Visual Spatial Color Gamut Model Establishment Method and Interaction Method

Abstract

The present application provides a method for establishing a visual spatial color gamut model and an interaction method. The method for establishing the visual spatial color gamut model includes: establishing a three-dimensional color model; wherein, the three-dimensional color model takes the hue circle as the reference plane, establishes a lightness axis perpendicular to the reference plane, represents the position along the lightness axis with a lightness value, and represents the radial spatial distance value from the center of the hue circle to any point with a chroma value; obtaining first color data and mapping the first color data to the corresponding position in the three-dimensional color model; generating a visual color sample representing the first color data based on the first color data and the position of the first color data in the three-dimensional color model; arranging a plurality of visual color samples to construct a visual spatial color gamut model. The present application realizes the optimized utilization of the color space by converting the traditional color model into a three-dimensional display. Users can more conveniently perform color matching and accurately and quickly find colors.

Description

Technical Field

[0001] This application relates to the technical field of digital inkjet printing, and particularly relates to a method for establishing a visual spatial color gamut model and an interaction method. Background Art

[0002] Currently, in the field of solid-color inkjet printing technology, the process of color matching mainly involves linearizing the inkjet printing first, restricting the amount of single-color ink used, and then printing a fixed color chart set and measuring the color data LAB values (Lab values are important color control and management indicators in the color system) of the color chart set. After that, a professional color management software such as Neostampa is used to generate an ICC profile related to this printing device. When an image needs to be printed, the printing software reads the image color information RGB or CMYK (printing four-color mode) of the design file, and through the CMM color conversion module, converts the color into the CMYK or multi-channel separation information of this inkjet printer.

[0003] In the solid-color printing in the textile industry, due to the lack of standardized connection and definition of the actual ink used for "printable colors", the printing substrate fabric, and the subsequent process flow, there is a lack of a method for establishing a color system and database to manage the colors in the color gamut space that can be achieved by the printer, which can no longer meet the requirements of designers for more colors, resulting in designers being unable to select colors according to their needs. In addition, when making physical colors, each specific color needs to be dyed in a traditional dye vat by mixing dyes, and the final satisfactory color is selected through color difference data selection and visual evaluation. The color gamut dye liquor is restricted by the characteristics of dye color mixing, resulting in some colors being unable to be replicated quickly, thus unable to improve the problem of color communication consistency between the color design end and the production supplier, and reducing the color communication efficiency and proofing production efficiency. Summary of the Invention

[0004] The purpose of the embodiments of this application is to provide a method for establishing a visual spatial color gamut model and an interaction method. By converting the traditional color model into a three-dimensional display, the optimized utilization of the color space is realized, making color selection and change more intuitive and balanced. Users can more conveniently perform color matching and accurately and quickly find colors.

[0005] In a first aspect, the present application provides a method for establishing a visual spatial color gamut model, the method comprising: establishing a three-dimensional color model; wherein, the three-dimensional color model uses a color wheel as a reference plane, establishing a lightness axis perpendicular to the reference plane, representing the position along the lightness axis with a lightness value, and representing the radial spatial distance value from the center of the color wheel to any point with a chroma value; obtaining first color data, and mapping the first color data to a corresponding position in the three-dimensional color model; generating a visual color sample representing the first color data based on the first color data and the position of the first color data in the three-dimensional color model; arranging a plurality of the visual color samples to construct a visual spatial color gamut model.

[0006] In one embodiment, after establishing the three-dimensional color model, the method further comprises the following steps: obtaining a first threshold range of the color wheel to define a hue range; obtaining a second threshold range of the lightness value to define a height range; obtaining a third threshold range of the chroma value to define a radial distance range; making the three-dimensional color model present as a regular sphere according to the first threshold range, the second threshold range, and the third threshold range.

[0007] In one embodiment, the obtaining of the first color data comprises the following steps: obtaining discrete color data, the discrete color data being obtained by discretizing a preset basic color model based on a preset data screening strategy; obtaining a conversion relationship between the basic color model and the three-dimensional color model, and converting the discrete color data into corresponding first color data in the three-dimensional color model, wherein the three-dimensional color model is different from the basic color model.

[0008] In one embodiment, the discrete color data is obtained by discretizing a preset basic color model based on a preset data screening strategy, and comprises the following steps: the discrete color data is obtained by discretizing the colors in the basic color model according to the equal-distance principle by using a preset selected color difference value to generate a series of discrete color data with uniform color differences.

[0009] In one embodiment, the discrete color data is obtained by discretizing the colors in the basic color model according to the equal-distance principle by using a preset selected color difference value to generate a series of discrete color data with uniform color differences. The steps for obtaining the discrete color data are as follows: Using the preset selected color difference value as the edge length of a regular polyhedron and constructing an array of regular polyhedrons through space tiling to divide the preset basic color model; determining the reference color point data of the basic color model; the reference color point data coincides with the vertex or center point of a certain regular polyhedron in the regular polyhedron array, and equidistant color difference discrete point data of the vertices of each regular polyhedron in the basic color model is obtained, thereby obtaining the discrete color data.

[0010] In one embodiment, the discrete color data is obtained by discretizing the colors in the basic color model according to the equal-distance principle by using a preset selected color difference value to generate a series of discrete color data with uniform color differences. The steps for obtaining the discrete color data further include: obtaining a color difference value sequence with multiple gradient levels, where any one of the gradient levels corresponds to a color difference value; based on each gradient level in the color difference value sequence, respectively determining the color difference value as the selected color difference value, and obtaining the corresponding discrete color data by discretizing the preset basic color model based on each selected color difference value.

[0011] In one embodiment, the following steps are further included: constructing a corresponding visual space color gamut model based on the discrete color data corresponding to each selected color difference value, thereby constructing multiple visual space color gamut models corresponding to the color difference values of multiple gradient levels in the color difference value sequence.

[0012] In one embodiment, the discretizing the colors in the basic color model according to the equal-distance principle includes the following steps: The basic color model includes three dimensions of lightness value, red-green degree value, and yellow-blue degree value, and the colors in the basic color model are discretized according to the equal-distance principle of the three dimensions of lightness value, red-green degree value, and yellow-blue degree value.

[0013] In one embodiment, based on the lightness value, the red-green degree value, and the yellow-blue degree value of the basic color model, it further includes: obtaining a fourth threshold range of the lightness value to define the brightness range; obtaining a fifth threshold range of the red-green degree value to define the red-green degree range; obtaining a sixth threshold range of the yellow-blue degree value to define the yellow-blue degree range.

[0014] Second aspect, the present application provides a method for visualizing a spatial color gamut model interaction, and the method includes the following steps: in response to a user's color gamut model selection operation, determining first color data; displaying on a user interface the visual spatial color gamut model corresponding to the first color data; wherein, the visual spatial color gamut model is constructed by the method described in any embodiment of the first aspect of the present application: establishing a three-dimensional color model; wherein, the three-dimensional color model takes a color wheel as a reference plane, establishing a lightness axis perpendicular to the reference plane, representing the position along the lightness axis with a lightness value, and representing the radial spatial distance value from the center of the color wheel to any point with a chroma value; obtaining the first color data, and mapping the first color data to a corresponding position in the three-dimensional color model; based on the first color data and the position of the first color data in the three-dimensional color model, generating a visual color sample representing the first color data, and arranging a plurality of the visual color samples to construct a visual spatial color gamut model.

