Backlight brightness adjustment method, device, equipment and medium

Abstract

The application discloses a backlight brightness adjusting method, device, equipment and medium, the backlight brightness adjusting method comprises: acquiring a to-be-displayed image, and segmenting the to-be-displayed image to obtain M*N backlight regions; an edge is established according to the pixel brightness of the backlight region, a graph network structure G=(V, E) is established by taking one backlight region as one node, wherein V represents a node set, and E represents an edge set; the centrality index of the node in the graph network structure G is calculated; the brightness of the backlight region is selected according to the centrality index of the node, and the final backlight value of each backlight region is obtained; the final backlight values of all the backlight regions are combined to form a backlight graph, a liquid crystal compensation image is generated according to the backlight graph, and the brightness of the backlight graph and the liquid crystal compensation image is adjusted. The application relies on image structure information, realizes accurate backlight value acquisition and image compensation reconstruction through complex network modeling and graph theory analysis.

Description

Technical Field

[0001] This invention relates to the field of liquid crystal display technology, and more specifically to a method, apparatus, device, and medium for adjusting backlight brightness. Background Technology

[0002] Liquid crystal displays (LCDs) are characterized by their ultra-long lifespan, energy efficiency, low operating voltage, high color rendering index, low operating temperature, fast response speed, and environmental friendliness. Therefore, LCDs are widely used in various electronic devices (such as LCD TVs or computers). However, the screen of an LCD is a passive light-emitting device and cannot emit light itself; therefore, a backlight must be provided to illuminate the entire screen from its rear surface.

[0003] With the increasing emphasis on high dynamic range display and energy-saving control, local dimming technology has become a key means for improving contrast and energy efficiency in LCD devices. Contrast ratio and energy saving rate are important indicators for evaluating image display quality. Currently, local dimming technology typically employs statistical methods (such as maximum value-based local dimming) and feature-based methods (such as CDF (Cumulative Probability Distribution Function) threshold-based local dimming). While statistical methods are relatively simple to implement, they ignore the spatial distribution of brightness, treating all pixels equally. This makes them suitable only for simple scene displays, and in complex scenes, they can easily lead to detail blurring, affecting the overall image display quality. CDF threshold-based local dimming offers better energy saving rates, but it only focuses on the brightness distribution ratio when processing images, resulting in compression of the brightness of key content and some degree of image distortion, thus affecting image display quality. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a method, apparatus, device and medium for adjusting backlight brightness in order to enhance the image display quality.

[0005] Firstly, a backlight brightness adjustment method is provided, including:

[0006] Obtain the image to be displayed and segment it to obtain M×N backlight areas;

[0007] Edges are established based on the pixel brightness of the backlight area, and a graph network structure G = (V, E) is established with a backlight area as a node, where V represents the set of nodes and E represents the set of edges.

[0008] Computing the centrality index of nodes in a graph network structure G;

[0009] The brightness of the backlight area is selected based on the centrality index of the node to obtain the final backlight value of each backlight area.

[0010] The final backlight values ​​of all backlight areas are combined to form a backlight map, and a liquid crystal compensation image is generated based on the backlight map. The brightness of the backlight map and the liquid crystal compensation image are then adjusted.

[0011] Secondly, a backlight brightness adjustment device is provided, comprising:

[0012] The segmentation module is used to acquire the image to be displayed and segment it to obtain M×N backlight areas;

[0013] The network construction module is used to build edges based on the pixel brightness of the backlight area, and to build a graph network structure G = (V, E) with a backlight area as a node, where V represents the set of nodes and E represents the set of edges;

[0014] The computation module is used to calculate the centrality index of nodes in a graph network structure G;

[0015] The backlight value processing module is used to select the brightness of the backlight area according to the centrality index of the node, so as to obtain the final backlight value of each backlight area.

[0016] The adjustment module is used to assemble the final backlight values ​​of all backlight areas into a backlight map, generate a liquid crystal compensation image based on the backlight map, and drive the backlight map and the liquid crystal compensation image to adjust the brightness.

[0017] Thirdly, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the aforementioned backlight brightness adjustment method.

[0018] Fourthly, a computer-readable storage medium is provided, which stores a computer program that, when executed by a processor, implements the steps of the aforementioned backlight brightness adjustment method.

