Halo optimization method and device of display equipment, computer equipment and storage medium

Abstract

The invention provides a halo optimization method and device for display equipment, computer equipment and a storage medium, and the method comprises the steps: obtaining a first brightness value of the display equipment in a full black picture, and obtaining second brightness values of the display equipment in white field pictures with different proportions at the peripheral edges of the white field pictures; and according to the first brightness value, the second brightness value and a preset optimization model, performing halo optimization on the partitions of the display equipment under the white field pictures with different proportions. According to the first brightness value of the display device in the full black picture and the second brightness value of the display device in the white field pictures in different proportions, the partition halo of the display device in the white field pictures in different proportions is optimized through the preset optimization model, and the optimization precision is high; the image quality effect of the display equipment can be effectively improved.

Description

Technical Field

[0001] The present invention relates to the field of display devices, and in particular to a halo optimization method, device, computer equipment and storage medium for a display device. Background Art

[0002] In the display device field, Local Dimming technology is an important means of improving the dynamic range of images and is widely used in products such as televisions and monitors. Its working mechanism is to divide the screen backlight into multiple independently controlled zones, dynamically adjusting the brightness of each backlight zone based on the brightness of each zone in the current image. When the image is dark, the backlight in the corresponding zone is reduced in brightness or even turned off to produce deeper blacks. In bright scenes, the backlight in the corresponding zone is increased to make highlights more transparent, thereby enhancing image contrast and making light and dark details clearer.

[0003] However, current products equipped with this technology have significant practical drawbacks: when playing videos, the screen is prone to haloing, which is large and noticeable. This phenomenon is particularly prominent in images with strong contrast between light and dark. For example, when displaying bright text or graphics against a black background, the edges of the bright areas will spread a blurred white light and shadow into the surrounding dark areas, blurring the edges of the image and destroying the clear boundaries that should be there.

[0004] As consumers' demands for display performance continue to rise, image quality has become a core factor influencing the product experience. Sharp edges, pure blacks, and precise light-shadow transitions are fundamental user expectations for high-quality display devices. The current halo issue with the Local Dimming function directly impacts the detail and realism of the image, becoming a key bottleneck hindering further improvements in display device image quality. Summary of the Invention

[0005] Embodiments of the present invention provide a method and apparatus for optimizing the halo of a display device, a computer device, and a storage medium to solve the problem of poor image quality caused by the halo problem of the display device.

[0006] In a first aspect, an embodiment of the present invention provides a halo optimization method for a display device, comprising: obtaining a first brightness value of the display device under a completely black screen, and respectively obtaining second brightness values ​​of the display device at the edges around the white screen under white screens with different proportions; performing halo optimization on partitions of the display device under white screens with different proportions according to the first brightness value, the second brightness value and a preset optimization model.

[0007] In a second aspect, an embodiment of the present invention further provides a halo optimization apparatus for a display device, which includes a unit for executing the above method.

[0008] In a third aspect, an embodiment of the present invention further provides a computer device, which includes a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the above method when executing the computer program.

[0009] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, wherein the storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a processor, the above method can be implemented.

[0010] The present application provides a halo optimization method, apparatus, computer device, and storage medium for a display device. The method optimizes the halo of the partitioned areas of the display device for white screens of different proportions based on the first brightness value of the display device under a completely black screen and the second brightness value of white screens of different proportions through a preset optimization model. The method has high optimization accuracy and can effectively improve the image quality of the display device. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0012] Figure 1 A schematic flow chart of a halo optimization method for a display device provided by an embodiment of the present invention; Figure 2 A schematic diagram of a sub-process of a halo optimization method for a display device provided by an embodiment of the present invention; Figure 3 A schematic diagram of a sub-process of a halo optimization method for a display device provided by an embodiment of the present invention; Figure 4 A schematic diagram of a sub-process of a halo optimization method for a display device provided by an embodiment of the present invention; Figure 5 A schematic diagram of a sub-process of a halo optimization method for a display device provided by an embodiment of the present invention; Figure 6 A schematic diagram of a sub-process of a halo optimization method for a display device provided by an embodiment of the present invention; Figure 7 A schematic block diagram of a halo optimization apparatus for a display device provided by an embodiment of the present invention; Figure 8 A schematic block diagram of a computer device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0013] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0014] It will be understood that when used in this specification and the appended claims, the terms “comprises” and “comprising” indicate the presence of described features, integers, steps, operations, elements and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof.