[0015] In one embodiment, the step of in response to a user's color gamut model selection operation, determining first color data; and displaying on a user interface the visual spatial color gamut model corresponding to the first color data includes the following steps: in response to a user's color gamut model selection operation, based on a preset color difference value sequence with multiple gradient levels, where any one of the gradient levels corresponds to a color difference value, determining one of the color difference values from the color difference value sequence as the selected color difference value; based on the correspondence between the preset color difference value and the preset first color data, determining the first color data corresponding to the selected color difference value; and displaying on the user interface the visual spatial color gamut model constructed corresponding to the first color data.

[0016] In one embodiment, the method further includes the following steps: in response to a user's color sample selection operation on the visual spatial color gamut model, determining that one or more of the visual color samples are selected as target objects.

[0017] In one embodiment, the step of in response to a user's color sample selection operation on the visual spatial color gamut model, determining that one or more of the visual color samples are selected as target objects further includes the following steps: in response to a user's preliminary color sample selection operation on the visual spatial color gamut model, determining that one or more of the visual color samples are selected as preliminary target objects; based on the preliminary target objects, generating one or more recommended target objects according to a preset recommendation strategy; and in response to a user's final color sample selection operation on the visual spatial color gamut model, determining that one or more of the recommended target objects are selected as target objects from the recommended target objects.

[0018] In one embodiment, generating one or more recommended target objects based on the preliminary target object according to a preset recommendation strategy further includes the following steps: Based on the preliminary target object, according to a preset color space distance threshold, determine, on the visualized spatial color gamut model, a visualized color sample whose color space distance from the preliminary target object is less than or equal to the specified threshold as the recommended target object.

[0019] In one embodiment, in response to a user's selection operation on a color sample of the visualized spatial color gamut model to determine that one or more of the visualized color samples are selected as target objects, it further includes the following steps: Receive the text input provided by the user; in response to the text input, call a preset artificial intelligence model to perform semantic analysis on the text input to obtain semantic features associated with the text input; based on the semantic features, determine, on the visualized spatial color gamut model, the visualized color sample with the highest degree of association with the semantic features as the target object.

[0020] In one embodiment, in response to a user's selection operation on a color sample of the visualized spatial color gamut model to determine that one or more of the visualized color samples are selected as target objects, it further includes the following steps: Receive the image input provided by the user; in response to the image input, extract the main color of the image input; based on the main color, determine, on the visualized spatial color gamut model, the visualized color sample closest to the main color as the target object.

[0021] In one embodiment, it further includes the following steps: In response to a user's selection operation on a color sample of the visualized spatial color gamut model, determine that one or more of the visualized color samples are highlighted in the visualized spatial color gamut model.

[0022] In one embodiment, it further includes the following steps: In response to a user's dragging operation on a color sample of the visualized spatial color gamut model, determine the moving distance and moving direction corresponding to the color sample dragging operation, determine the dragged distance of the visualized color sample based on the moving distance and the moving direction, and control the visualized color sample to move the dragged distance in the moving direction.

[0023] In one embodiment, it further includes the following steps: In response to a user's rotation operation on the visualized spatial color gamut model, rotate the visualized spatial color gamut model according to the rotation operation.

[0024] In one embodiment, the following steps are further included: in response to a perspective operation by a user on the visualized spatial color gamut model, adjusting the simulated field depth of the visualized spatial color gamut model according to the perspective operation, so as to display, on a user interface, visualized color samples located inside the visualized spatial color gamut model based on the simulated field depth.

[0025] In a third aspect, the present application provides a visualized spatial color gamut model establishment device, which is applied to the visualized spatial color gamut model establishment method according to any one of the embodiments in the first aspect of the present application, and includes: a establishment module, configured to establish a three-dimensional color model; the three-dimensional color model uses a hue circle as a reference plane, establishes a lightness axis perpendicular to the reference plane, represents the position along the lightness axis direction with a lightness value, and represents the radial spatial distance value from the center of the hue circle to any point outward with a chroma value; an acquisition module, configured to acquire first color data; a mapping module, configured to map the first color data to a corresponding position in the three-dimensional color model; a construction module, configured to generate, based on the first color data and the position of the first color data in the three-dimensional color model, a visualized color sample representing the first color data, and the arrangement of the visualized color samples constructs a visualized spatial color gamut model.

[0026] In a fourth aspect, the present application provides an electronic device, which includes: a processor; a memory for storing instructions executable by the processor; wherein, the processor is configured to execute the visualized spatial color gamut model establishment method according to any one of the first aspects of the present application, or execute the visualized spatial color gamut model interaction method according to any one of the second aspects of the present application.

[0027] In a fifth aspect, the present application provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, it implements the visualized spatial color gamut model establishment method according to any one of the first aspects of the present application, or executes the visualized spatial color gamut model interaction method according to any one of the second aspects of the present application.

[0028] In a sixth aspect, the present application provides a computer-readable storage medium, which stores a computer program, and when the computer program is run by a processor, it is used to execute the visualized spatial color gamut model establishment method according to any one of the first aspects of the present application, or execute the visualized spatial color gamut model interaction method according to any one of the second aspects of the present application.

[0029] Through precise color mapping and continuous variation, this application can more effectively display the relationships and trends between color data, enhancing the expressiveness of data visualization. By converting the traditional color model into a three-dimensional display, the optimal utilization of the color space is achieved, making color selection and variation more intuitive and balanced. Users can more conveniently perform color matching and accurately and quickly find colors, thus transforming complex color theories into simple and understandable visualization tools and enabling users to use colors more easily. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] To more clearly illustrate the technical solutions of the embodiments of this application, the following will briefly introduce the drawings required for use in the embodiments. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as limiting the scope. For those of ordinary skill in the art, without creative efforts, other related drawings can also be obtained based on these drawings.

[0031] Figure 1 Flow diagram of the method for establishing a visualization space color gamut model provided by an embodiment of this application;

[0032] Figure 2 Schematic diagram of a three-dimensional color model provided by an embodiment of this application;

[0033] Figure 3 Cross-sectional view of a three-dimensional color model provided by an embodiment of this application;

[0034] Figure 4 Schematic diagram of mapping the first color data to a three-dimensional color model provided by an embodiment of this application;

[0035] Figure 5 Schematic diagram of a visualization space color gamut model provided by an embodiment of this application;

[0036] Figure 6 Spatial coordinate schematic diagram of a three-dimensional space color model provided by an embodiment of this application;

[0037] Figure 7 Flow diagram of the method for interacting with a visualization space color gamut model provided by an embodiment of this application;

[0038] Figure 8 Schematic diagram of a device for establishing a visualization space color gamut model provided by an embodiment of this application;

[0039] Figure 9 Schematic diagram of the structure of an electronic device provided by an embodiment of this application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0040] Next, the technical solutions in the embodiments of the present application will be described with reference to the accompanying drawings in the embodiments of the present application.

