Picture light control method and device, electronic equipment and storage medium

Abstract

The invention relates to a picture light control method and device, electronic equipment and a storage medium. The method comprises the steps that picture gray information of an input picture is acquired; determining a picture scene of the input picture based on the picture gray scale information; judging whether the input picture has a picture light leakage risk in the picture scene or not according to the picture gray scale information; under the condition that the input picture has the picture light leakage risk in the picture scene, the light leakage level of the input picture is obtained; and calling a backlight regulation and control strategy corresponding to the light leakage level in the picture scene, and adjusting backlight parameters of the input picture based on the backlight regulation and control strategy. Scenarized processing of the picture light leakage problem is achieved, and differentiated light leakage detection logic can be adopted for different picture scenes; meanwhile, by quantifying the light leakage level and calling the corresponding backlight regulation and control strategy, the backlight parameters can be adjusted in a targeted mode, the halo phenomenon is effectively restrained, the contrast ratio of image display and dark scene performance are improved, and the visual experience of a user is improved.

Description

Technical Field

[0001] This application relates to the field of image processing technology, and in particular to an image light control method, apparatus, electronic device and storage medium. Background Technology

[0002] LCD display products often employ global backlight control technology, where the backlight is fully illuminated when the TV is turned on, regardless of the screen content. This lack of backlight adjustment results in poor contrast, difficulty in rendering dark scenes, and higher power consumption. Local dimming (LD) technology allows for zoned backlight control, adjusting brightness or contrast in real-time based on the current frame, thereby reducing overall power consumption and improving contrast. While LD divides the screen into zones based on the number of backlight zones, the inability to precisely control the backlight diffusion range, coupled with the complex composition of these areas containing multiple grayscale information, can lead to noticeable halo effects.

[0003] However, existing solutions use intelligent calculation of the input image signal to determine the brightness value that each backlight zone should output in order to suppress halos and ensure the overall brightness and contrast of the image, but they still cannot intelligently eliminate the further perception of halos by the human eye.

[0004] Therefore, there is an urgent need to develop a method, device, electronic device, and storage medium for controlling screen light to solve one or more of the aforementioned problems. Summary of the Invention

[0005] In view of this, in order to solve the above-mentioned technical problems or some of the technical problems, the embodiments of this application provide a screen light control method, device, electronic device and storage medium. The method can accurately identify the screen scene and light leakage according to the grayscale information of the input screen, and adaptively match the backlight control strategy according to the light leakage level, effectively suppressing the halo phenomenon, improving the screen display contrast while reducing power consumption.

[0006] In a first aspect, this application provides a method for controlling screen light, the method comprising: Obtain the grayscale information of the input screen; Based on the grayscale information of the image, the scene of the input image is determined; Based on the grayscale information of the image, determine whether the input image has a risk of light leakage in the scene. If there is a risk of light leakage in the input screen under the scene, obtain the light leakage level of the input screen; The backlight control strategy corresponding to the light leakage level in the scene is retrieved, and the backlight parameters of the input scene are adjusted based on the backlight control strategy.

[0007] In one possible implementation, acquiring the grayscale information of the input screen includes... Obtain the grayscale value information histogram of the input image, and analyze the grayscale value information histogram frame by frame to obtain the grayscale value of each frame of the input image; The global average image level of the input image is determined based on the grayscale value of each frame of the input image. According to the preset hardware partitioning rules, the input screen is divided into grids in the horizontal and vertical directions to obtain a preset number of screen partitions. Based on the grayscale value of each frame of the input image, grayscale value analysis is performed on each frame partition of the input image to determine the average and maximum grayscale values ​​of each frame partition. The global average image level of the input image, as well as the average and maximum grayscale values ​​of each image partition of the input image, are determined as the image grayscale information of the input image.

[0008] In one possible implementation, determining the scene of the input screen based on the screen grayscale information includes: Retrieve the preset backlight specification threshold; The global average image level, which is included in the grayscale information of the image, is compared with the backlight specification threshold to obtain the relationship between the global average image level and the backlight specification threshold. If the global average image level is greater than the backlight specification threshold, the scene of the input image is determined to be the first scene; If the global average image level is less than or equal to the backlight specification threshold, the scene of the input image is determined to be the second scene.

[0009] In one possible implementation, when the scene is a first scene, determining whether the input image has a risk of light leakage in the scene based on the image grayscale information includes: Based on the grayscale information of the image, all image partitions of the input image are traversed to determine the number of pixels with zero grayscale value in each image partition. Determine whether there is an abnormal partition in the input screen, wherein the proportion of the number of zero grayscale pixels in the abnormal partition to the total number of pixels is greater than a preset zero grayscale proportion threshold. If there are abnormal partitions in the input screen, obtain the average grayscale value and the maximum grayscale value of the abnormal partitions; Determine whether the maximum grayscale value of the abnormal partition is greater than the average grayscale value by a preset multiple; If the maximum grayscale value is greater than the average grayscale value by a preset multiple, it is determined that the input screen has a risk of light leakage in the first scene.

[0010] In one possible implementation, when the scene is a second scene, determining whether the input image has a risk of light leakage in the scene based on the image grayscale information includes: Based on the grayscale information of the image, it is determined whether there is a completely black partition in the input image, wherein the average grayscale value and the maximum grayscale value of the completely black partition are both zero; If there is a completely black section in the input screen, determine whether the input screen is a completely black screen or a partially black screen; If the input screen is a completely black screen or a partially black screen, it is determined that the input screen has a risk of light leakage in the second scene.

[0011] In one possible implementation, when the scene is a first scene, obtaining the light leakage level of the input scene includes: Obtain the maximum and average grayscale values ​​of each abnormal partition in the input screen; For each of the abnormal partitions, the ratio of the maximum grayscale value to the average grayscale value is calculated to obtain the light leakage quantization value of each abnormal partition; The light leakage level of the input screen is determined based on the light leakage quantization value of all the abnormal partitions.