[0019] Compared with existing technologies, this invention establishes edges based on the pixel brightness of the backlight area, constructs a graph network structure with each backlight area as a node, and selects and adjusts the brightness of the backlight area according to the centrality index of the nodes in the graph network structure G to obtain the final backlight value of the backlight area. Then, the final backlight values ​​of all backlight areas are combined to form a backlight map, and a liquid crystal compensation image is generated based on the backlight map. The backlight map and the liquid crystal compensation image are driven to adjust brightness. It can be seen that this invention comprehensively considers the structural correlation between the backlight areas of the image, constructs the pixel brightness similarity relationship between regions, introduces a graph network structure, and naturally captures the spatial relationship of brightness distribution through the graph network structure. It is suitable for complex scenes with non-uniform brightness. By using the centrality index to select and adjust the brightness of the backlight area, key brightness information is extracted from the perspective of spatial correlation to guide backlight allocation. That is, the centrality index emphasizes key areas and suppresses secondary areas, thereby fully reflecting the dominant brightness within the backlight area, optimizing backlight allocation, achieving a high-contrast and energy-saving display effect, and improving dimming accuracy and image display quality. Attached Figure Description

[0020] Figure 1 This is a schematic flowchart of a backlight brightness adjustment method in one embodiment of the present invention;

[0021] Figure 2 for Figure 1 A schematic diagram of a specific implementation method for step S20;

[0022] Figure 3 This is a schematic diagram of the display image simulated using the backlight brightness adjustment method provided in the embodiments of the present invention and the area dimming method based on maximum value and CDF.

[0023] Figure 4 This is a schematic diagram of the backlight brightness adjustment method provided in the embodiments of the present invention and the backlight image obtained by simulation using the regional dimming method based on maximum value and CDF.

[0024] Figure 5 This is a schematic diagram of a backlight brightness adjustment device in one embodiment of the present invention;

[0025] Figure 6 This is a schematic diagram of the structure of a computer device according to an embodiment of the present invention. Detailed Implementation

[0026] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0027] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0028] It should also be understood that the term “and / or” as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0029] Please see Figure 1 , Figure 1 This is a schematic flowchart illustrating a backlight brightness adjustment method provided in an embodiment of the present invention. In the embodiment shown in the figures, the backlight brightness adjustment method includes the following steps S10-50:

[0030] S10. Obtain the image to be displayed and segment it to obtain M×N backlight areas.

[0031] In this embodiment, the image to be displayed can be evenly divided into several non-overlapping backlight areas. The image to be displayed can be an RGB image or a grayscale image. If the size is H×W, then the size of each backlight area is (H / M)×(W / N).

[0032] S20. Establish edges based on the pixel brightness of the backlight area, and establish a graph network structure G = (V, E) with a backlight area as a node.

[0033] In this step, each backlight area is treated as a node, and edges are constructed based on the pixel brightness relationship between the backlight areas, thereby introducing a graph network structure to form a weighted undirected graph.

[0034] Specifically, such as Figure 2 As shown, step S20, which establishes the edge based on the pixel brightness of the backlight area, may specifically include steps S21-S22:

[0035] S21. Based on the pixel brightness of each backlight area, use the formula... Calculate the average pixel brightness of the backlit area.

[0036] In this step, Y k The value Y represents the pixel brightness of the k-th pixel, and n represents the total number of pixels in the backlight area. The pixel brightness Y of the backlight area can be calculated using the formula Y = 0.299R + 0.587G + 0.114B, where R, G, and B are the values ​​of the red, green, and blue channels, respectively, and their values ​​are usually in the range of 0-255.

[0037] S22. Establish an edge based on the average pixel brightness of any two backlight regions.

[0038] In this step, specifically, for any two backlight regions, if the absolute value of the deviation of the average pixel brightness of the two backlight regions is less than the preset threshold T, an edge is established. That is, for any two regions v i and v j , if |L i -L j |<T, an edge e ij is established, where L i and L j are the average pixel brightnesses of regions v i and v j respectively.

[0039] S30. Calculate the centrality index of the nodes in the graph network structure G.

[0040] In the present invention, the representative brightness in the selected backlight region is adjusted through the centrality index of the nodes in the graph network structure. That is, the key regions are adaptively emphasized and the secondary regions are suppressed through the centrality index, and the key brightness information is extracted from the perspective of spatial association to guide the optimization of backlight allocation.

[0041] In this step, the centrality index of the nodes may include eigenvector centrality and / or betweenness centrality, etc.