[0041] Similar reference numerals and letters denote similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of the present application, terms such as "first" and "second" are only used for distinguishing descriptions and cannot be construed as indicating or implying relative importance.

[0042] Next, the technical solutions of the present application will be described with reference to the accompanying drawings.

[0043] In the field of pure-color inkjet printing technology, the process of color matching mainly linearizes the printing device, restricts the amount of monochromatic ink used, and then prints a fixed color table set, measures the Lab values of the color data of the color table set, and generates a printing characteristic file related to the printing device through professional color management software. The printing software reads the image color information of the design file, and then performs color conversion on the graphic color information to convert it into multi-channel color separation information on the printing device.

[0044] However, the existing inkjet printing technology has difficulty in realizing the problem of rapid color reproduction according to the characteristics of the printing device and the characteristics of the ink, resulting in a decrease in the color communication efficiency between the color design end and the production and supply end, and ultimately leading to a decrease in the printing production efficiency.

[0045] To solve the above technical problems, the present application establishes a set of visual spatial color gamut models to realize the color implementation path from computer color design to printable by the printing device. By establishing a set of visual spatial color gamut models, it can provide users with a way to quickly obtain ideal printing colors, and further improve the problem of poor color matching effect of the printing device.

[0046] Please refer to Figure 1 , which is a schematic flowchart of a method for establishing a visual spatial color gamut model provided by an embodiment of the present application. The method of the present application is applied to the server side. As an example, the server side can be a single computer or a computer cluster.

[0047] In the present application, through precise color mapping and continuous change, the relationship and trend between color data can be more effectively displayed, enhancing the expressiveness of data visualization. By converting the traditional color model into a three-dimensional display, the optimal utilization of the color space is realized, making color selection and change more intuitive and balanced. Users can more conveniently compare the differences between different colors, perform color matching, and accurately and quickly find colors, thus transforming complex color theories into simple and understandable visualization tools and making it easier for users to use colors.

[0048] Specifically, the method for establishing a spatial color gamut model in this application includes the following steps S110 - S130:

[0049] Step S110: Establish a three - dimensional color model; among them, the three - dimensional color model uses the color wheel as the reference plane, establishes a lightness axis perpendicular to the reference plane, represents the position along the lightness axis with a lightness value, and represents the radial spatial distance value from the center of the color wheel to any point with a chroma value.

[0050] In color science, the LCH color model is a color space based on human visual perception. It consists of three components, namely: lightness (abbreviated as L), chroma (abbreviated as C), and hue (abbreviated as H). As an example, the three - dimensional color model described in this step can be an LCH color model.

[0051] Please refer to Figure 2 shown. Among them, hue is the H component in the LCH color model, which describes the type of color, such as red, green, blue, etc. Hue is usually represented by an angle, ranging from 0° to 360°, indicating the position of the color on the color wheel. When establishing the three - dimensional color model in this step, the color wheel is used as the reference plane. The color wheel is divided into 24 hue zones, each zone is divided into 8 sub - zones, the range of each zone is 1.875 degrees, and it is divided into 192 color sub - zones in total. Please refer to Figure 3 shown.

[0052] Lightness is the L component in the LCH color model, which describes the light and dark degree of the color, that is, the brightness level of the color. The position along the lightness axis is represented by a lightness value, which can be expressed as a vector parameter in the direction perpendicular to the reference plane of the color wheel. The higher the lightness value, the brighter the color looks. On the contrary, the lower the lightness value, the darker the color looks.

[0053] Chroma is the C component in the LCH color model, which describes the purity or saturation of the color, that is, the intensity or vividness of the color. The radial spatial distance value from the center of the color wheel to any point is represented by a chroma value. The higher the chroma value, the more vivid the color looks. The lower the chroma value, the softer the color looks or the closer it is to gray.

[0054] It can be understood that the purpose of step S110 is to establish a spatial coordinate system of a three - dimensional color model, where the reference plane of the color wheel, the chroma value, and the lightness value respectively represent the X, Y, and Z axes of the spatial coordinate system of the three - dimensional color model. Please refer to Figure 2As shown above. In the above embodiments, in the three-dimensional color model, the color perpendicular to the hue ring is used to represent the lightness, which is consistent with the human perception of the linear change of lightness, enabling users to intuitively adjust the brightness of the color. The gap distance from the center of the hue ring outward is used to represent the chroma, which conforms to the human perception of the radial change of chroma, enabling users to adjust the vividness of the color by observation. A circular hue ring is used to represent the hue, which perfectly fits the human acquisition of the hue, making the relationship between adjacent colors clearer and making it easier to understand the concept of complementary colors. Therefore, users can more conveniently compare the differences between different colors, perform color matching, and accurately and quickly find colors.

[0055] Step S120: Obtain the first color data and map the first color data to the corresponding position in the three-dimensional color model.

[0056] The first color data can be the color defined by the user as needed, and the first color data includes: the hue parameter, the chroma value parameter, and the lightness value parameter of the color defined by the user.

[0057] For example, if the user needs to establish the color data of blue, based on the description of the three components of lightness, chroma, and hue above, when the user determines the hue parameter, chroma value parameter, and lightness value parameter of the blue color, it indicates that the spatial coordinate system of the blue color in the three-dimensional color model is determined. According to the hue parameter data, chroma value data, and lightness value data of the blue color, the position of the blue color in the three-dimensional color model can be determined. Therefore, the user can find the unique position corresponding to the blue in the three-dimensional color model coordinate system based on the color data of the set hue parameter, chroma value parameter, and lightness value parameter of blue. Please refer to Figure 4 As shown.

[0058] Step S130: Generate a visual color sample representing the first color data based on the first color data and the position of the first color data in the three-dimensional color model; arrange several visual color samples to construct a visual spatial color gamut model.

[0059] When the user adjusts the chroma value of the blue color or the lightness value of the blue color as needed, different chroma or different lightness color change effects of the blue color will be presented in the three-dimensional color model. If the user needs to adjust the color, the user can first adjust the hue, and then adjust the chroma value and the lightness value, so as to present color change effects of other colors different from the blue color in the three-dimensional color model to meet the color requirements in different scenarios.

[0060] Therefore, the user can generate a visual color sample of the first color data (e.g., blue) based on the first color data and its position in the three-dimensional color model. In the same way, visual color samples of other types of colors can be obtained. According to the hue circle divided into 24 hue zones and 192 sub-color zones as described above, the user can obtain a series of visual color samples for representing 24 colors such as yellow, green, red, etc. The visual color samples of all 24 colors are arranged to form a visual space color gamut model. Please refer to Figure 5 as shown.

[0061] In some embodiments, after step S110, the method further includes steps S111 - S114:

[0062] Step S111: Obtain the first threshold range of the hue circle to define the hue range.