[0015] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the present invention. As used in the specification and appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms unless the context clearly indicates otherwise.

[0016] It should be further understood that the term "and / or" used in the present description and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0017] See also Figure 1 This is a schematic flow chart of the halo optimization method for a display device provided by an embodiment of the present invention. In this application, the halo optimization method for a display device is applied in the field of production of display devices, and is suitable for debugging scenarios of display devices where the display device is prone to poor image quality due to obvious halo, large range, etc. when using the zone dimming technology. By analyzing the first brightness value of the display device under a completely black screen and the second brightness value of white screens with different proportions, the zone halo of the display device with different proportions of white screens is optimized according to the preset optimization model. The optimization accuracy is high, and the image quality of the display device can be effectively improved.

[0018] The present application provides a halo optimization method, apparatus, computer device, and storage medium for a display device. The halo optimization method for the display device includes: obtaining a first brightness value of the display device under a completely black screen, and respectively obtaining second brightness values ​​of the display device at the edges around the white screen under white screens of different proportions; and performing halo optimization on partitions of the display device under white screens of different proportions based on the first brightness value, the second brightness value, and a preset optimization model.

[0019] This application optimizes the partitioned halo of the display device with different proportions of white field images based on the first brightness value of the display device under a completely black screen and the second brightness value of the white field images with different proportions through the preset optimization model. The optimization accuracy is high and the picture quality of the display device can be effectively improved.

[0020] Figure 1 FIG. 1 is a flow chart of a halo optimization method for a display device according to an embodiment of the present invention. Figure 1 As shown, the method includes the following steps S10-S20.

[0021] S10, obtaining a first brightness value of a display device under a completely black screen, and obtaining second brightness values ​​of the display device at edges around white screens of different proportions; Specifically, a display device refers to an electronic device capable of displaying images, such as LCD TVs, OLED displays, and Mini LED screens. Its core function is to convert electrical signals into visual images. Zone dimming technology is an important means of improving the dynamic range of an image. It primarily divides the screen backlight into multiple independently controlled zones, dynamically adjusting the brightness of each corresponding backlight zone based on the brightness of each zone in the current image. Haloing, a whitening phenomenon that occurs when a display device displays images with strong contrast, causes the edges of bright areas to spread into dark areas. This reduces image contrast and clarity, thereby affecting image quality.

[0022] In this embodiment, a method for optimizing the halo of a display device is mainly provided. First, it is necessary to detect whether the halo range and visibility of the display device do not meet the standards in the current state, and then optimize the halo that does not meet the standards.

[0023] First, the system needs to obtain the first brightness value of the display device under a completely black screen. The completely black screen refers to a screen in which all pixels output by the display device are black, which is used to detect the basic luminescence of the device under an ideal dark state. The specific detection steps are: under the premise of turning off the partitioning algorithm, control the display device to play a completely black screen, and then use a brightness measuring instrument to test the brightness value of any point on the display device to obtain the first brightness value. The first brightness value is the brightness measurement value of the display device under a completely black screen. The first brightness value reflects the basic light leakage level of the device. The lower the value, the higher the dark field purity of the device. Under normal circumstances, the first brightness value is 0.

[0024] Then, the second brightness value of the edge of the white screen of the display device is obtained for different proportions of white screen. A white screen refers to a screen in which all pixels of the display device are white. Different proportions of white screen refer to screens in which the white area accounts for different proportions of the total screen area (e.g., a 10% white screen means that the white area accounts for 10% of the screen area, and the remaining area is completely black), thereby simulating display scenes of the display device under different brightness ranges.