[0042] In this embodiment, the centrality index includes eigenvector centrality. Then, according to the formula calculate the eigenvector centrality value C e of node V e (V e ) in the graph network structure G; where A represents the adjacency matrix, and A ij represents the element of the adjacency matrix, indicating whether there is an edge between node i and node j. If there is an edge, then A ij =1; if there is no edge, then A ij =0, and λ represents the largest eigenvalue. In this embodiment, the importance of the node in the graph network structure is quantified through the eigenvector centrality value to fully reflect the dominant brightness inside the region.

[0043] In some other embodiments, the centrality index includes betweenness centrality. Then, according to the formula calculate the betweenness centrality value of the nodes in the graph network structure G; where σ st represents the number of shortest paths from node s to t, and σ st(v) represents the number of paths from node s to t that pass through node v. In this embodiment, all pairs of nodes in the graph network structure that satisfy s≠v≠t and s≠t (i.e., excluding v itself as a start or end point) are traversed, and the number of shortest paths from node s to t (the number of paths with the smallest length) σ is calculated. st (v), and calculate the number of paths passing through node v in the shortest path from node s to t, thereby obtaining the betweenness centrality value of node v, which can enhance the edge structure, that is, strengthen the importance of the light and dark boundary region. The betweenness centrality value quantifies the keyness of the node in the graph network structure, and can also fully reflect the dominant brightness inside the region.

[0044] S40. Select the brightness of the backlight area according to the centrality index of the node to obtain the final backlight value of each backlight area.

[0045] In this invention, a centrality-driven backlight representativeness adjustment selection mechanism is used to adjust and select the brightness value that best represents the visual importance of the backlight area, so as to determine the most representative final backlight value for backlight adjustment for each backlight area.

[0046] Specifically, this step includes: weighting the pixel brightness of the backlight area according to the centrality index of the node to obtain the final backlight value of each backlight area. Preferably, in this embodiment, the average / maximum pixel brightness of the backlight area can be weighted according to the centrality index of the node, adaptively emphasizing key backlight areas and suppressing secondary backlight areas. The weighted allocation reflects the dominant brightness and optimizes the backlight distribution. That is, the brightness characteristics of the backlight area are adjusted according to the centrality index of the node. By emphasizing the influence of the global key area through the centrality index, the problem of over-brightness or under-brightness caused by simply using the maximum value for dimming can be avoided. Moreover, the centrality weighted adjustment method can also make each backlight area transition smoothly in a manner that conforms to the optical diffusion characteristics when the image is displayed.

[0047] S50. The final backlight values ​​of all backlight areas are combined to form a backlight map, and a liquid crystal compensation image is generated based on the backlight map. The brightness of the backlight map and the liquid crystal compensation image is then adjusted.

[0048] In this step, the final backlight values ​​of all backlight areas form a backlight image B with a size of M×N. A liquid crystal compensation image is generated based on the backlight image, which in turn drives the backlight image and the liquid crystal compensation image to perform regional backlight adjustment.

[0049] Specifically, generating a liquid crystal compensation image based on the backlight image can be achieved by: expanding the backlight image to the same size as the image to be displayed using a diffusion function to obtain a backlight diffusion image, that is, expanding it to the same size as the image to be displayed using a diffusion function K(x,y) convolution to obtain a backlight diffusion image B. full(x,y)=B(x,y)*K(x,y), where x and y represent the number of rows and columns of pixels, respectively; then, based on the backlight diffusion image, the formula is used... Calculate the liquid crystal compensation image L(x,y); where ∈ is a small constant to avoid division by zero, and I(x,y) is the brightness value of the image to be displayed.

[0050] Understandably, the backlight adjustment method of the present invention can be applied to different diffusion functions when generating liquid crystal compensated images, so as to be suitable for images of different sizes, content types and display requirements.

[0051] To verify the performance of the backlight adjustment method proposed in this invention, simulations were performed using a subset of test images from the LOL dataset to compare the backlight adjustment method of the above embodiments (with eigenvector centrality as the centrality metric) with the area dimming method based on maximum value / CDF. Figure 3 As shown, Figure 3 The presentation shows four original images selected for testing and the displayed images output after dimming using various methods. The backlight images obtained using each dimming method are shown below. Figure 4 As shown in Table 1 below, the specific simulation test results are as follows:

[0052]

[0053] As shown in the table, the backlight brightness adjustment method of the present invention can take into account PSNR, SSIM and energy saving rate. It has high contrast and high energy saving rate. The overall image display quality is better than the local dimming method based on maximum value / CDF.