[0063] As mentioned above, hue is usually represented by an angle, ranging from 0° to 360°, indicating the position of the color on the color wheel. Therefore, take 0° to 360° as the first threshold range of the hue circle to define the hue range.

[0064] Step S112: Obtain the second threshold range of the lightness value to define the height range.

[0065] The range of lightness is usually from 0 (black) to 100 (white), indicating the brightness of the color. Therefore, take 0% to 100% as the second threshold range of the lightness value to define the height range.

[0066] Step S113: Obtain the third threshold range of the chroma value to define the radial distance range.

[0067] The range of chroma is usually from 0 (gray, no color) to infinity. However, the maximum value of chroma is limited by the color gamut of the specific printing device or display device. In actual color picking, the maximum value of chroma is usually determined according to the capabilities and conditions of the printing device. Therefore, take 0% to 100% as the third threshold range of the chroma value to define the radial distance range.

[0068] Step S114: Make the three-dimensional color model present as a regular sphere according to the first threshold range, the second threshold range, and the third threshold range.

[0069] Through steps S111 - S113, the hue range, the lightness range, and the chroma range are respectively defined, which is equivalent to determining the coordinate ranges of the X-axis, Y-axis, and Z-axis in the space coordinate system of the three-dimensional color model. Thus, a three-dimensional color model presenting a regular spherical shape is constructed, as Figure 6 shown.

[0070] It can be understood that in this spherical three-dimensional color model, each color data has a unique coordinate parameter in this spherical three-dimensional color model.

[0071] The three-dimensional color model represented by a sphere allows for more flexible color selection and adjustment in the three dimensions of hue, lightness, and chroma, meeting the color requirements in different scenarios. Through the three-dimensional color model represented by a sphere, color samples can be generated and presented, providing a richer form of expression for data visualization.

[0072] Since when establishing the three-dimensional color model, when the variation ranges of the chroma values and lightness values of the colors within the same hue region are small, the color differences presented by the colors within the same hue region are small and difficult to distinguish by the human eye. When printing colors according to the colors in the visualization space gamut model through a printing device, it is even more difficult to distinguish the differences between each color.

[0073] To solve this problem, in some embodiments, step S111 may include steps S1111 - S1112:

[0074] Step S1111: Obtain discrete color data, which is obtained by discretizing a preset basic color model based on a preset data screening strategy.

[0075] Step S1112: Obtain the conversion relationship between the basic color model and the three-dimensional color model, and convert the discrete color data into corresponding first color data in the three-dimensional color model, where the three-dimensional color model is different from the basic color model.

[0076] The basic color model refers to the color data representing the colors that the user sets to be printed, and should have a hue value, a lightness value, and a chroma value. The purpose of discretizing the basic color model is to obtain a series of discrete color data with more obvious color differences. If the obtained discrete color data wants to present the color difference effect of the colors presented by the printing device, the discrete color data needs to be converted into the coordinate system of the three-dimensional color model according to the preset space conversion relationship, because as long as obvious color effects can be presented in the three-dimensional color model, then when the printing device performs a printing operation according to the corresponding colors in the visualization space gamut model, a more obvious printing effect of colors can be presented.

[0077] In the above steps, a certain basic color model set by the user is discretized so that the color differences between adjacent colors in this type of color are more obvious, and then the discrete color data after the discrete processing is converted into the three-dimensional color model, thereby constructing a visualization space gamut model.

[0078] As an example, taking the blue color set by the user as an example, the basic color model of blue is discretized so that the color difference between adjacent blue colors among all blue colors is greater, and then the discrete blue color data after the discrete processing is converted into the corresponding blue color data in the three-dimensional color model.

[0079] In some embodiments, step S1111 may include step S11110: The discrete color data is discretized based on a preset selected color difference value according to the equal-distance principle for the colors in the basic color model to generate a series of discrete color data with uniform color differences, thereby obtaining the discrete color data.

[0080] Color difference refers to the perceivable difference between two colors. The color difference value can be expressed as the lightness difference degree between two adjacent colors. The color difference value can be calculated using various calculation formulas, such as CIE76, CIR94, CIEDE2000, CMC, etc. In this embodiment, the CMC formula can be used as the color difference calculation formula.

[0081] In the memory of the server, the CMC( l :c) color difference calculation formula can be preset in advance, as shown in Equation (1). According to the color difference calculation formula, the preset selected color difference value can be calculated. The CMC( l :c) color difference formula was recommended by the Color Measurement Committee of the Society of Dyers and Colourists (CMC) in 1984. The CMC( l :c) color difference formula introduces the lightness weight factor " l " and the chroma weight factor "c".

[0082] Equation (1)

[0083] Given two colors A1 and A2, their chromaticity coordinates in the Lab color space are respectively:

[0084] Equation (2)

[0085] Where:

[0086] represents the lightness coordinate value of color A1;

[0087] represents the red / green coordinate value of color A1;

[0088] represents the yellow / blue coordinate value of color A1;

[0089] represents the lightness coordinate value of color A2;

[0090] Red / green coordinate value representing color A2;

[0091] Yellow / blue coordinate value representing color A2;

[0092] l , c is a factor; l represents the lightness weight factor, adjusting the relative broad capacity of lightness; c represents the chroma weight factor, adjusting the relative broad capacity of chroma;

[0093]

[0094]

[0095]

[0096] Equation (3)

[0097] Where:

[0098] represents the lightness difference between color A1 and color A2;

[0099] , both represent the chromaticity difference between color A1 and color A2;

[0100] is the total color difference, represented by the Euclidean distance between the coordinates of two colors (such as color A1, color A2) in three-dimensional space;

[0101] Equation (4)

[0102]

[0103] Equation (5)

[0104]

[0105] Where:

[0106] represents the chroma value of color A1;

[0107] represents the chroma value of color A2;

[0108] represents the chroma difference between color A1 and color A2;

[0109] represents the hue difference between color A1 and color A2.

[0110] In the CIELab color space, the CMC( l :c) formula defines the visual volume around the standard color as an ellipse. The colors inside the ellipse are visually the same as the standard color, while the colors outside the ellipse are different from the standard color. In the entire CIELab color space, the size and eccentricity of the ellipse are different. The characteristics of the ellipse centered on a given standard color are determined by the lengths of the two semi-axes in the , , directions. The color difference formula CMC( l :c) is defined by the ellipse equation as shown in Equation (6) below:

[0111] Equation (6)

[0112] Equation (7)

[0113] Equation (8)

[0114] Equation (9)

[0115] Equation (10)

[0116] Equation (11)

[0117] where S L , S c and S H are the semi-axes of the ellipse, and the ellipse semi-axes correspond to the hue S H , saturation S c , and lightness S L respectively;

[0118] , , are all chromaticity parameters of the standard color sample. Among them, represents the lightness parameter of the standard color sample, represents the chroma parameter of the standard color sample, represents the hue parameter of the standard color sample;

[0119] F and T are correction terms related to the hue angle ( ), used to more accurately reflect the human eye's perception of color differences; among them, F is a correction term related to the hue angle ( ); T is another correction term related to the hue angle ( );

[0120] represents the hue angle difference value;

[0121] represents the red / green coordinate value;

[0122] represents the yellow / blue coordinate value.