[0012] In one possible implementation, when the scene is a second scene, obtaining the light leakage level of the input scene includes: The normalized light leakage quantization value of the input image is obtained by calculating the ratio of the global average image level of the input image to the maximum standard gray level. The light leakage level of the input image is determined based on the normalized light leakage quantization value.

[0013] Secondly, this application provides a screen light control device, the device comprising: The information acquisition module is used to acquire the grayscale information of the input screen; The determining module is used to determine the scene of the input screen based on the grayscale information of the screen. The judgment module is used to determine whether there is a risk of light leakage in the input image under the scene based on the image grayscale information; The level acquisition module is used to acquire the light leakage level of the input screen when there is a risk of light leakage in the screen scene. The adjustment module is used to retrieve the backlight control strategy corresponding to the light leakage level in the scene and adjust the backlight parameters of the input scene based on the backlight control strategy.

[0014] Thirdly, this application provides an electronic device, 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 screen light control method described in any embodiment of the first aspect.

[0015] Fourthly, this application also provides a computer storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the screen light control method described in any embodiment of the first aspect.

[0016] Compared with the prior art, the technical solutions provided in this application have the following advantages: The method provided in this application determines the scene of the image by performing grayscale analysis, and then accurately judges whether there is a risk of light leakage based on the grayscale information of the image under different scenes. In addition, it obtains the light leakage level and matches the corresponding backlight control strategy, realizing intelligent and scene-based processing of the light leakage problem. It can adopt differentiated light leakage detection logic for different scene scenes. At the same time, by quantifying the light leakage level and calling the corresponding backlight control strategy, it can make targeted adjustments to the backlight parameters, effectively suppress the halo phenomenon, improve the contrast of the image display and the performance in dark scenes, and at the same time help reduce the power consumption of the whole machine and improve the user's visual experience. Attached Figure Description

[0017] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] One or more embodiments are illustrated by way of example with reference numerals in the accompanying drawings. These illustrations do not constitute a limitation on the embodiments. Elements with the same reference numerals in the drawings are denoted as similar elements. Unless otherwise stated, the figures in the drawings are not to be limited by scale.

[0020] Figure 1 A schematic flowchart illustrating a screen lighting control method provided in an embodiment of this application; Figure 2A schematic diagram illustrating a process for acquiring grayscale information of an image, provided as an embodiment of this application; Figure 3 A schematic diagram illustrating a scene determination process provided in an embodiment of this application; Figure 4 A schematic flowchart illustrating image light leakage detection provided in an embodiment of this application; Figure 5 A schematic diagram illustrating another process for determining screen light leakage provided in an embodiment of this application; Figure 6 This is a schematic diagram illustrating the steps of a screen light control method provided in an embodiment of this application; Figure 7 This is a schematic diagram of the structure of a screen light control device provided in an embodiment of this application; Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0022] The following disclosure provides numerous different embodiments or examples for implementing various structures of the invention. To simplify the disclosure, specific examples of components and arrangements are described below. These are merely examples and are not intended to limit the scope of the invention. Furthermore, reference numerals and / or letters may be repeated in different examples. Such repetition is for simplification and clarity and does not in itself indicate a relationship between the various embodiments and / or arrangements discussed.

[0023] To address the technical problem in existing technologies where intelligent methods cannot effectively eliminate or mitigate the further perception of halo phenomena by the human eye, thereby improving the visual experience, this application provides a screen light control method, device, electronic device, and storage medium. By performing grayscale analysis on the image, it accurately identifies the scene and, based on the grayscale information under different scenes, accurately determines whether light leakage exists. Based on this, it obtains the light leakage level and matches a corresponding backlight control strategy, thereby achieving intelligent and scene-specific processing of screen light leakage. Furthermore, by quantifying the light leakage level and retrieving the corresponding backlight control strategy, it is possible to specifically adjust backlight parameters, effectively suppressing halo phenomena, improving the contrast of the screen display and performance in dark scenes, which not only helps reduce overall power consumption but also significantly improves the user's visual experience.

[0024] Figure 1 This is a flowchart illustrating a screen lighting control method provided in an embodiment of this application, as shown below. Figure 1 As shown, the method specifically includes: S101. Obtain the grayscale information of the input screen.

[0025] In this embodiment, grayscale information of the image is obtained by analyzing and processing the pixel data of the input image.

[0026] S102. Based on the grayscale information of the image, determine the scene of the input image.

[0027] The scene is a display state type divided according to the overall brightness characteristics of the input scene, such as the first scene where the overall scene is bright and the second scene where the overall scene is dark.

[0028] In this embodiment, the global average image level in the grayscale information of the image is compared with a preset backlight specification threshold to determine the backlight level, laying the foundation for subsequent differentiated light leakage detection and backlight control for images with different brightness characteristics.

[0029] S103. Determine whether there is a risk of light leakage in the input image under the scene based on the grayscale information of the image.

[0030] In this embodiment, differentiated judgment logic is adopted for different screen scenes (such as the first scene and the second scene) to determine whether there is a risk of light leakage in the input screen under the scene scene; by using differentiated judgment logic for different screen scenes, the accuracy and adaptability of light leakage detection are improved.

[0031] S104. If there is a risk of light leakage in the input screen under the scene, obtain the light leakage level of the input screen.

[0032] In this embodiment, different quantification methods are used to obtain the light leakage level according to the scene in which the input screen is located, and the degree of light leakage is accurately measured through differentiated processing.

[0033] S105. Retrieve the backlight control strategy corresponding to the light leakage level in the scene, and adjust the backlight parameters of the input screen based on the backlight control strategy.

[0034] The screen backlight control method provided in this application can dynamically match the optimal backlight control strategy according to the light leakage level in different scenarios, thereby achieving fine adjustment of backlight parameters. Specifically, by reducing the local backlight intensity in dark scenes to suppress halo diffusion, and appropriately improving brightness uniformity in bright scenes to avoid overly dark areas, the method effectively enhances the sense of layering and detail in the image. This not only improves display quality but also optimizes power consumption control while ensuring visual comfort, making it suitable for various display scenarios.

