Brightness and darkness adjusting method and system for mobile phone display screen

Abstract

The invention belongs to the field of display screens, and provides a brightness adjusting method and system for a mobile phone display screen, and the method comprises the steps: carrying out the preprocessing of an input LDR video frame through a fast guide filter, and removing the noise and artifacts generated by compression or a sensor; expanding the brightness range of the input LDR video frame based on the global operator of the medium gray value mapping; while diffusing the brightness range of the LDR video frame, iteratively removing a false contour in a smooth transition region in the LDR video frame through a minimization algorithm based on iterative projection to a convex set; analyzing an artifact-free LDR video frame and a brightness channel thereof to detect highlight and generate an expansion graph, analyzing the expansion graph and marking a highlight area, and fusing original brightness details by adopting a guide filter; redistributing the brightness of the LDR video frame after brightness expansion to an RGB color channel by adopting a Mantiuk formula; according to the invention, a good display effect can be realized when LDR is converted into HDR.

Description

Technical Field

[0001] The present invention relates to the field of display screens, and in particular to a method and system for adjusting the brightness of a mobile phone display screen. Background Art

[0002] The development of high dynamic range (HDR) display technology has significantly increased the contrast and peak brightness of displays, and HDR technology is able to capture and display a wide range of brightness values, from the deepest shadows to the brightest highlights. In the coming years, HDR displays that can provide higher brightness and contrast than today's models are expected to become increasingly popular, especially on mobile devices such as mobile phone displays. Although HDR technology has developed rapidly in the past few years, low dynamic range (LDR) content is still popular because a large amount of video content is currently recorded and stored in LDR form. In addition, while the HDR standard supports multimedia content with brightness levels up to 10,000cd / m2 (a standard measure of brightness), the maximum brightness of most HDR content is generally limited to around 1000 cd / m2. This limit is consistent with the current capabilities of consumer-grade HDR displays, but the brightness is about five times that of current LDR. In order to accurately present LDR content on HDR displays, it needs to be processed through a dynamic range extension process called inverse tone mapping (iTM). This LDR-to-HDR conversion faces many challenges, including noise artifacts, false contours, loss of detail, color desaturation, and temporal inconsistencies. In particular, the conversion adjustment methods of the prior art cannot adapt to different displays and the display effect is poor. For example, it is easy to lack details in underexposed / overexposed areas, and when capturing scenes in LDR, areas with extremely bright or extremely dark elements cannot be fully presented, resulting in the loss of complex details. This problem stems from two different reasons: the technical limitations of camera sensors in capturing full-spectrum brightness values, and intentional artistic grading choices designed to suppress certain parts of the dynamic range for aesthetic purposes. For example, in high-contrast scenes, details in very bright areas (overexposed) or very dark areas (underexposed) may not be fully captured due to the dynamic range limitations of the sensor. At the same time, during the grading process, these details are deliberately enhanced or reduced to be consistent with artistic vision within the constraints of the limited dynamic range. The inverse tone mapping methods of the prior art have difficulty in reconstructing the lost details in these areas, such as subtle textures, dark gradients, or high brightness details that are not captured in the original LDR image, and the dark and bright display effects are poor. Summary of the invention

[0003] In view of the above technical problems, the present invention provides a method and system for adjusting the brightness of a mobile phone display screen to achieve a good display effect when converting LDR to HDR.

[0004] Other features and advantages of the present invention will become apparent from the following detailed description, or may be learned in part by practice of the present invention.

[0005] According to one aspect of the present invention, a method for adjusting brightness of a mobile phone display screen is disclosed, the method comprising: Preprocessing the input LDR video frame by a fast guided filter to remove noise and artifacts caused by compression or sensor while preserving edge details, wherein the parameters of the fast guided filter include a local window radius, a regularization parameter, and a subsampling rate to manage smoothness and improve filtering efficiency; Expanding the brightness range of the input LDR video frame based on a global operator of mid-grey value mapping, specifically comprising: automatically calculating a mid-grey value output parameter, using the statistical characteristics of the geometric mean brightness, contrast and percentage of overexposed pixels of the LDR video frame, and determining it through multi-linear regression; using a weighted average method to adjust the mid-grey value output parameter to reduce the brightness variation between frames to suppress flicker artifacts; While diffusing the brightness range of the LDR video frame, iteratively removing false contours in smooth transition areas within the LDR video frame by a minimization algorithm based on iterative projection to a convex set; Analyzing the artifact-free LDR video frame and its brightness channel to detect highlights and generate an extended map, analyzing the extended map and marking highlight areas, and using a guided filter to fuse original brightness details to enhance peak brightness of the highlight areas; The Mantiuk formula is used to redistribute the brightness of the LDR video frame after brightness expansion to the RGB color channels to achieve the conversion of the LDR video to the HDR video frame, and the color loss in the HDR conversion process is compensated by setting the saturation enhancement parameter.