[0123] Lightness weight factor l and the chroma weight factor c are used to adjust the influence degree of lightness and chroma on the total color difference. Therefore, in different application scenarios, different ratios should be taken. A large number of experiments show that when evaluating the acceptability of color difference, it is recommended to adopt l : c = 2:1. For example, in the textile printing and dyeing industry, the CMC(2:1) formula is mostly used for product quality control; while when evaluating the perceptibility of color difference, it is recommended to adopt l : c = 1:1. For example, for the chromaticity correction of digital systems, and in industries such as coatings or plastics, the CMC(1:1) formula is generally adopted.

[0124] After calculating and selecting the color difference value, the colors in the basic color model are discretized according to the selected color difference value to generate a series of discrete color data with uniform color differences, and discrete color data is obtained.

[0125] As an example, the calculated color difference value 5 can be selected as the color difference value for discretization processing. The color difference between the position of each color in the space coordinate system of the three-dimensional color model and the position of the adjacent color in the space coordinate system of the basic color model is 5. Therefore, according to the equal-distance principle, the colors in the basic color model are discretized with an equal-distance color difference of 5.

[0126] In some embodiments, step S11110 may specifically include steps S111101 - step S111103:

[0127] Step S111101: Based on using the preset selected color difference value as the edge length of a regular polyhedron, and constructing an array of regular polyhedrons through space tiling to divide the preset basic color model;

[0128] Step S111102: Determine the reference color point data of the basic color model;

[0129] Step S111103: The reference color point data coincides with the vertex or center point of a certain regular polyhedron in the regular polyhedron array, and equidistant color difference discrete point data of the vertices of each regular polyhedron in the basic color model is obtained, and discrete color data is obtained.

[0130] In step S11110, a preset color difference value of 5 is calculated through a color difference calculation formula. Using the color difference value of 5 as the edge length of a regular polyhedron, a regular polyhedron array with an edge length of 5 is reconstructed. This regular polyhedron array can be used to perform data partitioning on the basic color model.

[0131] The reference color point data in the basic color model can be determined by selecting a point that coincides with the vertex or the center point of a certain regular polyhedron in the regular polyhedron array. Since the edge length of the regular polyhedron is a fixed value, the equidistant color discrete point data formed by the vertices of each regular polyhedron in the basic color model can be used as the discrete color data of the preset color.

[0132] In some other embodiments, step S11110 further includes: steps S111104 - S111105:

[0133] Step S111104: Obtain a sequence of color difference values with multiple gradient levels, where any one gradient level corresponds to a color difference value;

[0134] Step S111105: Based on each gradient level in the sequence of color difference values, respectively determine the color difference value as the selected color difference value, and based on each selected color difference value, perform discretization processing on the preset basic color model to obtain the corresponding discrete color data.

[0135] The color difference value can be a non-fixed value. For example, a sequence of color difference values is selected, and each gradient level corresponds to a color difference value. According to each gradient level in each sequence of color difference values, determine the color difference value as the color difference value selected by the user, and then according to step S11110, discretize the colors in the basic color model according to the equidistant principle to generate a series of discrete color data with uniform color differences to obtain the discrete color data.

[0136] Further, it further includes step S111106: Based on the discrete color data corresponding to each selected color difference value, construct a corresponding visual space color gamut model, thereby constructing multiple visual space color gamut models corresponding to the color difference values of multiple gradient levels in the sequence of color difference values. According to the same steps, perform discretization processing on the basic color model respectively for the selected color difference values of each gradient level in the sequence of color difference values, and finally obtain a series of discrete color data with uniform color differences corresponding to the color difference values of multiple gradient levels in the sequence of color differences, thereby constituting multiple visual space color gamut models.

[0137] In some other embodiments, step S11110 may further include step S111107: Discretize the colors in the basic color model according to the equidistant principle in three dimensions: lightness value, red - green degree value, and yellow - blue degree value.

[0138] The basic color model includes three dimensions: lightness value, red-green degree value, and yellow-blue degree value. In this step, the basic color model can be discretized according to the range criteria of lightness value, red-green degree value, and yellow-blue degree value as the equal-distance principle.

[0139] As an implementation, obtain the fourth threshold range of the lightness value to define the brightness range; obtain the fifth threshold range of the red-green degree value to define the red-green degree range; obtain the sixth threshold range of the yellow-blue degree value to define the yellow-blue degree range.

[0140] In this embodiment, as an example, the lightness value range of 0% to 100% is taken as the fourth threshold range to define the brightness range.

[0141] Please refer to Figure 3 As shown, the Lab color model consists of three elements: lightness L and two color channels a and b. Among them, the a channel represents the change range of the color from red to green, and the b channel represents the change range of the color from blue to yellow. The value of the a channel determines the offset degree of the color between red and green. The value of the b channel determines the offset degree of the color between yellow and blue. It can be understood that the change range of the brightness channel in the Lab color model is the range of 0% to 100% in the fourth threshold range of the lightness value described in this embodiment.

[0142] The change range of the a channel value in the Lab color model can be -120 to +120. Among them, +120a represents red, and -120a represents green. The range of -120 to +120 can be defined as the fifth threshold range of the red-green degree value. By adjusting the value of the a channel to control the red or green component, precise adjustment and description of the color can be achieved.

[0143] The change range of the b channel value in the Lab color model can be -120 to +120. Among them, +120 represents yellow, and -120 represents blue. The range of -120 to +120 can be defined as the sixth threshold range of the yellow-blue degree value. By adjusting the value of the b channel to control the yellow or blue component, precise adjustment and description of the color can be achieved.

[0144] In the above embodiment, the discretization processing method based on the equal-distance principle of multi-level data can achieve equal-distance color selection of multiple data levels in the three-dimensional color model, ensuring the consistency and comparability of data representation.

[0145] Please refer to Figure 7 , this application provides a method for visualizing the spatial color gamut model interaction, including step S210 - step S220:

[0146] Step S210: Respond to the user's color gamut model selection operation to determine the first color data;

[0147] Step S220: Display the visual spatial color gamut model corresponding to the first color data on the user interface;

[0148] Among them, the visual spatial color gamut model is constructed by the method of steps S110 - S130, which will not be elaborated here.

[0149] The visual spatial color gamut model can be stored in the memory of the server or the terminal. When the user calls the visual spatial color gamut model, the server or the terminal responds to the instruction of the user's selection operation of the color gamut model and retrieves the color gamut model selected by the user.

[0150] When the user needs to perform color printing through a printing device, first, it is necessary to call the visual spatial color gamut model from the server of the printing device. When the user performs the operation of calling the color gamut model, the visual spatial color gamut model corresponding to the first color data can be displayed on the user interface.