[0025] The second brightness value refers to the brightness measurement value at the boundary between the white area and the surrounding black area (usually within 3-5 mm outside the edge) in white images of different proportions. That is, the brightness value outside the white image and close to the edge of the white image. The measurement location of the second brightness value cannot be too far from the white area and cannot cover the white area to avoid inaccurate test values. The second brightness value can be accurately measured by physical fixed points. The second brightness value is used to quantitatively evaluate the degree of halo diffusion. The specific acquisition steps are: when the display device is playing a white image of a certain proportion, using a brightness measuring instrument to obtain the second brightness value at the center of the upper, lower, left, and right edges of the white image in four directions. Since the display device can play white images of different proportions, it is necessary to detect the second brightness value at the four directions in each white image separately and record all the second brightness values ​​in a table to facilitate subsequent comparison of each second brightness value with the first brightness value to determine whether the halo in the corresponding white image needs to be optimized.

[0026] Through the above method, the halo characteristics of display devices in different display scenarios can be accurately quantified, providing data support for targeted optimization and effectively improving display quality problems caused by halo.

[0027] In one embodiment, step S10 may include step S11 .

[0028] S11. The proportion of the white screen includes 5% to 70% of the white screen relative to the screen of the display device.

[0029] Since the halo is most obvious in the white field, because white is a pure white screen and is the brightest; the white field basically covers all the middle partitions. When the halo of these partitions is well optimized, when you go to any screen, you will find that the halo effect of these screens is also greatly optimized. Therefore, in this embodiment, different proportions of white field screens are used to optimize the halo of the display device respectively, instead of selecting only a 20% white field screen for optimization.

[0030] Specifically, the white screen ratio range is set between 5% and 70%. Specifically, images with a white screen area of ​​5% to 70% of the total screen area have a better halo optimization effect on display devices. Furthermore, images with a white screen ratio of more than 70% are so large that virtually the entire screen area is illuminated, eliminating the need for testing and optimization, thereby improving optimization efficiency and saving costs.

[0031] More specifically, if the display device has a large number of partitions and a small partition size, a white field image with a ratio of 5%-90% can be used to optimize the halo of the display device.

[0032] S20, performing halo optimization on partitions of the display device under white field images with different proportions according to the first brightness value, the second brightness value, and a preset optimization model; Specifically, the preset optimization model is a pre-built algorithm model with built-in ideal brightness distribution data under different display scenarios. It can calculate the adjustment parameters of the backlight partition according to the actual brightness value input to achieve halo optimization.

[0033] When optimizing the halo of a display device, it is first necessary to obtain the first brightness value and the second brightness value as basic data. When obtaining the first brightness value, control the display device to output a completely black screen. After the screen stabilizes, use a brightness measuring instrument to detect the brightness of any point on the screen, and finally obtain the first brightness value reflecting the device under a completely black screen. Afterwards, select different white field pictures that occupy a certain range of the total screen area. The white areas of these white field pictures are usually located in the center of the screen, with regular shapes and clear boundaries with the surrounding black areas. For each white field picture, perform brightness measurement at the boundary edge with the black area to obtain the second brightness value under the corresponding proportion. These values ​​can intuitively reflect the degree of halo diffusion in different display scenarios. After obtaining the first brightness value and each of the second brightness values, these data are input into a preset optimization model. The optimization model analyzes the first brightness value and the second brightness value, and by comparing the difference between the first brightness value and each of the second brightness values, determines the range and obviousness of the halo under white field images of different proportions. Subsequently, the optimization model calculates the corresponding brightness adjustment parameters for each partition based on the built-in algorithm and the distribution characteristics of the backlight partitions of the display device. These parameters can accurately control the backlight output intensity of each partition. For areas with severe halo diffusion, the model will calculate the parameters to appropriately reduce the backlight brightness to reduce the diffusion of light to dark areas; for areas that need to maintain brightness, it will ensure that their brightness is not excessively affected, thereby effectively reducing the halo range and reducing the obviousness of the halo while ensuring the normal display effect of the picture, and ultimately achieving the optimization of the halo of the display device.