[0054] As can be seen from the above scheme, the backlight brightness adjustment method of the present invention adopts a structure-guided brightness estimation method, which quantifies and represents the spatial structure information between pixels or regions in the image. That is, it comprehensively considers the structural correlation between the backlight regions of the image, constructs a graph network structure that can naturally capture the spatial relationship of brightness distribution based on the similarity of pixel brightness, and then, based on the image structure information, adjusts and selects the most representative backlight value from the perspective of spatial correlation through the centrality index. When adjusting the backlight, the key areas are emphasized and the secondary areas are suppressed according to the centrality index to improve the dimming accuracy and image quality, and can achieve a high contrast and energy-saving display effect.

[0055] It should be noted that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0056] Reference Figure 5 , Figure 5This is a schematic diagram of a backlight brightness adjustment device according to an embodiment of the present invention. In the embodiment shown in the figure, the backlight brightness adjustment device includes an acquisition and segmentation module 101, a network construction module 102, a calculation module 103, a backlight value processing module 104, and an adjustment module 105. Detailed descriptions of each functional module are as follows:

[0057] The segmentation module 101 is used to acquire the image to be displayed and segment the image to be displayed to obtain M×N backlight areas;

[0058] Network construction module 102 is used to establish edges based on the pixel brightness of the backlight area, and to establish a graph network structure G = (V, E) with a backlight area as a node, where V represents the set of nodes and E represents the set of edges;

[0059] Calculation module 103 is used to calculate the centrality index of nodes in the graph network structure G;

[0060] The backlight value processing module 104 is used to select the brightness of the backlight area according to the centrality index of the node, and obtain the final backlight value of each backlight area.

[0061] The adjustment module 105 is used to compose a backlight map from the final backlight values ​​of all backlight areas, generate a liquid crystal compensation image based on the backlight map, and drive the backlight map and the liquid crystal compensation image to adjust the brightness.

[0062] In some embodiments, the calculation module 103 is specifically used for:

[0063] According to the formula In the computational graph network structure G, node V e The eigenvector centrality values; where A represents the adjacency matrix and λ represents the largest eigenvalue.

[0064] In some embodiments, the calculation module 103 is further specifically used for:

[0065] According to the formula Compute the betweenness centrality of nodes in a graph network structure G; where σ st σ represents the number of shortest paths from node s to t. st (v) represents the number of paths that pass through node v in the shortest path from node s to t.

[0066] In some embodiments, the network construction module 102 is specifically used for:

[0067] Based on the pixel brightness of each backlight area, the formula is used. Calculate the average pixel brightness of the backlight area; where Y k This represents the pixel brightness of the k-th pixel, and n represents the total number of pixels in the backlight area;

[0068] Edges are constructed based on the average pixel brightness of any two backlit regions.

[0069] In some embodiments, the network construction module 102 is specifically used for:

[0070] For any two backlight areas, if the absolute value of the deviation between the average pixel brightness of the two backlight areas is less than a preset threshold, then an edge is established.

[0071] In some embodiments, the backlight value processing module 104 is specifically used for:

[0072] The pixel brightness of the backlight area is weighted and adjusted according to the centrality index of the node to obtain the final backlight value of each backlight area.

[0073] In some embodiments, the adjustment module 105 is specifically used for:

[0074] The backlight image is expanded to the same size as the image to be displayed using a diffusion function to obtain a backlight diffusion image;

[0075] Based on the backlight diffusion image, using the formula Calculate the liquid crystal compensation image L(x,y); where ∈ represents a small constant, and I(x,y) is the brightness value of the image to be displayed.

[0076] This invention provides a backlight brightness adjustment device that can abstract backlight diffusion as a graph network structure propagation. It measures the importance of the backlight area in the global brightness structure through centrality index and quantifies the visual importance of the area. That is, based on image structure information, it achieves accurate backlight value acquisition and image compensation reconstruction through complex network modeling and graph theory analysis, so as to achieve a high contrast and energy-saving display effect, improve dimming accuracy and image display quality.

[0077] For specific limitations regarding the backlight brightness adjustment device, please refer to the limitations on the backlight brightness adjustment method above, which will not be repeated here. Each module in the aforementioned backlight brightness adjustment device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of the computer device in hardware form or independently of it, or stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0078] In one embodiment, a computer device is provided, the internal structure of which can be shown as follows: Figure 6As shown, the computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile and / or volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface is used to communicate with external devices via a network connection. Furthermore, the computer device may also include a display screen and input devices (e.g., mouse, keyboard, etc.) for interactive purposes.