[0151] In some embodiments, steps S210 - S220 may specifically include: steps S230 - S250:

[0152] Step S230: In response to the user's selection operation of the color gamut model, based on a preset sequence of color difference values with multiple gradient levels, where any one of the gradient levels corresponds to a color difference value, determine a color difference value from the sequence of color difference values as the selected color difference value;

[0153] Step S240: Based on the correspondence between the preset color difference value and the preset first color data, determine the first color data corresponding to the selected color difference value;

[0154] Step S250: Display the visual spatial color gamut model constructed corresponding to the first color data on the user interface.

[0155] In order to make the color difference of the color printed by the printing device more obvious, before calling the visual spatial color gamut model, the user can select to perform discrete processing on the basic color model to obtain discrete color data, then convert the discrete color processing into the corresponding first color data in the three - dimensional color model, and finally construct the corresponding visual spatial color gamut model. For details, reference can be made to the description of step S11110 and the descriptions of steps S111104 - S111105.

[0156] As described in steps S110 - S130, the construction of the visual spatial color gamut model is generated based on the position of the first color data in the three - dimensional color model. Therefore, the acquisition of the first color data is the basis.

[0157] In steps S1111 - S1112 and steps S111104 - S111105, according to a sequence of color difference values with multiple gradient levels defined by the user, for each gradient level in each sequence of color difference values, the color difference value is determined as the color difference value selected by the user. Then, in accordance with step S11110, the colors in the basic color model are discretized according to the equal - distance principle to generate a series of discrete color data with uniform color differences, thereby obtaining the discrete color data.

[0158] Based on the conversion relationship between the discrete data and the three - dimensional color model, the discrete color data is converted into the corresponding first color data in the three - dimensional color model. According to the position of the first color data in the three - dimensional color model, a visual color sample representing the first color data is generated. According to the color difference values of different gradient levels, multiple visual color samples representing the first color data can be generated. Based on the color difference value set by the user, the server retrieves the corresponding visual spatial color gamut model and displays it on the monitor.

[0159] In some embodiments, the visual spatial color gamut model interaction method further includes step S260: In response to a user's color sample selection operation on the visual spatial color gamut model, one or more of the visual color samples are determined to be selected as target objects.

[0160] The visual spatial color gamut model includes one or more color gamut models, and the user can independently select one or more color gamut models in the visual spatial color gamut model that they need as the user's target objects for display.

[0161] In some embodiments, step S260 may include steps S261 - S263:

[0162] Step S261: In response to a user's preliminary color sample selection operation on the visual spatial color gamut model, one or more of the visual color samples are determined to be selected as preliminary target objects;

[0163] Step S262: Based on the preliminary target objects, one or more recommended target objects are generated according to a preset recommendation strategy;

[0164] In some embodiments, step S262 may specifically include: Based on the preliminary target objects, according to a preset color space distance threshold, the visual color samples on the visual spatial color gamut model whose color space distance from the preliminary target objects is less than or equal to the specified threshold are determined as the recommended target objects.

[0165] Step S263: In response to a user's final color sample selection operation on the visual spatial color gamut model, one or more of the recommended target objects are determined to be selected as target objects.

[0166] In the above steps, the user operates the server of the printing device to perform the operation of selecting the initial color samples of the visual spatial color gamut model. The server can call one or more initial target objects. The preset recommendation strategy can be based on the user's common login account information, the identity information of the user's operations, the user's preferences, etc. The server automatically calls one or more target objects as the color samples of the visual spatial color gamut model that the user is about to print.

[0167] The user can finally select one or more target objects as the visual spatial color gamut model displayed on the user interface according to the recommendation strategy.

[0168] In some embodiments, it further includes step S270: receiving text input provided by the user; in response to the text input, calling a preset artificial intelligence model to perform semantic analysis on the text input to obtain semantic features associated with the text input; based on the semantic features, determining the visual color sample with the highest degree of association with the semantic features on the visual spatial color gamut model as the target object.

[0169] In this embodiment, as an example, the artificial intelligence model can be ChatGPT. The user can describe the color to be printed in words. ChatGPT can perform semantic analysis on the user's words to obtain semantic features associated with the text input. According to the semantic features, select the visual color sample with the highest degree of association with the semantic features on the visual spatial color gamut model as the target object.

[0170] In some embodiments, it further includes step S280: receiving image input provided by the user; in response to the image input, extracting the main color of the image input; based on the main color, selecting the visual color sample closest to the main color on the visual spatial color gamut model as the target object.

[0171] In this embodiment, the user can input an image of the color to be printed. After the server of the printing device extracts the color image, it can extract the main color of the image. According to the extracted main color, select the visual color sample closest to the main color in the visual spatial color gamut model, and mark this visual color gamut as the user's target object.

[0172] In some embodiments, it includes step S290: in response to the user's operation of selecting color samples of the visual spatial color gamut model, determining that one or more of the visual color samples are highlighted in the visual spatial color gamut model.

[0173] In this embodiment, after the user selects the operation of selecting color samples of the visual spatial color gamut model, the selected color samples of the visual spatial color gamut model can be highlighted. The highlighting can include: the user highlights by selecting a specific color, enlarges or reduces the display, etc.

[0174] In some embodiments, it further includes step S2100: In response to a user's color sample dragging operation on the visual spatial color gamut model, determine the moving distance and moving direction corresponding to the color sample dragging operation, determine the dragged distance of the visual color sample based on the moving distance and moving direction, and control the visual color sample to move the dragged distance in the moving direction.

[0175] In this embodiment, by receiving the input signal of the user operating the mouse to drag, according to the input signal of the user operating the mouse to drag, perform a dragging operation on the color sample in the visual spatial color gamut model, and control the color sample in the visual spatial color gamut model to move the dragged distance in the moving direction according to the distance and moving direction information instructions generated by moving the dragged mouse.

[0176] In some embodiments, it further includes step S2110: In response to a user's rotation operation on the visual spatial color gamut model, rotate the visual spatial color gamut model according to the rotation operation.

[0177] By receiving the input signal of the user operating the mouse to drag and rotate, according to the input signal of the user operating the mouse to drag and rotate, perform a rotation operation on the color sample in the visual spatial color gamut model.

[0178] In some embodiments, it further includes step S2120: In response to a user's perspective operation on the visual spatial color gamut model, adjust the simulated field of view depth of the visual spatial color gamut model according to the perspective operation, so as to display the visual color sample located inside the visual spatial color gamut model on the user interface based on the simulated field of view depth.

[0179] In this embodiment, the perspective operation can be an operation method for presenting a three-dimensional space effect on a two-dimensional plane. Based on the principle of the perspective operation, adjust the simulated field of view depth of the visual spatial color gamut model according to the perspective operation, and display the visual color sample located inside the visual spatial color gamut model on the user interface according to the simulated field of view depth.

[0180] Therefore, the above steps S270, step S280, step S290, step S2100, step S2110, and step S2120 give a variety of color sample interaction methods for the user to implement the visual spatial color gamut model, making the user operation methods more diverse.

[0181] In summary, through precise color mapping and continuous changes, the present application can more effectively display the relationships and trends between color data, enhancing the expressiveness of data visualization. By converting the traditional color model into a three-dimensional display, the optimized utilization of the color space is realized, making color selection and change more intuitive and balanced. Users can more conveniently perform color matching and accurately and quickly find colors, thus transforming complex color theories into simple and understandable visualization tools, making it easier for users to use colors.