[0035] Figure 2 This application provides a schematic diagram of a process for acquiring grayscale information of an image, as illustrated in the embodiments of the present application. Figure 2 As shown, obtaining the grayscale information of the input screen includes: S201. Obtain the grayscale value information histogram of the input screen, and perform frame-by-frame analysis on the grayscale value information histogram to obtain the grayscale value of each frame of the input screen.

[0036] A grayscale histogram is a statistical chart that reflects the distribution of pixels at various grayscale levels in an input image. The horizontal axis represents the grayscale level, and the vertical axis represents the number of pixels at the corresponding grayscale level. By analyzing the morphological characteristics of the histogram, the overall brightness distribution, contrast characteristics, and the proportion of dark and bright areas in the image can be extracted, providing data support for subsequent scene segmentation and light leak detection.

[0037] In this embodiment, the pixel data of the input image is scanned, and the number of pixels corresponding to different grayscale values ​​(usually levels 0-255) is counted to generate a grayscale value information histogram. Then, a frame-by-frame traversal analysis is performed on the histogram to extract the grayscale values ​​of all pixels in each frame as the basis for subsequent grayscale feature calculations, ensuring that the grayscale change characteristics of the image over time can be accurately captured.

[0038] S202. Determine the global average image level of the input screen based on the grayscale value of each frame of the input screen.

[0039] Global average image level refers to the arithmetic mean of the grayscale values ​​of all pixels in the input image, reflecting the overall brightness and darkness of the entire image.

[0040] In this embodiment, the grayscale values ​​of all pixels in each frame of the input image are summed and then divided by the total number of pixels in that frame to obtain the global average image level of a single frame. This serves as a core indicator for measuring the overall brightness of the image and provides key data support for subsequent scene segmentation.

[0041] S203. According to the preset hardware partitioning rules, the input screen is divided into grids in the horizontal and vertical directions to obtain a preset number of screen partitions.

[0042] Hardware partitioning rules refer to the partitioning specifications formulated based on the number and arrangement of physical backlight partitions of the display device. For example, the horizontal direction is divided into M partitions and the vertical direction is divided into N partitions, thereby dividing the input screen into M×N independent rectangular screen partitions. This ensures that each screen partition corresponds one-to-one with the actual backlight control partition of the display device, providing a hardware-matched partitioning basis for subsequent partition-based light leakage detection and backlight adjustment.

[0043] In this embodiment, based on the maximum number of partitions supported by the backlight driver chip of the display device and the physical resolution of the screen, the screen is divided into M intervals in the horizontal direction according to the number of pixel rows and N intervals in the vertical direction according to the number of pixel columns, thereby dividing the entire input screen into M×N uniformly sized rectangular screen partitions, each partition containing a continuous multi-row and multi-column pixel array.

[0044] For example, for an input screen with a resolution of 3840×2160, if it is divided into 32 horizontal sections, each horizontal section contains 120 pixel columns (3840÷32=120), and if it is divided into 16 vertical sections, each vertical section contains 135 pixel rows (2160÷16=135). The pixel size of a single screen section is 120×135 pixels, ensuring that the number of sections is consistent with the number of hardware backlight control channels, and achieving a precise correspondence between sections and backlight units.

[0045] S204. Based on the grayscale value of each frame of the input screen, perform grayscale value analysis on each screen partition of the input screen to determine the average grayscale value and the maximum grayscale value of each screen partition.

[0046] In this embodiment, for each screen partition, the grayscale values ​​of all pixels within that partition are traversed, the sum of all pixel grayscale values ​​is calculated and divided by the total number of pixels in that partition to obtain the average grayscale value of that partition, reflecting the overall brightness level of the partition. Simultaneously, the maximum value among all pixel grayscale values ​​within that partition is selected as the maximum grayscale value of that partition, used to capture any potentially bright local areas within the partition. This provides partition-level refined data support for subsequent identification of abnormal partitions and analysis of light leakage in different screen scenes, ensuring that light leakage detection can accurately locate specific backlight control partitions.

[0047] S205. The global average image level of the input screen, and the average and maximum grayscale values ​​of each screen partition of the input screen are determined as the screen grayscale information of the input screen.

[0048] In this embodiment, the overall grayscale information includes the global average image level, which reflects the overall brightness characteristics of the input image, and the average and maximum grayscale values ​​of each image partition, which reflect the brightness characteristics of each local area. The global average image level describes the overall brightness of the image from a macroscopic perspective, while the average and maximum grayscale values ​​of each image partition provide details of the brightness distribution within that partition from a microscopic perspective. The combination of these two provides comprehensive and detailed data for subsequent accurate light leakage judgment and light leakage level quantification based on different image scenes, ensuring that subsequent light leakage detection and backlight adjustment can simultaneously consider both the overall characteristics and local details of the image.

[0049] The grayscale information acquisition method provided in this application first generates a grayscale value histogram and analyzes it frame by frame to accurately acquire the grayscale value of each frame. Then, based on these grayscale values, it calculates the global average image level to reflect the overall brightness of the image from a macroscopic perspective. Simultaneously, the image is divided into grids according to preset hardware partitioning rules to obtain image partitions corresponding to the actual backlight control partitions of the display device. The average and maximum grayscale values ​​are calculated for each partition to capture the brightness characteristics of local areas from a microscopic perspective. By performing multi-dimensional analysis and processing of the pixel data of the input image, the overall brightness characteristics and local brightness distribution details of the image can be comprehensively captured. This provides comprehensive and reliable data support for accurately judging the image scene, detecting light leakage, and achieving refined backlight control, ensuring the accuracy and effectiveness of the entire image light control process.

[0050] Figure 3 This is a schematic diagram of a scene determination process provided in an embodiment of this application, such as... Figure 3 As shown, determining the scene of the input screen based on the grayscale information includes: S301, retrieve the preset backlight specification threshold.