[0006] Furthermore, the expansion function based on the middle gray value mapping is expressed as: ; in and Represents at a given pixel The brightness of the filtered LDR video frame and the output HDR video frame, , yes The maximum brightness value in .

[0007] Furthermore, It is determined based on the expected peak brightness of the output HDR video frame or the peak brightness capability of the HDR display screen.

[0008] Furthermore, when the brightness is expanded by using the extended function of the middle gray value mapping, the following two conditions are defined: For any value , ; ; Substitute the condition into the expansion function of the mid-grey value map to solve the condition: ; ; The solution for parameters b and c is: ; ; The condition is ; Among them, parameter a defines the lower end of the curve of the expansion function of the middle gray value mapping, affecting the output contrast, parameter d defines the upper shape of the curve, affecting the expansion of the highlight, and parameter For the defined mid-gray value input, the parameter is the expected mid-gray value output, and Defines the anchor point of the curve.

[0009] Furthermore, the parameters is calculated using basic features derived from the filtered LDR video frame, including geometric mean, contrast, and the percentage of overexposed pixels in the filtered LDR video frame.

[0010] Furthermore, when removing the false contours of the LDR video frame, the key parameters used are: the difference between two consecutive pixels in the smoothing area, the radius of the average filter, and the number of iterations.

[0011] Furthermore, when detecting the highlight of the LDR video frame and generating an extended image, it includes: A binary map is created by selecting pixels identified as highlights from the artifact-free LDR video frame, in which a pixel value is set to 1 if it is determined to be a highlight and to 0 if it is not.

[0012] Furthermore, when determining whether a pixel is a highlight, the judgment conditions include: Pixels with brightness values ​​greater than 222; Pixels whose RGB channel values ​​exceed 230.

[0013] Furthermore, the Mantiuk formula is expressed as: ; in, and They are the HDR extended brightness obtained during highlight enhancement and the LDR video frame after filtering. The brightness at is the LDR video frame after filtering The color component at is the color component of the output HDR video frame, is the color channel and s is the color saturation parameter.

[0014] According to another aspect of the present invention, a brightness adjustment system for a mobile phone display screen is disclosed, the system comprising: An artifact suppression module, the artifact suppression module is used to pre-process the input LDR video frame through a fast guided filter to remove noise and artifacts caused by compression or sensor while retaining edge details, wherein the parameters of the fast guided filter include a local window radius, a regularization parameter and a subsampling rate to manage smoothness and improve filtering efficiency; A dynamic range extension module, the dynamic range extension module is used to expand the brightness range of the input LDR video frame based on the global operator of the mid-grey value mapping, specifically including: automatically calculating the mid-grey value output parameter, using the statistical characteristics of the geometric mean brightness, contrast and overexposed pixel percentage of the LDR video frame, and determining it through multi-linear regression; using the weighted average method to adjust the mid-grey value output parameter to reduce the brightness variation between frames to suppress flicker artifacts; A dequantization module, the dequantization module is used to iteratively remove false contours in a smooth transition area in the LDR video frame by a minimization algorithm based on iterative projection to a convex set while diffusing the brightness range of the LDR video frame; A brightness enhancement module, the brightness enhancement module is used to analyze the artifact-free LDR video frame and its brightness channel to detect highlights and generate an extended map, analyze the extended map and mark the highlight area, and use a guided filter to fuse the original brightness details to enhance the peak brightness of the highlight area; The saturation enhancement module is used to redistribute the brightness of the LDR video frame after brightness expansion to the RGB color channels using the Mantiuk formula to achieve the conversion of the LDR video to the HDR video frame, and at the same time compensate for the color loss in the HDR conversion process by setting the saturation enhancement parameters.

