimal matching of the color gamut conversion model, calculate the optimal color gamut conversion matrix of the color gamut conversion model, and then perform color gamut conversion on the input grayscale image through the calculated optimal color gamut conversion matrix, thereby improving the color performance accuracy of the display panel and realizing color unification among multiple display devices. Attached Figure Description

[0047] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0048] Figure 1 A schematic flowchart of a color gamut conversion method provided in an embodiment of this application;

[0049] Figure 2 This is a schematic diagram of the structure of a color gamut conversion device provided in an embodiment of this application. Detailed Implementation

[0050] The foregoing and other technical contents, features, and effects of this application will be clearly presented in the following detailed description of the preferred embodiments with reference to the accompanying drawings. Through the description of the specific embodiments, a more in-depth and specific understanding can be gained of the technical means and effects adopted by this application to achieve its intended purpose. However, the accompanying drawings are for reference and illustration only and are not intended to limit this application; some well-known parts may not be shown. In the various drawings, the same elements are represented by similar reference numerals. For clarity, the various parts in the drawings are not drawn to scale.

[0051] According to the theory of linear superposition of light, any color is obtained by mixing the three primary colors RGB in a certain proportion. Therefore, color gamut conversion is essentially a conversion of this proportion. The typical process of color gamut conversion is as follows: first, convert the grayscale values ​​of the pixels in the image [Gr...] r Gr g Gr b The brightness is converted to a luminance ratio through gamma transformation, then converted to a new luminance ratio through color gamut conversion. This new luminance ratio is then subjected to inverse gamma transformation to obtain a new set of grayscale values ​​[Gr′]. r ,Gr′ g ,Gr′ b The entire conversion process can be combined into:

[0052]

[0053] R and T represent the grayscale conversion relationship of a pixel from the original color gamut to the target color gamut. Therefore, to achieve high color accuracy after color gamut conversion, an optimal conversion relationship needs to be determined. This application provides a method for calculating the optimal color gamut conversion matrix R and T, resulting in a smaller JNCD value for the overall color after conversion using this optimal matrix, thus achieving higher color accuracy.

[0054] Figure 1 This is a schematic diagram of a color gamut conversion method provided in an embodiment of this application; as shown Figure 1 As shown, the color gamut conversion method provided in this application includes the following steps:

[0055] Step S110: Obtain the initial grayscale value of each sampled pixel in the original color gamut, and calculate the color space coordinates of the sampled pixel;

[0056] Specifically, in some embodiments of this application, the initial grayscale values ​​[Gr] of several pixels in the original image in the current color gamut can be randomly sampled. r Gr g Gr b The standard color space coordinates of the currently sampled pixel in the current color gamut are calculated based on its initial grayscale value. Since the CIE color space, developed by the International Commission on Illumination (CIE) and based on human visual perception, can accurately reproduce images in any device, the color space coordinates in this embodiment are standard CIE-XYZ color space coordinates. The CIE-XYZ colorimetric system ensures consistency in color description and measurement results across different regions and devices. Furthermore, the CIE-XYZ colorimetric system uses mathematical models to describe colors, enabling precise calculations and measurements, which is beneficial for scientific research and engineering applications.

[0057] It should be noted that the color gamut described in the embodiments of this application can be understood as the color gamut space specified in the color standard protocol or the color gamut space that has been generally recognized in the industry, such as the sRGB color gamut space, the National Television System Committee (NTSC) color gamut space, the Adobe RGB color gamut space, and the Display-P3 color gamut space.

[0058] Step S120: Based on the color space coordinates, obtain the first target grayscale value of the sampled pixel in the target color gamut using a color analyzer;

[0059] Specifically, in this embodiment of the application, the optical parameters corresponding to the target color gamut and the sampled color space coordinates are input into a color analyzer, and the first target grayscale value of the sampled pixel in the target color gamut is obtained by the color analyzer.

[0060] Step S130: Calculate the optimal color gamut conversion matrix of the color gamut conversion model based on the initial grayscale value and the first target grayscale value;

[0061] Specifically, step S130 includes the following steps:

[0062] Step S131: The loss function corresponding to the preset color gamut conversion model is:

[0063]

[0064] Step S132: Based on the initial grayscale value and the first target grayscale value, solve for the optimal color gamut conversion matrix of the color gamut conversion model according to the loss function:

[0065] [R * ,T * ] = min(E(R,T));

[0066] Among them, [R * ,T * [R] is the optimal color gamut conversion matrix, R is the first prediction reference conversion matrix, and T is the second prediction reference conversion matrix; Gr r Gr g Gr b These are the initial grayscale values ​​for the red, green, and blue sub-pixels, respectively; Gr′ r Gr′ g Gr′ b These are the first target grayscale values ​​for the red, green, and blue sub-pixels, respectively, and n is the number of samples for the sampled pixels.