[0051] Backlight specification thresholds are brightness judgment standards preset based on the hardware parameters of the display device and the visual characteristics of the human eye, used to distinguish different types of screen scenes. For example, for display devices using direct-lit local dimming, the backlight specification threshold can be set to a specific percentage of the global average image level (such as 20%, 50%, etc.), or set to a fixed grayscale value range (such as 0-64 for dark scenes, 192-255 for bright scenes, etc.).

[0052] It should be noted that the backlight specification threshold can be determined through equipment calibration experiments before leaving the factory, and users can also make personalized adjustments according to their usage habits to adapt to the needs of different display content scenarios.

[0053] S302. The global average image level included in the grayscale information of the image is compared with the backlight specification threshold to obtain the relationship between the global average image level and the backlight specification threshold.

[0054] In this embodiment, the specific value of the global average image level is directly compared with the retrieved backlight specification threshold. Through this numerical comparison, the relative relationship between the overall brightness level of the input image and the preset threshold can be clearly defined, providing a clear basis for the classification of subsequent image scenes.

[0055] S303. If the global average image level is greater than the backlight specification threshold, the scene of the input screen is determined to be the first scene.

[0056] The first scene is a scene type where the overall image is relatively bright. At this time, the brightness of most areas in the input image is high, and the global average image level exceeds the backlight specification threshold, indicating that the overall image is in a relatively bright display state.

[0057] In this embodiment, when the global average image level of the input screen is determined to be greater than the backlight specification threshold, the scene of the input screen is classified as the first scene. In this scene, the bright area accounts for a large proportion of the screen, and the dark details are relatively few. The subsequent light leakage judgment will adopt specific logic for the characteristics of the bright scene to improve the adaptability of the detection.

[0058] S304. If the global average image level is less than or equal to the backlight specification threshold, the scene of the input screen is determined to be the second scene.

[0059] The second scenario is a scene where the overall image is dark. In this scenario, the brightness of most areas of the input image is low, and the global average image level does not exceed the backlight specification threshold, indicating that the overall image is in a dark display state.

[0060] In this embodiment, when the global average image level of the input screen is determined to be less than or equal to the backlight specification threshold, the scene of the input screen is determined to be the second scene. In this scene, the dark area accounts for a large proportion of the screen, making it more sensitive to light leakage. The human eye can more easily perceive the halo caused by improper backlight control. Therefore, the subsequent light leakage judgment and backlight adjustment strategy will be specially optimized for the characteristics of dark scenes to more accurately identify and suppress light leakage, improve the display quality of dark scenes and the user's visual experience.

[0061] For example, a threshold spec_BL_lev is set to determine whether a special mechanism will be entered; if global_apl > spec_BL_lev, the current screen is determined to be too bright, and if global_apl ≤ spec_BL_lev, the current screen is determined to be too dark.

[0062] The scene determination method provided in this application retrieves a preset backlight specification threshold and compares the global average image level in the grayscale information of the image with the threshold. Based on the comparison result, the scene is accurately divided. When the global average image level is greater than the backlight specification threshold, the input image is determined to be a first scene that is generally bright; when the global average image level is less than or equal to the backlight specification threshold, it is determined to be a second scene that is generally dark. By dividing the scene based on global brightness characteristics, the overall brightness and darkness attributes of the image can be accurately captured. This provides a clear scene basis for subsequent execution of differentiated light leakage detection logic and backlight adjustment strategies for images with different brightness characteristics. It ensures that light leakage detection and backlight adjustment can be adapted to the actual display state of the image, thereby improving the pertinence and effectiveness of the entire image light control scheme.

[0063] Figure 4 This is a flowchart illustrating a method for determining screen light leakage, as provided in an embodiment of this application. Figure 4 As shown, when the scene is the first scene, determining whether the input image has a risk of light leakage in the scene based on the image grayscale information includes: S401. Based on the grayscale information of the image, traverse all image partitions of the input image and determine the number of pixels with zero grayscale value in each image partition.

[0064] A zero-grayscale pixel is a pure black pixel with a grayscale value of 0. In theory, it should appear completely dark in a bright scene. If there is abnormal brightness, it may be due to light leakage.

[0065] In this embodiment, by traversing all pixels within each screen partition and counting the total number of pixels with a grayscale value of 0, the basic data for measuring the size of the dark area of ​​that partition is used.

[0066] S402. Determine whether there is an abnormal partition in the input screen, wherein the proportion of the number of zero grayscale pixels in the abnormal partition to the total number of pixels is greater than a preset zero grayscale proportion threshold.

[0067] Abnormal partitioning refers to a partition in a bright scene where the proportion of dark areas is abnormally high.

[0068] In this embodiment, the criterion for determining abnormal partitions is whether the proportion of zero-grayscale pixels within a partition to the total number of pixels in that partition exceeds a preset zero-grayscale proportion threshold. By filtering out abnormal partitions, the focus can be placed on key areas in the scene that may have light leakage issues, narrowing the scope of light leakage detection and improving detection efficiency.

[0069] S403. If there is an abnormal partition in the input screen, obtain the average grayscale value and the maximum grayscale value of the abnormal partition.

[0070] The average grayscale value reflects the overall average brightness level of the dark areas within the abnormal partition; the maximum grayscale value is used to determine whether there are any locally abnormally bright pixels within the abnormal partition due to light leakage.

[0071] In this embodiment, the average and maximum grayscale values ​​of the identified abnormal partitions are extracted from the grayscale information of the image, providing local brightness feature data of the abnormal partitions for subsequent quantification of light leakage levels in the first scene.

[0072] S404. Determine whether the maximum grayscale value of the abnormal partition is greater than the average grayscale value by a preset multiple.

[0073] In this embodiment, the maximum grayscale value of the abnormal partition is compared with the average grayscale value of a preset multiple to determine whether there is a significant local brightness abnormality in the partition.

[0074] It should be noted that the preset multiplier can be set according to the backlight uniformity index and light leakage detection accuracy requirements of the display device, such as setting it to 2 times or 3 times.