[0015] The technical solution of the present invention has the following beneficial effects: A comprehensive LDR to HDR conversion method is provided for LDR video frames, which can adapt to the peak brightness of different displays and create HDR video frame sequences with high peak brightness capabilities; it can detect and enhance highlights in HDR videos while staying within the parameter limits of mobile phone displays; it can significantly improve the overall brightness of existing HDR content obtained by displays at lower brightness levels, thereby significantly improving visual quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a flow chart of a method for adjusting the brightness of a mobile phone display screen in an embodiment of this specification; Figure 2 This is a structural block diagram of a brightness adjustment system for a mobile phone display screen in an embodiment of this specification. DETAILED DESCRIPTION

[0017] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as being limited to the examples set forth herein; on the contrary, these embodiments are provided so that the present invention will be more comprehensive and complete, and the concept of the example embodiments will be fully conveyed to those skilled in the art. The described features, structures, or characteristics may be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present invention. However, those skilled in the art will appreciate that the technical solutions of the present invention may be practiced while omitting one or more of the specific details, or other methods, components, devices, steps, etc. may be adopted. In other cases, known technical solutions are not shown or described in detail to avoid obscuring various aspects of the present invention.

[0018] In addition, the accompanying drawings are only schematic illustrations of the present invention. The same reference numerals in the figures represent the same or similar parts, and thus their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities, which do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0019] In one embodiment, if Figure 1 As shown, this specification provides a method for adjusting the brightness of a mobile phone display screen, and the execution subject of the method can be a computer, a server, a tablet computer, a mobile phone, etc. The method can specifically include the following steps S101~S104: In step S101, the input LDR video frame is preprocessed by a fast guided filter to remove noise and artifacts caused by compression or sensor while retaining edge details, wherein the parameters of the fast guided filter include local window radius, regularization parameter and subsampling rate to manage smoothness and improve filtering efficiency.

[0020] Among them, LDR video frames inherently contain noise and artifacts, a feature that is often ignored when the display brightness and dynamic range are limited. Artifacts mostly originate from compression algorithms and some from the camera sensor at the time of original acquisition, which sacrifices artifacts at a lower dynamic range in order to reduce data size. Therefore, it is very important to filter the LDR video frames to reduce these artifacts and noise before expanding the dynamic range, which can prevent the artifacts from being aggravated during the dynamic range enhancement process. Specifically, a time-efficient implementation of guided filters can be used, especially fast guided filters. Guided filters have strong edge-aware image filtering capabilities and can remove or reduce noise and artifacts while preserving subtle details and textures in the image. Specifically, the edge-preserving smoothing function of the fast guided filter is used to quickly and effectively remove artifacts from the input LDR video frame. The fast guided filter has three parameters for controlling artifact denoising and processing speed. These parameters are as follows: the local window radius, the regularization parameter for managing the degree of smoothing, and the subsampling ratio that can speed up the filtering process. Careful adjustment of the first two parameters can accurately control the strength of the filter and adjust the final appearance of the processed video frame according to the desired specifications.

[0021] In step S102, the brightness range of the input LDR video frame is expanded based on the global operator of the mid-grey value mapping, specifically including: automatically calculating the mid-grey value output parameter, using the statistical characteristics of the geometric mean brightness, contrast and overexposed pixel percentage of the LDR video frame, and determining it through multi-linear regression; using the weighted average method to adjust the mid-grey value output parameter to reduce the brightness variation between frames to suppress flicker artifacts.

[0022] Among them, dynamic range expansion can be a global function. The function is proposed in the context of enhancing visual effects. It effectively maintains the peak brightness while adjusting the middle gray value (i.e., the overall perceived brightness) to a comfortable level. The middle gray value, usually referred to as "middle gray", represents the perceptual midpoint between the extremes of black and white on the brightness scale. The expansion function based on the middle gray value mapping is expressed as: ; in and Represents at a given pixel The brightness of the filtered LDR video frame and the output HDR video frame, , yes The maximum brightness value in. Among them, It is determined based on the expected peak brightness of the output HDR video frame or the peak brightness capability of the HDR display screen.