[0067] Specifically, the process of solving the optimal color gamut conversion matrix includes:

[0068] The initial grayscale value of the sampled pixel and the grayscale value of the first target are mapped in three-dimensional space to obtain the initial coordinate set corresponding to the initial grayscale value and the target coordinate set corresponding to the first target grayscale value;

[0069] The initial coordinate set is denoted as: X = {x1, x2, x3, ..., x n};

[0070] The target coordinate set is denoted as: Y = {y1, y2, y3, ..., y n};

[0071] By decentralizing, the initial and target coordinate sets are transformed into forms with zero mean and unit variance:

[0072]

[0073] The target loss function is obtained based on the preset loss function:

[0074]

[0075] but:

[0076]

[0077] Expanding the above formula (1), we get:

[0078]

[0079] Because the first term in the expanded formula is related to R * Irrelevant, the second term R T ·R=E(3) is also related to R * Since it is irrelevant, the optimization objective becomes:

[0080]

[0081]

[0082] Solving linear least squares problems using singular value decomposition (SVD):

[0083] make

[0084] Then R * =argmin(-trace(R·W));

[0085] Perform singular value decomposition on W:

[0086] W = UΛV T ;

[0087] Among them, U, V T All are orthogonal matrices, Λ being a main diagonal matrix;

[0088] In order to make R * If the minimum value is taken, then trace(R·W) takes the maximum value;

[0089] Based on the commutative property of matrix traces: trace(A·B) = trace(B·A), then:

[0090] trace(R·W) = trace(R·UΛV) T ) = trace(Λ·V T RU);

[0091] When R * =R=VU T When the diagonal elements of an orthogonal matrix are at most 1, trace(R·W) reaches its maximum value.

[0092] trace(R·W) = trace(R·UΛV) T ) = trace(Λ·V T VUT U);

[0093] Similarly, we can obtain T. * The value,

[0094]

[0095] Step S140: Perform color gamut conversion on the input grayscale image based on the calculated optimal color gamut conversion matrix.

[0096] Specifically, based on the calculated optimal color gamut conversion matrix [R] * T * ], the initial grayscale values ​​of pixels in the original color gamut [Gr r Gr g Gr b Convert [Gr″] to the second target grayscale value corresponding to the pixel in the target color gamut. r Gr″ g Gr″ b That is, to perform color gamut conversion on the initial grayscale value of the pixel according to the following color gamut conversion model:

[0097]

[0098] Among them, Gr″ r Gr″ g Gr″ b These are the second target grayscale values ​​for the red, green, and blue sub-pixels of the pixel, respectively.

[0099] Based on the initial grayscale value and the second target grayscale value of each pixel, a look-up table (LUT) is established. The LUT is used to perform color gamut conversion on the input grayscale image. That is, the original image input to the display device is mapped to the pixel grayscale value according to the LUT, and the new grayscale value of each pixel in the image after color gamut conversion is obtained. The grayscale image is displayed according to the converted pixel grayscale value, so that the same image can show the most similar color performance effect on different display devices.

[0100] Based on the content described in the above embodiments, this application also provides a color gamut conversion device, with reference to... Figure 2 , Figure 2 This is a schematic diagram of a color gamut conversion device provided in an embodiment of this application. In this implementation, the color gamut conversion device 200 includes:

[0101] The first acquisition module 210 is used to acquire the initial grayscale value of each sampled pixel in the original color gamut and calculate the color space coordinates of the sampled pixel;

[0102] The second acquisition module 220 is used to acquire the first target grayscale value of the sampled pixel in the target color gamut based on the color space coordinates through a color analyzer;

[0103] Calculation module 230 is used to calculate the optimal color gamut conversion matrix of the color gamut conversion model based on the initial grayscale value and the first target grayscale value;

[0104] The color gamut conversion module 240 is used to perform color gamut conversion on the input grayscale image based on the calculated optimal color gamut conversion matrix.

[0105] Furthermore, the calculation module 230 is also used to: preset the loss function corresponding to the color gamut conversion model as:

[0106]

[0107] Based on the initial grayscale value and the first target grayscale value, the optimal color gamut conversion matrix of the color gamut conversion model is solved according to the loss function:

[0108] [R * ,T * ] = min(E(R,T));

[0109] Among them, [R * ,T * [R] is the optimal color gamut conversion matrix, R is the first prediction reference conversion matrix, and T is the second prediction reference conversion matrix; Gr r Gr g Gr b These are the initial grayscale values ​​for the red, green, and blue sub-pixels, respectively; Gr′ r Gr′ g Gr′ b These are the first target grayscale values ​​for the red, green, and blue sub-pixels, respectively, and n is the number of samples for the sampled pixels.

[0110] Furthermore, the color gamut conversion module 240 is also used to convert the initial grayscale value of the pixel in the original color gamut into the second target grayscale value corresponding to the pixel in the target color gamut according to the calculated optimal color gamut conversion matrix; establish a display lookup table based on the initial grayscale value and the second target grayscale value; and perform color gamut conversion on the input grayscale image using the display lookup table.

[0111] This application also provides a display device, including the color gamut conversion device described above. The display device can be any type of device with a display panel, such as a smartphone, smart bracelet, car navigation system, desktop computer, laptop computer, and smart TV.