[0034] Therefore, in this embodiment, the halo of the display device is optimized by using the first brightness value, the second brightness value and the optimization model, with high optimization accuracy and efficiency, which can significantly improve the image quality of the display device, thereby improving the user experience.

[0035] In one embodiment, if Figure 2 As shown, step S20 may include steps S21-S22.

[0036] S21, respectively determining the magnitude of the first brightness value and each of the second brightness values; S22: If the second brightness value is greater than the first brightness value, the optimization model performs halo optimization on the partition corresponding to the second brightness value.

[0037] Specifically, during the halo optimization process of the display device, the first brightness value and the second brightness value of each proportion of the white field image are first obtained through a brightness measuring instrument. These data are the basis for determining whether halo exists and the optimization range.

[0038] The system then enters the brightness comparison phase, determining the relative magnitude of the first brightness value against each of the second brightness values. The core logic behind this comparison is that the first brightness value represents the background brightness of the display device when the screen is completely black. If the second brightness value is greater than the first brightness value, it indicates that light from the white screen has diffused into the dark edge areas, forming a halo that exceeds the base light leakage. In this case, the subarea corresponding to the second brightness value needs to be optimized. If the second brightness value is equal to or less than the first brightness value, it indicates that no additional halo is generated in that area, and no optimization adjustment is required. Therefore, when it is determined that a second brightness value is greater than the first brightness value, the preset optimization model begins to optimize and adjust the partition corresponding to the second brightness value.

[0039] Specifically, the optimization model first locates the backlight subarea covered by the white image corresponding to the second brightness value. Based on the optimization model's built-in algorithm and the subarea's location characteristics (such as whether it directly corresponds to the edge of the white image), it calculates specific brightness adjustment parameters. For subareas directly causing haloing, the model generates parameters to reduce their backlight output, reducing the amount of light diffused into dark areas. For adjacent, related subareas, the brightness is fine-tuned to ensure a natural transition and avoid new brightness gaps after optimization. Alternatively, the algorithm can adjust and optimize the current of the subarea corresponding to the second brightness value. This targeted adjustment can suppress the scope of haloing while maintaining the normal display quality of the white image. Ultimately, it achieves precise optimization of subarea haloing in scenes with different white image ratios, improving the image contrast and clarity of the display device.

[0040] In one embodiment, if Figure 3 As shown, the second brightness value includes an upper brightness value, a lower brightness value, a left brightness value, and a right brightness value, and step S20 further includes steps S23-S25.

[0041] S23, obtaining an average of the upper brightness value, the lower brightness value, the left brightness value, and the right brightness value; S24, determining the size of the mean value and the first brightness value; S25. If the mean value is greater than the first brightness value, the optimization model performs halo optimization on the partition corresponding to the second brightness value.

[0042] Specifically, the second brightness value refers to the brightness value at the edge of a white screen (white area occupying a certain proportion of the screen) of different proportions. The second brightness value includes the upper brightness value (the brightness value outside the upper edge of the white screen), the lower brightness value (the brightness value outside the lower edge of the white screen), the left brightness value (the brightness value outside the left edge of the white screen), and the right brightness value (the brightness value outside the right edge of the white screen). The upper brightness value, the lower brightness value, the left brightness value, and the right brightness value are used to reflect the halo conditions of each edge under white screens of different proportions. The mean value refers to the average of the upper brightness value, the lower brightness value, the left brightness value, and the right brightness value, and the mean value reflects the obviousness of the halo of the white screen under the proportion.

[0043] After obtaining the upper, lower, left, and right luminance values ​​corresponding to a white image at a certain ratio, an average of the upper, lower, left, and right luminance values ​​is calculated. Specifically, the average of the luminance values ​​in the upper, lower, left, and right directions of the white image is calculated. The average is then compared with the first luminance value.