[0023] When using the expansion function of the middle gray value mapping to expand the brightness, the following two conditions are defined: For any value , ; ; Substitute the condition into the expansion function of the mid-grey value map to solve the condition: ; ; The solution for parameters b and c is: ; ; The condition is ; Among them, parameter a defines the lower end of the curve of the expansion function of the gray value mapping, affecting the contrast of the output, and parameter d defines the upper shape of the curve, affecting the expansion of highlights. Usually, a d value greater than 1 is required in inverse tone mapping to properly stretch highlights. Similarly, a value of a close to 1 keeps shadows, while significantly larger a values ​​(a>>1) are compressed in the output. Specifically, a slightly higher a value can be used to balance between enhancing and preserving shadows in the input LDR video frame and the output HDR video frame. Parameters For the defined mid-gray value input, the parameter is the expected mid-gray value output, and The anchor points of the curve are defined and represent the mid-gray value defined for L and the output The expected mid-gray value in .

[0024] parameter is set to the mid-gray value of the LDR video frame being processed. For example, for an LDR video frame encoded in the sRGB linear color space, the assigned value is 0.214. At the same time, the parameter Determines the mid-grey value of the intended HDR video frame, which essentially controls its overall brightness.

[0025] Medium gray output value It is calculated using basic features derived from the filtered LDR video frame, including geometric mean, contrast, and the percentage of overexposed pixels in the filtered LDR video frame.

[0026] ; is the geometric mean, is the contrast, is the percentage of overexposed pixels in the filtered LDR video frame. A, F, G, and H are constants that can be obtained through a limited number of experiments. Their values ​​affect size.

[0027] in: ; ; ; in is the average brightness value, and the maximum brightness value is the maximum brightness value in the filtered LDR video frame. is the total number of pixels, is a small constant to avoid undefined values, is the total number of overexposed pixels. Overexposed pixels are pixels with at least one color channel greater than or equal to 0.996 = 254 / 255. These values ​​are calculated after excluding 5% of pixels in the dark and bright parts, which are considered outliers.

[0028] The geometric mean, which represents the parameter of the perceived overall brightness of the input image, has the highest positive correlation with the mid-gray value in the output, which emphasizes the impact of perceived brightness on the mid-gray adjustment during the dynamic range extension process. In order to prevent flickering in the inverse tone-mapped HDR video zhen frame sequence due to sudden changes in the estimated mid-gray value between frames, the mid-gray output value used to extend the dynamic range of the current frame is adjusted by a weighted average as follows: ; in Represents the mid-gray output value used to expand the dynamic range of the previous frame, is the mid-gray output value calculated based on experience, is the weight value, which can be used as a "damping factor". Sudden changes in mid-gray output can be suppressed, preventing flickering artifacts in the resulting HDR video frame sequence.

[0029] In step S103, while diffusing the brightness range of the LDR video frame, false contours in the smooth transition area of ​​the LDR video frame are iteratively removed by a minimization algorithm based on iterative projection to a convex set.

[0030] Among them, when removing the false contour of the LDR video frame, the key parameters used are: the difference between two consecutive pixels in the smooth area, the radius of the average filter, and the number of iterations.

[0031] Specifically, step S103 is used to remove "false contours" or "banding artifacts" that are common in smooth transition areas within an LDR video frame. A fast iterative false contour removal method can be used, which regards the false contour removal operation as a signal reconstruction problem, which can be solved using a minimization algorithm based on iterative projection to convex sets (POCS). Among them, the decontouring method works in conjunction with the dynamic range extension function, that is, false contour removal and dynamic range extension are performed simultaneously in an iterative manner until convergence to an acceptable level, i.e., an inverse tone-mapped LDR video frame without visible false contours. Exemplarily, the pixel values ​​are filtered using a low-pass filter (the first operator), and the resulting values ​​are clamped (the second operator) to remain between quantization boundaries. The low-pass filter is a two-dimensional averaging filter.

[0032] The decontouring method is defined by three key parameters: the difference between two consecutive pixels within the smoothing region, the radius of the averaging filter, and the number of iterations. The difference between two consecutive pixels in the image that is perceived as a smooth transition depends on multiple factors, and for a standard 8-bit LDR video frame image, a typical difference threshold ranges from 1 to 5 units. However, this is only exemplary, and the optimal range can be determined by actual debugging.

[0033] In step S104, the artifact-free LDR video frame and its brightness channel are analyzed to detect highlights and generate an extended map, the extended map is analyzed and the highlight area is marked, and a guided filter is used to fuse the original brightness details to enhance the peak brightness of the highlight area.