[0182] Please refer to Figure 8 , this application provides a device for establishing a visual spatial color gamut model, which is applied to the method for establishing a visual spatial color gamut model, and includes: a establishing module 810, an obtaining module 820, a mapping module 830, and a constructing module 840.

[0183] The establishing module 810 is used to establish a three-dimensional color model; the three-dimensional color model takes the hue circle as a reference plane, establishes a lightness axis perpendicular to the reference plane, represents the position along the lightness axis direction with a lightness value, and represents the radial spatial distance value from the center of the hue circle to any point outward with a chroma value.

[0184] The obtaining module 820 is used to obtain first color data.

[0185] The mapping module 830 is used to map the first color data to the corresponding position in the three-dimensional color model.

[0186] The constructing module 840 is used to generate a visual color sample representing the first color data based on the first color data and the position of the first color data in the three-dimensional color model, and the arrangement of the visual color samples constructs a visual spatial color gamut model.

[0187] For the specific implementation process of the functions and roles of each module in the above device, please refer to the implementation process of the corresponding steps in the above, which will not be elaborated here.

[0188] Please refer to Figure 9 , which is a schematic structural diagram of an electronic device 1 provided by an embodiment of this application. As Figure 9 shown, the electronic device 1 includes: at least one processor 11 and a memory 12, Figure 9 Taking one processor 11 as an example in . The processor 11 and the memory 12 are connected through a bus 10 and complete communication with each other. The memory 12 stores instructions executable by the processor 11. The instructions are executed by the processor 11 so that the electronic device 1 can execute all or part of the processes of the method for establishing a visual spatial color gamut model in the above embodiment, or execute all or part of the processes of the method for visual spatial color gamut interaction in the above embodiment.

[0189] The bus 10 may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front-Side Bus (FSB), a HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an InfiniBand interconnect, a Low Pin Count (LPC) bus, a memory bus, a MicroChannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or a combination of two or more of these. Where appropriate, the bus 10 may include one or more buses.

[0190] The processor 11 implements all or part of the process of the method for establishing a visual spatial color gamut model in the above embodiments, or executes all or part of the process of the above method for visual spatial color gamut model interaction, by reading and executing computer program instructions stored in the memory 12.

[0191] The memory 12 may be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic memory, flash memory, magnetic disks, or optical discs.

[0192] Exemplarily, when executing the method for establishing a visual spatial color gamut model or the method for visual spatial color gamut model interaction, the electronic device 1 may be a server.

[0193] The present application also provides a computer-readable storage medium storing a computer program, which can be executed by a processor to complete the method for establishing a visual spatial color gamut model provided by the present application, or execute to complete the method for visual spatial color gamut model interaction.

[0194] The present application also provides a computer program product including a computer program, which, when executed by a processor, implements the method for establishing a visual spatial color gamut model provided by the present application, or executes to complete the method for visual spatial color gamut model interaction.

[0195] In several embodiments provided by the present application, the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architectures, functions, and operations of devices, methods, and computer program products according to multiple embodiments of the present application. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code, and a module, a program segment, or a part of code contains one or more executable instructions for implementing the specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than marked in the accompanying drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, as well as the combination of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system that performs the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions.

[0196] In addition, in each embodiment of the present application, the functional modules can be integrated together to form an independent part, or each module can exist alone, or two or more modules can be integrated to form an independent part.

[0197] If the function is implemented in the form of a software functional module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods in each embodiment of the present application.

Claims

1. A method for establishing a visualization space color gamut model, characterized in that: The method comprises: Establishing a three-dimensional color model; wherein the three-dimensional color model uses a hue ring as a reference plane, establishes a lightness axis perpendicular to the reference plane, uses lightness values ​​to represent positions along the lightness axis, and uses chroma values ​​to represent radial spatial distance values ​​from the center of the hue ring to any point outward; Acquire first color data, and map the first color data to a corresponding position in the three-dimensional color model; Based on the first color data and the position of the first color data in the three-dimensional color model, a visualized color sample representing the first color data is generated; and a plurality of the visualized color samples are arranged to construct a visualized space color gamut model; Wherein, the obtaining of the first color data comprises the following steps: Acquire discrete color data, wherein the discrete color data is obtained by discretizing a preset basic color model based on a preset data screening strategy; Acquire a conversion relationship between the basic color model and the three-dimensional color model, and convert the discrete color data into corresponding first color data in the three-dimensional color model, wherein the three-dimensional color model is different from the basic color model; The first color data is the color required by the user, and the basic color model refers to the color data represented by the color required to be printed set by the user.

2. The method for establishing a visualization space color gamut model according to claim 1, characterized in that: After the three-dimensional color model is established, the method further comprises the following steps: Obtaining a first threshold range of the hue circle to define a hue range; Obtaining a second threshold range of the brightness value to define a height range; Obtaining a third threshold range of the chroma value to define a radial distance range; The three-dimensional color model is presented as a regular sphere according to the first threshold range, the second threshold range, and the third threshold range.

3. The method for establishing a visualization space color gamut model according to claim 2, characterized in that: The discrete color data is obtained by discretizing a preset basic color model based on a preset data screening strategy, and includes the following steps: The discrete color data is obtained by discretizing the colors in the basic color model according to the equidistance principle based on the preset selected color difference values ​​to generate a series of discrete color data with uniform color difference.

4. The method for establishing a visualization space color gamut model according to claim 3, characterized in that: The discrete color data is obtained by discretizing the colors in the basic color model according to the equidistance principle based on the preset selected color difference value to generate a series of discrete color data with uniform color difference, including the following steps: Based on using the preset selected color difference value as the side length of the regular polyhedron, a regular polyhedron array is constructed by a spatial tessellation method to divide the preset basic color model; Determining reference color point data of the basic color model; The reference color point data coincides with a vertex or a center point of a regular polyhedron in the regular polyhedron array, and the equidistant color difference discrete point data of each vertex of the regular polyhedron in the basic color model are obtained to obtain the discrete color data.

5. The method for establishing a visualization space color gamut model according to claim 3, characterized in that: The discrete color data is based on using a preset selected color difference value to discretize the colors in the basic color model according to the equidistance principle to generate a series of discrete color data with uniform color difference to obtain the discrete color data, and also includes the following steps: Obtaining a color difference value sequence having a plurality of gradient levels, wherein any of the gradient levels corresponds to a color difference value; Based on each of the gradient levels in the color difference value series, the color difference values ​​are respectively determined as selected color difference values, and based on each of the selected color difference values, corresponding discrete color data are obtained by discretizing a preset basic color model.

6. The method for establishing a visualization space color gamut model according to claim 5, characterized in that: The following steps are also included: Based on the discrete color data corresponding to each selected color difference value, a corresponding visualization space color gamut model is constructed, thereby constructing multiple visualization space color gamut models corresponding to multiple gradient level color difference values ​​in the color difference value series.