[0044] If the mean value is greater than the first brightness value, it means that the degree of diffusion of light from the white field image to the surrounding dark areas exceeds the basic light leakage of the device, and there is an obvious halo phenomenon. At this time, the preset optimization model will start halo optimization of the partition corresponding to the second brightness value. The optimization model first identifies the backlight zones associated with the white field corresponding to the mean value and analyzes the impact of each zone on edge haloing. Based on the location and light spillage of each zone, the model generates corresponding adjustment parameters to precisely control the brightness of the relevant zones. For example, the model reduces the brightness of zones that cause the most haloing to reduce the spread of light into dark areas, effectively optimizing haloing and improving the display's image quality.

[0045] Therefore, in this embodiment, the average values ​​of the four directions under white field images of different proportions are obtained to reflect the degree of halo obviousness of white field images of different proportions, and then the halo of white field images of different proportions is accurately optimized according to the optimization model to improve the picture effect of the display device.

[0046] In one embodiment, if Figure 4 As shown, after step S20, steps S31-S32 are also included.

[0047] S31, obtaining a third brightness value at an edge of a white field image under different proportions of the optimized display device; S32: If the third brightness value is greater than the first brightness value, further perform halo optimization on the partitions of the display device under white field images with different proportions according to the third brightness value, the preset brightness value, and the optimization model.

[0048] Specifically, the third brightness value is the brightness measurement at the edge of the white field image with the same proportion after each halo optimization of the display device, which is used to evaluate the optimization effect. The preset brightness value is a pre-set acceptable halo brightness threshold, which is a subjectively set appropriate value, usually slightly higher than the first brightness value. The preset brightness value can be used to determine whether the third brightness value is acceptable.

[0049] In the halo optimization process of the display device, first, the halo optimization of the partition is completed according to the first brightness value, the second brightness value and the preset optimization model to reduce the halo range and obviousness of the edge of the white field picture.

[0050] However, after optimization, a brightness measurement instrument is required to obtain the optimized third brightness value. This value corresponds to the brightness of the edge area of ​​the white field image at different ratios. The third brightness value and the second brightness value are measured at the same location to ensure comparability of the previous and subsequent data. After obtaining the third brightness value, it is compared with the first brightness value to determine the effect of the optimization and whether further optimization is needed.

[0051] If the third brightness value is less than or equal to the first brightness value, it indicates that the halo has been effectively controlled and the basic optimization goal has been achieved, and no further optimization steps are required.

[0052] If the third brightness value is still greater than the first brightness value, it indicates that the halo has not been completely eliminated and further optimization process needs to be initiated.

[0053] When entering the further optimization phase, the system will input the third brightness value and the preset brightness value into the preset optimization model. The preset brightness value serves as the optimization target reference, providing the model with a clear upper limit for brightness control. The optimization model will first analyze the magnitude of the third brightness value and the preset brightness value, and then calculate more refined partition adjustment parameters based on the distribution characteristics of the partitions corresponding to different white field ratios. For areas with a large difference between the third brightness value and the preset brightness value, the model will increase the backlight suppression strength of the corresponding partition; for areas close to the preset brightness value, fine-tuning will be performed to avoid over-optimization and loss of image brightness.

[0054] Therefore, in this embodiment, through this feedback-based iterative optimization mechanism, the brightness of the edge of the white field image is gradually controlled within a preset range, and finally the deep optimization of the halo is achieved with high optimization accuracy, further improving the image purity and contrast of the display device, thereby improving the image quality of the display device.

[0055] In one embodiment, if Figure 5 As shown, step S32 also includes steps S321-S322.

[0056] S321, determining the difference between the third brightness value and the preset brightness value; S322: If the third brightness value is greater than the preset brightness value, the optimization model performs halo optimization on the partition corresponding to the second brightness value.

[0057] Specifically, after optimizing the zone halo, it is necessary to determine the effect of the optimization and whether further optimization is needed. Therefore, after obtaining the third brightness value, first determine its magnitude relative to the first brightness value. If the third brightness value is still greater than the first brightness value, it means that the previous optimization failed to completely eliminate the halo that exceeds the basic light leakage, and further optimization is required.