[0075] S405. If the maximum grayscale value is greater than the average grayscale value by a preset multiple, it is determined that the input screen has a risk of screen light leakage in the first scene.

[0076] In this embodiment, if the maximum grayscale value of an abnormal partition is greater than the average grayscale value by a preset multiple, it indicates that there are locally abnormally bright pixels in the partition, which are significantly different from the average brightness of the surrounding dark areas, consistent with the characteristics of local overbrightness caused by light leakage in a bright scene; conversely, it indicates that the brightness distribution in the partition is relatively uniform, and even if there is a high proportion of dark areas, it may not be caused by light leakage, but by dark elements in the image content itself; effectively eliminating the interference of dark areas in the image content itself, and accurately locating the partition with light leakage problem caused by improper backlight control.

[0077] For example, the current image is generally too bright, and it is necessary to further determine whether there are any star-shaped features in the image. The specific determination is based on the following two conditions: Condition a: Block_data0_cnt ≥ 2 / 3 * block_all_cnt, Where `Block_data0_cnt` represents the number of pixels in the current block with a `data` value of 0, and `block_all_cnt` represents the total number of pixels in the current block. The next condition is analyzed for blocks that satisfy condition a.

[0078] Condition b: block_max ≥ 2 * block_apl; If both of the above conditions are met, it can be determined that there are dot-shaped features in the current image that are prone to causing halo problems.

[0079] The image light leakage judgment method provided in this application embodiment first filters out abnormal areas that may have light leakage by the proportion of zero grayscale pixels in the first scenario, thus narrowing the detection range. Then, by using the multiple relationship between the maximum and average grayscale values, it effectively distinguishes between dark areas caused by the image content itself and local abnormal brightness caused by backlight leakage, avoiding misjudgment of normal dark scene elements. It can accurately identify light leakage phenomena caused by improper backlight control in bright scenes, providing accurate light leakage zone location and judgment basis for subsequent targeted backlight adjustments, and ensuring the accuracy and reliability of the light leakage judgment results.

[0080] Figure 5 This is a schematic diagram of another process for determining screen light leakage provided in an embodiment of this application, as shown below. Figure 5 As shown, when the scene is the second scene, determining whether the input image has a risk of light leakage in the scene based on the image grayscale information includes: S501. Based on the grayscale information of the image, determine whether there is a completely black partition in the input image, wherein the average grayscale value and the maximum grayscale value of the completely black partition are both zero.

[0081] A completely black area refers to a section of the image that should theoretically be completely devoid of light in a dark scene, where both the average and maximum grayscale values ​​should be 0.

[0082] In this embodiment, by traversing all screen partitions, it checks whether there are partitions where the average grayscale value and the maximum grayscale value are both 0, thereby determining the existence of completely black partitions.

[0083] S502. If there is a completely black section in the input screen, determine whether the input screen is a completely black screen or a partially black screen.

[0084] In this embodiment, the input screen type is determined by statistically analyzing the proportion of completely black partitions. If the proportion of completely black partitions to the total number of screen partitions reaches a preset completely black screen threshold, the input screen is determined to be a completely black screen; if the proportion of completely black partitions is within a preset partial black screen threshold range, and there are non-black partitions in the four corners of the input screen, it is determined to be a partial black screen.

[0085] S503. If the input screen is a completely black screen or a partially black screen, determine that the input screen has a risk of light leakage in the second scene.

[0086] In theory, all areas of a completely black screen should be in a state of complete darkness, but there may be light leakage. For a partially black screen, the non-black areas at the four corners are normal display areas, while the completely black area in the middle should remain pure black. If the average or maximum grayscale value of the completely black area in the middle is greater than 0, it indicates that there is light leakage in that completely black area.

[0087] In this embodiment, when the input screen is determined to be a completely black screen or a partially black screen, it can be determined that the input screen has a risk of light leakage in the second scene. The light leakage area will show abnormal brightness in the dark scene that does not match the content of the screen.

[0088] For example, if the current image is generally dark, it's necessary to further determine if there are any completely black blocks and check if there are any non-completely black blocks in the four corners. If all four corners are completely black, it's important to be aware that this might affect the brightness test in a small window, thus preventing further steps. Specific judgment criteria are as follows: Condition c: block_max=block_apl=0, used to confirm whether all blocks in the current frame are completely black.

[0089] Condition d: (block_apl_corner1≠0||block_apl_corner2≠0||block_apl_corner3≠0||block_apl_corner4≠0)||global_apl=0, is used to determine if there are any non-zero block_apl values ​​at the four corners, or if the current scene is completely black. This condition determines whether there are completely black sections in the current dark scene and whether they meet the scene characteristics for light leak detection, thus identifying the risk of light leaks in the scene.

[0090] The image light leakage judgment method provided in this application embodiment, in the second scenario, firstly identifies potential light leakage areas by judging whether the input image is a completely black image or a partially black image. For a completely black image, all its image partitions should theoretically be in a pure black state, and the average and maximum grayscale values ​​should both be 0. Once a grayscale value of any partition is detected to deviate from 0, it can be judged as light leakage. For partially black images, if a partition that should be pure black has a non-zero grayscale value, it can be clearly identified as light leakage. Through the judgment logic based on the characteristics of dark scenes, it can accurately capture the light leakage phenomenon caused by improper backlight control in dark environments, avoid misjudging normal dark content in complex dark scenes, and provide accurate light leakage area positioning for subsequent targeted backlight suppression.

[0091] In an optional embodiment of the present invention, when the scene is a first scene, obtaining the light leakage level of the input scene includes: Obtain the maximum and average grayscale values ​​of each abnormal partition in the input image; for each abnormal partition, calculate the ratio of the maximum grayscale value to the average grayscale value to obtain the light leakage quantization value of each abnormal partition; determine the light leakage level of the input image based on the light leakage quantization values ​​of all abnormal partitions.