[0112] In summary, the color gamut conversion method, apparatus, and display device provided in this application obtain the initial grayscale value of the sampled pixel in the original color gamut and the first target grayscale value in the target color gamut, perform optimal matching of the color gamut conversion model, calculate the optimal color gamut conversion matrix of the color gamut conversion model, and then perform color gamut conversion on the input grayscale image using the calculated optimal color gamut conversion matrix, thereby improving the color performance accuracy of the display panel and achieving color unification among multiple display devices.

[0113] In the description of this application, unless otherwise expressly specified and limited, the terms "first," "second," "third," etc., are used merely to distinguish elements with similar properties and are not intended to indicate or imply relative importance or a particular order. The terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, which includes not only the listed elements but also other elements not expressly listed.

[0114] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A color gamut conversion method, characterized in that, Includes the following steps: Obtain the initial grayscale value of each sampled pixel in the original color gamut, and calculate the color space coordinates of the sampled pixel; Based on the color space coordinates, the first target grayscale value of the sampled pixel in the target color gamut is obtained by a color analyzer. The optimal color gamut conversion matrix of the color gamut conversion model is calculated based on the initial grayscale value and the first target grayscale value; The input grayscale image is subjected to color gamut conversion based on the calculated optimal color gamut conversion matrix; The step of calculating the optimal color gamut conversion matrix of the color gamut conversion model based on the initial grayscale value and the first target grayscale value includes: The loss function corresponding to the color gamut conversion model is preset to be: ； Based on the initial grayscale value and the first target grayscale value, the optimal color gamut conversion matrix of the color gamut conversion model is solved according to the loss function: ； in, Let R be the optimal color gamut conversion matrix, R be the first prediction reference conversion matrix, and T be the second prediction reference conversion matrix; , , These are the initial grayscale values ​​for the red, green, and blue sub-pixels, respectively. , , The first target grayscale values ​​of the red, green, and blue sub-pixels are respectively, and n is the number of samples of the sampled pixels.

2. The color gamut conversion method according to claim 1, characterized in that, The step of solving for the optimal color gamut conversion matrix of the color gamut conversion model based on the loss function includes: The initial grayscale value and the first target grayscale value of the sampled pixel are mapped in three-dimensional space to obtain the initial coordinate set corresponding to the initial grayscale value and the target coordinate set corresponding to the first target grayscale value; The initial coordinate set is denoted as: ; The target coordinate set is denoted as: ; Transform the initial coordinate set and the target coordinate set into a form with zero mean and unit variance: ； ； The target loss function is obtained based on the preset loss function: 。 3. The color gamut conversion method according to claim 2, characterized in that, The step of performing color gamut conversion on the input grayscale image based on the calculated optimal color gamut conversion matrix includes: Based on the calculated optimal color gamut conversion matrix, the initial grayscale value of the pixel in the original color gamut is converted into the second target grayscale value corresponding to the pixel in the target color gamut; Based on the initial grayscale value and the second target grayscale value, a display lookup table is established; The color gamut of the input grayscale image is converted using the aforementioned display lookup table.

4. The color gamut conversion method according to claim 3, characterized in that, The step of converting the initial grayscale value of the pixel in the original color gamut into the second target grayscale value corresponding to the pixel in the target color gamut includes: Perform color gamut conversion on the initial grayscale value of the pixel according to the following color gamut conversion model: ； in, , , These are the second target grayscale values ​​of the red, green, and blue sub-pixels of the pixel, respectively.

5. The color gamut conversion method according to claim 1, characterized in that, The color space coordinates of the sampled pixels are standard CIE-XYZ color space coordinates.

6. A color gamut conversion device, characterized in that, include: The first acquisition module is used to acquire the initial grayscale value of each sampled pixel in the original color gamut and calculate the color space coordinates of the sampled pixel; The second acquisition module is used to acquire the first target grayscale value of the sampled pixel in the target color gamut by means of a color analyzer based on the color space coordinates. The calculation module is used to calculate the optimal color gamut conversion matrix of the color gamut conversion model based on the initial grayscale value and the first target grayscale value; The color gamut conversion module is used to perform color gamut conversion on the input grayscale image based on the calculated optimal color gamut conversion matrix. The computing module is also used for: The loss function corresponding to the color gamut conversion model is preset to be: ； Based on the initial grayscale value and the first target grayscale value, the optimal color gamut conversion matrix of the color gamut conversion model is solved according to the loss function: ； in, Let R be the optimal color gamut conversion matrix, R be the first prediction reference conversion matrix, and T be the second prediction reference conversion matrix; , , These are the initial grayscale values ​​for the red, green, and blue sub-pixels, respectively. , , The first target grayscale values ​​of the red, green, and blue sub-pixels are respectively, and n is the number of samples of the sampled pixels.

7. The color gamut conversion device according to claim 6, characterized in that, The color gamut conversion module is also used to convert the initial grayscale value of the pixel in the original color gamut into the second target grayscale value of the pixel in the target color gamut according to the calculated optimal color gamut conversion matrix. Based on the initial grayscale value and the second target grayscale value, a display lookup table is established; the display lookup table is used to perform color gamut conversion on the input grayscale image.

8. A display device, characterized in that, Includes the color gamut conversion device as described in claim 6 or 7.

Images