[0058] The key to further optimization is determining the relationship between the third brightness value and the preset brightness value. The preset brightness value serves as a critical value for determining whether haloing is acceptable. Its setting takes into account the balance between display quality and device performance—ensuring the purity of dark areas while avoiding brightness loss in bright areas due to over-optimization. If the third brightness value is less than or equal to the preset brightness value, it indicates that haloing is within an acceptable range and no further adjustment is required. If the third brightness value is greater than the preset brightness value, haloing is still noticeable and requires secondary optimization using the preset optimization model.

[0059] Since the measurement location of the third brightness value and the measurement location of the second brightness value are the same, at this time, the optimization model will call the partition information corresponding to the second brightness value recorded during the last optimization, analyze the brightness control residuals of these partitions after the last optimization, and combine the difference between the third brightness value and the preset brightness value to generate more refined partition adjustment parameters.

[0060] Therefore, in this embodiment, by enhancing the backlight suppression strength of the key partitions, the halo diffusion at the edge of the white field image is further reduced, so that the third brightness value gradually approaches the preset brightness value, and finally achieves the expected halo optimization effect, thereby improving the picture contrast and visual experience of the display device.

[0061] In one embodiment, if Figure 6 As shown, step S20 also includes steps S26-S27.

[0062] S26, reducing the brightness and current of the partition corresponding to the second brightness value by the optimization model; S27, and / or, the optimization model reduces the aperture diffusion range of the partition corresponding to the second brightness value.

[0063] Specifically, during the halo optimization process for a display device, if it is determined that the display device exhibits large and noticeable haloing under white images of varying proportions, optimization operations are performed on the subareas corresponding to the second brightness value according to the preset optimization model. These subareas are typically backlight units directly corresponding to the edges of the white image, where light overflow is the primary cause of haloing. Therefore, these subareas are the target for optimization.

[0064] The first optimization method employed by the optimization model is to reduce the brightness and current of the sub-area to be optimized. Based on the second and first brightness values, the model calculates a reasonable brightness reduction and adjusts the current driving that sub-area accordingly. Because current and brightness are positively correlated, reducing current directly reduces the backlight unit's luminous intensity, thereby reducing light diffusion into surrounding dark areas and reducing halo intensity at the edges of the white field.

[0065] Another optimization approach is to reduce the aperture diffusion range of the subarea corresponding to the second brightness value. The model adjusts the optical structure control parameters of the subarea (such as microlens angle and shading component position) to focus light more closely on the target display area and reduce scattering toward dark areas at the edges. This approach doesn't directly reduce subarea brightness. Instead, it constrains the light propagation path, minimizing the halo's diffusion area while maintaining white image brightness, resulting in a clearer boundary between bright and dark areas.

[0066] These two optimization methods can be used separately or in combination, depending on the cause of the halo. If the halo is mainly caused by excessive brightness, the priority is to reduce the brightness and current. If the halo is caused by excessive light scattering angles, the focus is on reducing the aperture diffusion range.

[0067] Therefore, in this embodiment, the optimization model is used to perform targeted partition halo adjustment on the halo of white field images of different proportions, which can not only effectively suppress the halo, but also maintain the normal brightness and detail performance of the display image, and ultimately improve the image contrast and visual experience of the display device.

[0068] This application optimizes the partitioned halo of the display device with different proportions of white field images based on the first brightness value of the display device under a completely black screen and the second brightness value of the white field images with different proportions through the preset optimization model. The optimization accuracy is high and the picture quality of the display device can be effectively improved.

[0069] Figure 7 FIG. 3 is a schematic block diagram of a halo optimization device 300 for a display device provided by an embodiment of the present invention. Figure 7 As shown, corresponding to the halo optimization method of the display device above, the present invention also provides a halo optimization device 300 for a display device. The halo optimization device 300 for a display device includes a unit for executing the halo optimization method of the display device above, and the device can be configured in a computer device. Specifically, please refer to Figure 7 The halo optimization device 300 of the display device includes an acquisition unit 301 and an optimization unit 302.