[0079] Specifically, when the processor in the computer device executes the computer program, it implements each step of the backlight brightness adjustment method provided in the above embodiments.

[0080] In one embodiment, the present invention may also provide a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the various steps of the backlight brightness adjustment method provided in the above embodiments.

[0081] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0082] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0083] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for adjusting backlight brightness, characterized in that, The backlight brightness adjustment method includes: Obtain the image to be displayed and segment it to obtain M×N backlight areas; Edges are established based on the pixel brightness of the backlight area, and a graph network structure is built with each backlight area as a node. Where V represents the set of nodes and E represents the set of edges; Computing the centrality index of nodes in a graph network structure G; The brightness of the backlight area is selected based on the centrality index of the node to obtain the final backlight value of each backlight area. The final backlight values ​​of all backlight areas are combined to form a backlight map, and a liquid crystal compensation image is generated based on the backlight map. The brightness of the backlight map and the liquid crystal compensation image are then adjusted. Specifically, establishing edges based on pixel brightness in the backlight area includes: Based on the pixel brightness of each backlight area, the formula is used. Calculate the average pixel brightness of the backlight area; where, This represents the pixel brightness of the k-th pixel, and n represents the total number of pixels in the backlight area; For any two backlight areas, if the absolute value of the deviation between the average pixel brightness of the two backlight areas is less than a preset threshold, then an edge is established.

2. The backlight brightness adjustment method as described in claim 1, characterized in that, The centrality indices of nodes in the computational graph network structure G specifically include: According to the formula Nodes in a computational graph network structure G The eigenvector centrality values; where A represents the adjacency matrix, This represents the connection relationship between node i and node j in the adjacency matrix. Let j represent the largest eigenvalue, j represent the neighboring nodes of node i, and N(i) represent the set of neighboring nodes of node i. Represents a node The eigenvector centrality value.

3. The backlight brightness adjustment method as described in claim 1, characterized in that, The centrality indices of nodes in the computational graph network structure G specifically include: According to the formula Calculate the betweenness centrality value of node v in a graph network structure G; where s and t represent any two distinct nodes in the graph network structure G other than node v. Represents a node arrive The number of shortest paths, Represents a node arrive The shortest path passes through the nodes The number of paths.

4. The backlight brightness adjustment method as described in claim 1, characterized in that, The step of selecting the brightness of the backlight area based on the centrality index of the node to obtain the final backlight value of each backlight area specifically includes: The pixel brightness of the backlight area is weighted and adjusted according to the centrality index of the node to obtain the final backlight value of each backlight area.

5. The backlight brightness adjustment method as described in claim 1, characterized in that, The step of generating a liquid crystal compensation image based on the backlight image specifically includes: The backlight image is expanded to the same size as the image to be displayed using a diffusion function to obtain a backlight diffusion image; Based on the backlight diffusion image, using the formula Calculate the liquid crystal compensation image Where x and y represent the number of rows and columns of pixels, respectively. Represents a small constant. The brightness value of the image to be displayed. This represents the backlight diffusion image at coordinates (x, y).

6. A backlight brightness adjustment device, characterized in that, include: The segmentation module is used to acquire the image to be displayed and segment it to obtain M×N backlight areas; The network building module is used to calculate the pixel brightness of each backlight area using a formula. Calculate the average pixel brightness of the backlight area; where, Let represent the pixel brightness of the k-th pixel, and n represent the total number of pixels in the backlit region. For any two backlit regions, if the absolute value of the deviation between the average pixel brightness of the two backlit regions is less than a preset threshold, then an edge is established, and a graph network structure is built with each backlit region as a node. Where V represents the set of nodes and E represents the set of edges; The computation module is used to calculate the centrality index of nodes in a graph network structure G; The backlight value processing module is used to select the brightness of the backlight area according to the centrality index of the node, so as to obtain the final backlight value of each backlight area. The adjustment module is used to assemble the final backlight values ​​of all backlight areas into a backlight map, generate a liquid crystal compensation image based on the backlight map, and drive the backlight map and the liquid crystal compensation image to adjust the brightness.

7. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the backlight brightness adjustment method as described in any one of claims 1 to 5.

8. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the backlight brightness adjustment method as described in any one of claims 1 to 5.

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