[0092] The light leakage quantification value directly reflects the degree of deviation of the local maximum brightness in the abnormal zone from the average brightness of the overall dark area. The larger the ratio, the more severe the local bright phenomenon caused by light leakage in the zone.

[0093] In this embodiment, firstly, the maximum grayscale value of each abnormal partition is divided by the average grayscale value of that partition to obtain the light leakage quantization value of that abnormal partition. After obtaining the light leakage quantization values ​​of all abnormal partitions, these light leakage quantization values ​​can be summarized and analyzed to determine the light leakage level of the input screen in the first scene, providing a quantitative basis for subsequent differentiated backlight intensity settings.

[0094] For example, leakage_level = [block_max / block_apl] ∈ [2, m]; If the range of backlight adjustment is set to α, then α∈[0,1]; the larger the value of α, the higher the degree of global backlight dimming.

[0095] When leakage_level=2, α is 0, which means that the backlight is not darkened.

[0096] When leakage_level=m, α is 1, which means that the backlight is darkened to the maximum extent.

[0097] The light leakage level determination method provided in this application can transform the abstract light leakage phenomenon into a specific numerical index by quantifying the light leakage quantification value of each abnormal partition, making the classification of light leakage level more objective and accurate.

[0098] In an optional embodiment of the present invention, when the scene is a second scene, obtaining the light leakage level of the input scene includes: Calculate the ratio of the global average image level of the input image to the maximum standard grayscale value to obtain the normalized light leakage quantization value of the input image; determine the light leakage level of the input image based on the normalized light leakage quantization value.

[0099] The standard maximum grayscale value is usually set to 255 (corresponding to the grayscale value of a pure white pixel). In this embodiment, by dividing the global average image level by 255, the light leakage level can be mapped to a normalized range of 0-1, which facilitates unified measurement and level classification. After obtaining the normalized light leakage quantization value, the light leakage level can be divided by preset multiple light leakage level threshold ranges. Based on the abnormal brightness level of the overall image in dark scenes, the severity of light leakage can be objectively assessed, providing a quantitative reference for the subsequent implementation of backlight suppression strategies of different intensities.

[0100] For example, leakage_level = global_apl / 255, where global_apl ∈ [0, spec_BL_lev]. Through normalization, leakage_level ∈ [0, 1].

[0101] If the range of backlight adjustment is set to β, then β∈[0,1]. The larger the value of β, the higher the overall backlight dimming level.

[0102] When leakage_level=0, β is 0, indicating that no backlight dimming operation is performed; when leakage_level=spec_BL_lev, β is 1, indicating that the backlight is dimmed to the maximum extent.

[0103] The light leakage level determination method provided in this application normalizes the global average image level and the maximum standard grayscale value in dark scenes, limiting the light leakage quantization value to a standardized range of 0-1. This avoids deviations in light leakage level assessment caused by differences in the original brightness of the image, ensuring the consistency and comparability of light leakage degree evaluation under different dark scenes. By determining the light leakage level based on the global brightness anomaly level, the method can accurately reflect the overall severity of light leakage in dark scenes. This facilitates more precise backlight control for subsequent backlight dimming operations based on the light leakage level, effectively suppressing light leakage in dark areas and improving the contrast and purity of the image display.

[0104] Figure 6 This is a schematic diagram illustrating the steps of a screen light control method provided in an embodiment of this application, as shown below. Figure 6 As shown, the image lighting control method mainly includes the following steps: Step 1: Obtain the original video footage that needs to be processed.

[0105] Step 2: Divide the screen into regions based on hardware (such as the partitioning capabilities of the display device).

[0106] Step 3: Calculate the global APL (global_apl) of the current screen by statistically analyzing the APL parameters, and at the same time, calculate the average block_apl and maximum block_apl (block_max) of each partition.

[0107] Step 4: Determine if the global APL is greater than Spec_BL_Lv1. This is the core decision point in the process, and the analysis is divided into two paths based on the result: Path 1 (Global APL>Spec_BL_Lv1): Check if there are "star-shaped blocks" in the screen, and if the number of such blocks exceeds 1 / 3 of the global total.

[0108] Path 2 (Global APL≤Spec_BL_Lv1): First, determine whether there is a "completely black block" in the entire screen, then further confirm whether there are "non-completely black blocks" around the entire screen, and finally determine whether it is a "completely black screen".

[0109] Step 5: Dynamically Adjust Parameters. Based on the analysis results of the two paths above, perform the "Dynamically Adjust Parameters" operation to ultimately optimize the display effect of the screen.

[0110] The screen light control method provided in this application constructs a complete logical system from screen analysis to light leakage assessment by performing hardware partitioning of the input screen, APL parameter statistics, scene type judgment, abnormal partition screening, light leakage risk identification, and light leakage level quantification. It can adopt differentiated judgment strategies for different screen scenes (bright scenes and dark scenes), accurately locate light leakage partitions and quantify light leakage levels, effectively eliminate the interference of the screen content itself on the light leakage judgment, and provide an accurate and reliable basis for subsequent targeted backlight adjustments, thereby realizing intelligent detection and assessment of screen light leakage problems.

[0111] Figure 7 This is a schematic diagram of the structure of a screen light control device provided in an embodiment of this application, as shown below. Figure 7 As shown, the device specifically includes: The information acquisition module 701 is used to acquire the grayscale information of the input screen; The determining module 702 is used to determine the scene of the input screen based on the screen grayscale information; The judgment module 703 is used to determine whether there is a risk of light leakage in the input image under the scene based on the image grayscale information; The level acquisition module 704 is used to acquire the light leakage level of the input screen when there is a risk of light leakage in the screen scene. The adjustment module 705 is used to retrieve the backlight control strategy corresponding to the light leakage level in the scene and adjust the backlight parameters of the input scene based on the backlight control strategy.