[0070] An acquisition unit 301 acquires a first brightness value of a display device under a completely black screen, and respectively acquires second brightness values ​​at the edges around the white screen of the display device under white screens of different proportions; acquires an average of the upper brightness value, the lower brightness value, the left brightness value, and the right brightness value; and acquires a third brightness value at the edges around the white screen of the optimized display device under white screens of different proportions; the proportion of the white screen includes each of the white screens ranging from 5% to 70% relative to the screen of the display device.

[0071] The optimization unit 302 performs halo optimization on the partitions of the display device under white field images with different proportions according to the first brightness value, the second brightness value and a preset optimization model; if the second brightness value is greater than the first brightness value, the optimization model performs halo optimization on the partition corresponding to the second brightness value; if the mean is greater than the first brightness value, the optimization model performs halo optimization on the partition corresponding to the second brightness value; if the third brightness value is greater than the first brightness value, the partitions of the display device under white field images with different proportions are further optimized according to the third brightness value, the preset brightness value and the optimization model; if the third brightness value is greater than the preset brightness value, the optimization model performs halo optimization on the partition corresponding to the second brightness value; the optimization model reduces the brightness and current of the partition corresponding to the second brightness value; and / or the optimization model reduces the aperture diffusion range of the partition corresponding to the second brightness value.

[0072] In one embodiment, the optimization unit 302 further includes a judgment unit.

[0073] The judgment unit is configured to judge the size of the first brightness value and each of the second brightness values ​​respectively; judge the size of the average value and the first brightness value; and judge the size of the third brightness value and the preset brightness value.

[0074] It should be noted that those skilled in the art can clearly understand that the specific implementation process of the halo optimization device and each unit of the above-mentioned display device can refer to the corresponding description in the aforementioned method embodiment. For the convenience and brevity of the description, it will not be repeated here.

[0075] The halo optimization device 300 of the display device can be implemented in the form of a computer program. The computer program can be used in Figure 8 Runs on the computer device shown.

[0076] See also Figure 8 , Figure 8 This is a schematic block diagram of a computer device provided in an embodiment of the present application. The computer device 500 can be a terminal or a server. The terminal can be a smart phone, tablet computer, laptop computer, desktop computer, personal digital assistant, wearable device, or other electronic device with communication capabilities. The server can be a standalone server or a server cluster consisting of multiple servers.

[0077] See Figure 8 The computer device 500 includes a processor 502 , a memory, and a network interface 505 connected via a system bus 501 , wherein the memory may include a non-volatile storage medium 503 and an internal memory 504 .

[0078] The non-volatile storage medium 503 can store an operating system 5031 and a computer program 5032. The computer program 5032 includes program instructions, which, when executed, can enable the processor 502 to execute a halo optimization method for a display device.

[0079] The processor 502 is used to provide computing and control capabilities to support the operation of the entire computer device 500.

[0080] The internal memory 504 provides an environment for the operation of the computer program 5032 in the non-volatile storage medium 503 . When the computer program 5032 is executed by the processor 502 , the processor 502 can execute a halo optimization method for a display device.

[0081] The network interface 505 is used to communicate with other devices through the network. Figure 8 The structure shown in the figure is merely a block diagram of a portion of the structure related to the solution of the present application, and does not constitute a limitation on the computer device 500 to which the solution of the present application is applied. The specific computer device 500 may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0082] The processor 502 is configured to run a computer program 5032 stored in a memory to implement the steps of the halo optimization method for the display device.

[0083] It should be understood that in the embodiment of the present application, the processor 502 may be a central processing unit (CPU), and the processor 502 may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc.

[0084] Those skilled in the art will appreciate that all or part of the steps in the method of the above-described embodiment can be implemented by instructing the relevant hardware through a computer program. The computer program includes program instructions, which can be stored in a storage medium that is computer-readable. The program instructions are executed by at least one processor in the computer system to implement the steps in the method of the above-described embodiment.