7. The method for establishing a visualization space color gamut model according to claim 3, characterized in that: The discretization of the colors in the basic color model according to the equidistant principle includes the following steps: the basic color model includes three dimensions: lightness value, redness-greenness value, and yellowness-blueness value; the colors in the basic color model are discretized according to the equidistant principle of the three dimensions: lightness value, redness-greenness value, and yellowness-blueness value.

8. The method for establishing a visualization space color gamut model according to claim 7, characterized in that: The basic color model includes three dimensions: lightness value, red-green value, and yellow-blue value, among which: Obtaining a fourth threshold range of the brightness value to define a brightness range; Obtaining a fifth threshold range of the redness and greenness values ​​to define a redness and greenness range; A sixth threshold range of the yellow-blue value is obtained to define a yellow-blue range.

9. A visual space color gamut model interaction method, characterized in that: The method comprises the following steps: In response to the user's color gamut model selection operation, determining first color data; and displaying the visualized space color gamut model corresponding to the first color data on the user interface; Wherein, the visualization space color gamut model is constructed according to the method described in any one of claims 1 to 8: establishing a three-dimensional color model; wherein, the three-dimensional color model takes the hue ring as a reference plane, establishes a lightness axis perpendicular to the reference plane, uses lightness values ​​to represent the position along the lightness axis, and uses chroma values ​​to represent the radial spatial distance value from the center of the hue ring to any point outward; obtains first color data, and maps the first color data to a corresponding position in the three-dimensional color model; based on the first color data and the position of the first color data in the three-dimensional color model, generates a visualization color sample representing the first color data, and arranges several of the visualization color samples to construct a visualization space color gamut model.

10. The visualization space color gamut model interaction method according to claim 9, characterized in that: The method of determining first color data in response to a color gamut model selection operation by a user; and displaying a visualized space color gamut model corresponding to the first color data on a user interface comprises the following steps: In response to a color gamut model selection operation by a user, based on a preset color difference value sequence having a plurality of gradient levels, wherein any of the gradient levels corresponds to a color difference value, determining a color difference value from the color difference value sequence as a selected color difference value; Determining the first color data corresponding to the selected color difference value based on the corresponding relationship between the preset color difference value and the preset first color data; The visualized space color gamut model constructed corresponding to the first color data is displayed on the user interface.

11. The visualization space color gamut model interaction method according to claim 9, characterized in that: The method further comprises the steps of: In response to a color sample selection operation by a user for the visualization space color gamut model, it is determined that one or more of the visualization color samples are selected as target objects.

12. The visualization space color gamut model interaction method according to claim 11, wherein in response to the user's selection operation of the visualization space color gamut model color sample, determining that one or more of the visualization color samples are selected as the target object, is characterized in that: The following steps are also included: In response to a user's preliminary color sample selection operation for the visualization space color gamut model, determining that one or more of the visualization color samples are selected as preliminary target objects; Based on the preliminary target object, generating one or more recommended target objects according to a preset recommendation strategy; In response to the user's final color sample selection operation for the visualization space color gamut model, one or more of the recommended target objects are determined to be selected as target objects from the recommended target objects.

13. The visualization space color gamut model interaction method according to claim 12, characterized in that: The method of generating one or more recommended target objects based on the preliminary target object according to a preset recommendation strategy also includes the following steps: Based on the preliminary target object, according to a preset color space distance threshold, a visualization color sample whose color space distance from the preliminary target object is less than or equal to a specified threshold is determined on the visualization space color gamut model as a recommended target object.

14. The visualization space color gamut model interaction method according to claim 11, characterized in that: The method of determining that one or more of the visualized color samples are selected as target objects in response to the user's color sample selection operation for the visualized space color gamut model is characterized by further comprising the following steps: Receiving text input provided by the user; in response to the text input, calling a preset artificial intelligence model to perform semantic analysis on the text input to obtain semantic features associated with the text input; Based on the semantic feature, the visualized color sample with the highest correlation with the semantic feature is determined as a target object on the visualized space color gamut model.

15. The interactive method of the visualization space color gamut model according to claim 11, wherein in response to the user's selection operation of the visualization space color gamut model color sample, determining that one or more of the visualization color samples are selected as the target object, is characterized in that: The following steps are also included: Receiving an image input provided by the user; extracting a main color of the image input in response to the image input; Based on the main color, the visualized color sample closest to the main color is determined as a target object on the visualized space color gamut model.

16. The visualization space color gamut model interaction method according to claim 11, characterized in that: The following steps are also included: In response to a color sample selection operation by a user for the visualization space color gamut model, one or more of the visualization color samples are determined to be highlighted in the visualization space color gamut model.

17. The visualization space color gamut model interaction method according to claim 9, characterized in that: The following steps are also included: In response to a user's color sample dragging operation on the visualization space color gamut model, a moving distance and a moving direction corresponding to the color sample dragging operation are determined, a dragged distance of the visualization color sample is determined based on the moving distance and the moving direction, and the visualization color sample is controlled to move the dragged distance in the moving direction.

18. The visualization space color gamut model interaction method according to claim 9, characterized in that: The following steps are also included: In response to a user's rotation operation on the visualization space color gamut model, the visualization space color gamut model is rotated according to the rotation operation.

19. The visualization space color gamut model interaction method according to claim 9, characterized in that: The following steps are also included: In response to a user's perspective operation on the visualization space color gamut model, a simulated field of view depth of the visualization space color gamut model is adjusted according to the perspective operation to display a visualization color sample located inside the visualization space color gamut model on a user interface based on the simulated field of view depth.

20. A visualization space color gamut model building device, applied to the visualization space color gamut model building method according to any one of claims 1 to 8, characterized in that: include: An establishment module is used to establish a three-dimensional color model; the three-dimensional color model uses the hue ring as a reference plane, establishes a lightness axis perpendicular to the reference plane, uses lightness values ​​to represent the position along the lightness axis, and uses chroma values ​​to represent the radial spatial distance value from the center of the hue ring to any point outward; An acquisition module, used for acquiring first color data; A mapping module, used for mapping the first color data to a corresponding position in the three-dimensional color model; A construction module is used to generate a visual color sample representing the first color data based on the first color data and the position of the first color data in the three-dimensional color model, and the visual color samples are arranged to construct a visual space color gamut model.

21. An electronic device, characterized in that: The electronic device comprises: processor; a memory for storing processor-executable instructions; The processor is configured to execute the visualization space color gamut model establishment method described in any one of claims 1 to 8, or to execute the visualization space color gamut model interaction method described in any one of claims 9 to 19.

22. A computer program product, characterized in that The computer program product includes a computer program, and when the computer program is executed by a processor, it implements the method for establishing a visualization space color gamut model described in any one of claims 1 to 8, or executes the method for interacting with a visualization space color gamut model described in any one of claims 9 to 19.

23. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by the processor, it is used to execute the visualization space color gamut model establishment method described in any one of claims 1 to 8, or execute the visualization space color gamut model interaction method described in any one of claims 9 to 19.

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