[0112] In one possible implementation, the information acquisition module 701 is further configured to acquire a grayscale value information histogram of the input screen, perform frame-by-frame analysis on the grayscale value information histogram to obtain the grayscale value of each frame of the input screen; determine the global average image level of the input screen based on the grayscale value of each frame of the input screen; divide the input screen into grids in the horizontal and vertical directions according to a preset hardware partitioning rule to obtain a preset number of screen partitions; perform grayscale value analysis on each screen partition of the input screen based on the grayscale value of each frame of the input screen to determine the average grayscale value and the maximum grayscale value of each screen partition; and determine the global average image level of the input screen, as well as the average grayscale value and the maximum grayscale value of each screen partition of the input screen, as the screen grayscale information of the input screen.

[0113] In one possible implementation, the determining module 702 is further configured to retrieve a preset backlight specification threshold; compare the global average image level included in the image grayscale information with the backlight specification threshold to obtain the magnitude relationship between the global average image level and the backlight specification threshold; if the global average image level is greater than the backlight specification threshold, determine the image scene of the input image as a first scene; if the global average image level is less than or equal to the backlight specification threshold, determine the image scene of the input image as a second scene.

[0114] In one possible implementation, the judgment module 703 is further configured to: traverse all screen partitions of the input screen based on the screen grayscale information; determine the number of pixels with zero grayscale values ​​in each screen partition; determine whether there are abnormal partitions in the input screen, wherein the proportion of the number of pixels with zero grayscale values ​​in the abnormal partitions to the total number of pixels is greater than a preset zero grayscale proportion threshold; if there are abnormal partitions in the input screen, obtain the average grayscale value and the maximum grayscale value of the abnormal partitions; determine whether the maximum grayscale value of the abnormal partitions is greater than a preset multiple of the average grayscale value; if the maximum grayscale value is greater than a preset multiple of the average grayscale value, determine that the input screen has a risk of screen light leakage in the first scene.

[0115] In one possible implementation, the judgment module 703 is further configured to determine, based on the grayscale information of the image, whether there is a completely black partition in the input image, wherein the average grayscale value and the maximum grayscale value of the completely black partition are both zero; if there is a completely black partition in the input image, determine whether the input image is a completely black image or a partially black image; if the input image is a completely black image or a partially black image, determine that the input image has a risk of light leakage in the second scene.

[0116] In one possible implementation, the level acquisition module 704 is further configured to acquire the maximum grayscale value and the average grayscale value of each abnormal partition in the input screen; for each abnormal partition, calculate the ratio of the maximum grayscale value to the average grayscale value to obtain the light leakage quantization value of each abnormal partition; and determine the light leakage level of the input screen based on the light leakage quantization values ​​of all abnormal partitions.

[0117] In one possible implementation, the level acquisition module 704 is further configured to calculate the ratio of the global average image level of the input screen to the maximum standard grayscale value to obtain the normalized light leakage quantization value of the input screen; and determine the light leakage level of the input screen based on the normalized light leakage quantization value.

[0118] The screen lighting control device provided in this embodiment can be as follows: Figure 7The screen light control device shown can perform the following functions: Figure 1-6 All steps of mid-screen light control, thereby achieving Figure 1-6 For details on the light control technology shown in the image, please refer to [link / reference]. Figure 1-6 The relevant descriptions are presented concisely and will not be elaborated upon here.

[0119] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0120] Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application, such as... Figure 8 As shown, this application embodiment provides an electronic device, including a processor 801, a communication interface 802, a memory 803, and a communication bus 804. The processor 801, communication interface 802, and memory 803 communicate with each other via the communication bus 804. The memory 803 stores computer programs. When the processor 801 executes the program stored in the memory 803, it implements the screen light control steps provided in any of the aforementioned method embodiments. Obtain the grayscale information of the input screen; determine the scene of the input screen based on the grayscale information; determine whether there is a risk of light leakage in the input screen under the scene based on the grayscale information; if there is a risk of light leakage in the input screen under the scene, obtain the light leakage level of the input screen; retrieve the backlight control strategy corresponding to the light leakage level under the scene, and adjust the backlight parameters of the input screen based on the backlight control strategy.

[0121] In one possible implementation, a grayscale histogram of the input image is acquired, and the grayscale histogram is analyzed frame by frame to obtain the grayscale value of each frame of the input image. Based on the grayscale value of each frame of the input image, the global average image level of the input image is determined. According to a preset hardware partitioning rule, the input image is divided into grids in the horizontal and vertical directions to obtain a preset number of image partitions. Based on the grayscale value of each frame of the input image, grayscale value analysis is performed on each image partition of the input image to determine the average grayscale value and the maximum grayscale value of each image partition. The global average image level of the input image, as well as the average grayscale value and the maximum grayscale value of each image partition of the input image, are determined as the image grayscale information of the input image.

[0122] In one possible implementation, a preset backlight specification threshold is retrieved; the global average image level included in the image grayscale information is compared with the backlight specification threshold to obtain the magnitude relationship between the global average image level and the backlight specification threshold; if the global average image level is greater than the backlight specification threshold, the image scene of the input image is determined to be a first scene; if the global average image level is less than or equal to the backlight specification threshold, the image scene of the input image is determined to be a second scene.

[0123] In one possible implementation, based on the grayscale information of the image, all image partitions of the input image are traversed to determine the number of pixels with zero grayscale values ​​in each image partition; it is determined whether there are abnormal partitions in the input image, wherein the proportion of the number of pixels with zero grayscale values ​​in the abnormal partitions to the total number of pixels is greater than a preset zero grayscale proportion threshold; if there are abnormal partitions in the input image, the average grayscale value and the maximum grayscale value of the abnormal partitions are obtained; it is determined whether the maximum grayscale value of the abnormal partitions is greater than a preset multiple of the average grayscale value; if the maximum grayscale value is greater than a preset multiple of the average grayscale value, it is determined that the input image has a risk of image light leakage in the first scene.

[0124] In one possible implementation, based on the grayscale information of the image, it is determined whether there is a completely black partition in the input image, wherein the average and maximum grayscale values ​​of the completely black partition are both zero; if there is a completely black partition in the input image, it is determined whether the input image is a completely black image or a partially black image; if the input image is a completely black image or a partially black image, it is determined that the input image has a risk of light leakage in the second scene.