[0085] Therefore, the present invention also provides a storage medium. The storage medium may be a computer-readable storage medium. The storage medium stores a computer program, wherein the computer program includes program instructions. When executed by a processor, the program instructions cause the processor to perform the steps of the halo optimization method for a display device.

[0086] The storage medium may be any computer-readable storage medium that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a magnetic disk, or an optical disk.

[0087] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the above description has generally described the composition and steps of each example according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0088] In the several embodiments provided herein, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the various units is merely a logical functional division, and actual implementation may employ other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be omitted or not implemented.

[0089] The steps in the methods of the embodiments of the present invention may be adjusted in order, combined, or deleted as needed. The units in the devices of the embodiments of the present invention may be combined, divided, or deleted as needed. Furthermore, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit.

[0090] If this integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product, stored in a storage medium, includes instructions for enabling a computer device (such as a personal computer, terminal, or network device) to execute all or part of the steps of the method described in various embodiments of the present invention.

[0091] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and such modifications or substitutions are intended to be within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be subject to the scope of protection of the claims.

Claims

1. A halo optimization method for a display device, characterized in that: The method comprises: Obtaining a first brightness value of the display device under a completely black screen, and respectively obtaining second brightness values ​​of the display device at edges around the white screen under white screens of different proportions; Halo optimization is performed on partitions of the display device under white field images with different proportions according to the first brightness value, the second brightness value and a preset optimization model.

2. The method according to claim 1, characterized in that The step of performing halo optimization on partitions of the display device under white field images with different proportions according to the first brightness value, the second brightness value, and a preset optimization model includes: respectively determining the magnitude of the first brightness value and each of the second brightness values; If the second brightness value is greater than the first brightness value, the optimization model performs halo optimization on the partition corresponding to the second brightness value.

3. The method according to claim 1, characterized in that The second brightness value includes an upper brightness value, a lower brightness value, a left brightness value, and a right brightness value; and the step of performing halo optimization on partitions of the display device under white field images with different proportions according to the first brightness value, the second brightness value, and a preset optimization model includes: Obtaining an average of the upper brightness value, the lower brightness value, the left brightness value, and the right brightness value; Determining the size of the mean value and the first brightness value; If the mean value is greater than the first brightness value, the optimization model performs halo optimization on the partition corresponding to the second brightness value.

4. The method according to claim 1, wherein After the step of performing halo optimization on partitions of the display device under white field images with different proportions according to the first brightness value, the second brightness value and a preset optimization model, the method includes: Obtaining a third brightness value at an edge of a white field image under different proportions of the optimized display device; If the third brightness value is greater than the first brightness value, halo optimization is further performed on the partitions of the display device under white field images with different proportions according to the third brightness value, the preset brightness value and the optimization model.

5. The method according to claim 4, characterized in that If the third brightness value is greater than the first brightness value, the step of further performing halo optimization on partitions of the display device under white field images with different proportions according to the third brightness value, the preset brightness value, and the optimization model includes: Determining the magnitude between the third brightness value and the preset brightness value; If the third brightness value is greater than the preset brightness value, the optimization model performs halo optimization on the partition corresponding to the second brightness value.

6. The method according to any one of claims 1 to 5, characterized in that The step of performing halo optimization on partitions of the display device under white field images with different proportions according to the first brightness value, the second brightness value, and a preset optimization model includes: The optimization model reduces the brightness and current of the partition corresponding to the second brightness value; And / or, the optimization model reduces the aperture diffusion range of the partition corresponding to the second brightness value.

7. The method according to claim 1, characterized in that The step of respectively obtaining second brightness values ​​at edges around the white field image of the display device under white field images of different proportions includes: The proportion of the white screen includes 5% to 70% of each of the white screens relative to the screen of the display device.

8. A halo optimization device for a display device, characterized in that: The method comprises a unit for executing the method according to any one of claims 1 to 7.

9. A computer device, characterized in that: The computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the method according to any one of claims 1 to 7 when executing the computer program.

10. A storage medium, characterized in that: The storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a processor, the method according to any one of claims 1 to 7 can be implemented.

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