[0125] In one possible implementation, the maximum grayscale value and the average grayscale value of each abnormal partition in the input screen are obtained; for each abnormal partition, the ratio of the maximum grayscale value to the average grayscale value is calculated to obtain the light leakage quantization value of each abnormal partition; based on the light leakage quantization values ​​of all abnormal partitions, the light leakage level of the input screen is determined.

[0126] In one possible implementation, the ratio of the global average image level of the input image to the maximum standard grayscale value is calculated to obtain the normalized light leakage quantization value of the input image; based on the normalized light leakage quantization value, the light leakage level of the input image is determined.

[0127] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented using software plus a general-purpose hardware platform, or of course, using hardware. Based on this understanding, the above technical solutions, in essence or the parts that contribute to the related technology, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0128] It should be understood that the terminology used herein is for the purpose of describing particular exemplary embodiments only and is not intended to be limiting. Unless the context clearly indicates otherwise, the singular forms “a,” “an,” and “described” as used herein may also include the plural forms. The terms “comprising,” “including,” “containing,” and “having” are inclusive and therefore indicate the presence of the stated features, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, elements, components, and / or combinations thereof. The method steps, processes, and operations described herein are not construed as requiring them to be performed in a particular order described or illustrated unless the order of performance is explicitly indicated. It should also be understood that additional or alternative steps may be used.

[0129] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A method for controlling screen light, characterized in that, include: Obtain the grayscale information of the input screen; Based on the grayscale information of the image, the scene of the input image is determined; Based on the grayscale information of the image, determine whether the input image has a risk of light leakage in the scene. If there is a risk of light leakage in the input screen under the scene, obtain the light leakage level of the input screen; The backlight control strategy corresponding to the light leakage level in the scene is retrieved, and the backlight parameters of the input scene are adjusted based on the backlight control strategy.

2. The method according to claim 1, characterized in that, The acquisition of the grayscale information of the input screen includes: Obtain the grayscale value information histogram of the input image, and analyze the grayscale value information histogram frame by frame to obtain the grayscale value of each frame of the input image; The global average image level of the input image is determined based on the grayscale value of each frame of the input image. According to the preset hardware partitioning rules, the input screen is divided into grids in the horizontal and vertical directions to obtain a preset number of screen partitions. Based on the grayscale value of each frame of the input image, grayscale value analysis is performed on each frame partition of the input image to determine the average and maximum grayscale values ​​of each frame partition. The global average image level of the input image, as well as the average and maximum grayscale values ​​of each image partition of the input image, are determined as the image grayscale information of the input image.

3. The method according to claim 1, characterized in that, Determining the scene of the input screen based on the grayscale information includes: Retrieve the preset backlight specification threshold; The global average image level, which is included in the grayscale information of the image, is compared with the backlight specification threshold to obtain the relationship between the global average image level and the backlight specification threshold. If the global average image level is greater than the backlight specification threshold, the scene of the input image is determined to be the first scene; If the global average image level is less than or equal to the backlight specification threshold, the scene of the input image is determined to be the second scene.

4. The method according to claim 1, characterized in that, When the scene is the first scene, determining whether the input image has a risk of light leakage in the scene based on the image grayscale information includes: Based on the grayscale information of the image, all image partitions of the input image are traversed to determine the number of pixels with zero grayscale value in each image partition; Determine whether there is an abnormal partition in the input screen, wherein the proportion of the number of zero grayscale pixels in the abnormal partition to the total number of pixels is greater than a preset zero grayscale proportion threshold. If there are abnormal partitions in the input screen, obtain the average grayscale value and the maximum grayscale value of the abnormal partitions; Determine whether the maximum grayscale value of the abnormal partition is greater than the average grayscale value by a preset multiple; If the maximum grayscale value is greater than the average grayscale value by a preset multiple, it is determined that the input screen has a risk of light leakage in the first scene.

5. The method according to claim 1, characterized in that, When the scene is the second scene, determining whether the input image has a risk of light leakage in the scene based on the image grayscale information includes: Based on the grayscale information of the image, it is determined whether there is a completely black partition in the input image, wherein the average grayscale value and the maximum grayscale value of the completely black partition are both zero; If there is a completely black section in the input screen, determine whether the input screen is a completely black screen or a partially black screen; If the input screen is a completely black screen or a partially black screen, it is determined that the input screen has a risk of light leakage in the second scene.

6. The method according to claim 1, characterized in that, When the scene is the first scene, obtaining the light leakage level of the input scene includes: Obtain the maximum and average grayscale values ​​of each abnormal partition in the input screen; For each of the abnormal partitions, the ratio of the maximum grayscale value to the average grayscale value is calculated to obtain the light leakage quantization value of each abnormal partition; The light leakage level of the input screen is determined based on the light leakage quantization value of all the abnormal partitions.

7. The method according to claim 1, characterized in that, When the scene is the second scene, obtaining the light leakage level of the input scene includes: The normalized light leakage quantization value of the input image is obtained by calculating the ratio of the global average image level of the input image to the maximum standard gray level. The light leakage level of the input screen is determined based on the normalized light leakage quantization value.

8. A screen light control device, characterized in that, include: The information acquisition module is used to acquire the grayscale information of the input screen. The determining module is used to determine the scene of the input screen based on the grayscale information of the screen. The judgment module is used to determine whether there is a risk of light leakage in the input image under the scene based on the image grayscale information; The level acquisition module is used to acquire the light leakage level of the input screen when there is a risk of light leakage in the screen scene. The adjustment module is used to retrieve the backlight control strategy corresponding to the light leakage level in the scene and adjust the backlight parameters of the input scene based on the backlight control strategy.

9. An electronic 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 screen lighting control method according to any one of claims 1 to 7.

10. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the screen light control method according to any one of claims 1 to 7.

Images