[0034] The main goal of the highlight enhancement step is to restore the high brightness area to a higher output brightness relative to the mid-gray point within the capabilities of the display system. The highlight enhancement step specifically targets identifying and enhancing highlights, aiming to strengthen them to a higher brightness, by identifying the highlight locations in the current LDR video frame and specifying the degree of enhancement required for each pixel. Specifically, an artifact-free LDR video frame and its luminance channel are first analyzed to detect highlights and generate an expansion map.

[0035] Wherein, when detecting highlights of the LDR video frame and generating an extended map, it includes: creating a binary map by selecting pixels identified as highlights from the LDR video frame without artifacts, in which if a pixel is determined to be a highlight, its pixel value is set to 1, and if not, it is set to 0. Considering that the maximum pixel value of the LDR video frame is 255, the decision to mark a pixel as a highlight is based on the following criteria: Pixels with brightness values ​​greater than 222; a brightness value of 222 is used to detect areas that are considered to be highlight clipping. These areas are caused by the limited dynamic range of LDR video frames, which indicates that the brightness level exceeds the display capabilities and details may be lost; Pixels with RGB channel values ​​exceeding 230. This criterion helps to pinpoint highlights characterized by color saturation. Using this threshold helps to identify pixels associated with specular highlights and light sources that exhibit color saturation.

[0036] In order to compute the expansion map, we specifically exploit the structure transfer filtering property of the fast guided filter, i.e. its ability to transfer structural information from the guidance image to the target image. The binary map representing the highlights is filtered using the LDR brightness extracted from the artifact-free input LDR video frame as the guidance image, ensuring that the details and subtle gradients present in the original LDR brightness are effectively incorporated into the binary map, enhancing its accuracy and details.

[0037] In step S105, the brightness of the LDR video frame after brightness expansion is redistributed to the RGB color channels using the Mantiuk formula to achieve conversion of the LDR video to the HDR video frame, and the color loss in the HDR conversion process is compensated by setting the saturation enhancement parameter.

[0038] The Mantiuk formula is expressed as: ; in, and They are the HDR extended brightness obtained during highlight enhancement and the LDR video frame after filtering. The brightness at is the LDR video frame after filtering The color component at is the color component of the output HDR video frame, is the color channel and s is the color saturation parameter which should be set to a value greater than 1 to increase the color saturation in the output HDR video frame.

[0039] Based on the same idea, Figure 2 As shown, an exemplary embodiment of the present invention further provides a brightness adjustment system for a mobile phone display screen, the system comprising: An artifact suppression module 201 is used to pre-process the input LDR video frame by a fast guided filter to remove noise and artifacts caused by compression or sensor while retaining edge details, wherein the parameters of the fast guided filter include a local window radius, a regularization parameter and a subsampling rate to manage smoothness and improve filtering efficiency; A dynamic range extension module 202, the dynamic range extension module 202 is used to expand the brightness range of the input LDR video frame based on the global operator of the mid-grey value mapping, specifically including: automatically calculating the mid-grey value output parameter, using the statistical characteristics of the geometric mean brightness, contrast and overexposed pixel percentage of the LDR video frame, and determining it through multi-linear regression; using a weighted average method to adjust the mid-grey value output parameter to reduce the brightness variation between frames to suppress flicker artifacts; A dequantization module 203, the dequantization module 203 is used to iteratively remove false contours in a smooth transition area in the LDR video frame by a minimization algorithm based on iterative projection to a convex set while diffusing the brightness range of the LDR video frame; A brightness enhancement module 204, the brightness enhancement module 204 is used to analyze the artifact-free LDR video frame and its brightness channel to detect highlights and generate an extended map, analyze the extended map and mark the highlight area, and use a guided filter to fuse the original brightness details to enhance the peak brightness of the highlight area; The saturation enhancement module 205 is used to use the Mantiuk formula to redistribute the brightness of the LDR video frame after brightness expansion to the RGB color channels to achieve the conversion of the LDR video to the HDR video frame, and at the same time compensate for the color loss in the HDR conversion process by setting the saturation enhancement parameters.

[0040] In the above embodiments, a comprehensive LDR to HDR conversion method is provided for LDR video frames, which can adapt to the peak brightness of different display screens and create HDR video frame sequences with high peak brightness capabilities; it can detect and enhance highlights in HDR videos while remaining within the parameter limits of the mobile phone display screen; it can significantly improve the overall brightness of existing HDR content acquired by a display screen at a lower brightness level, thereby significantly improving the visual quality.

[0041] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to perform a method according to an exemplary implementation of the present invention.

[0042] In addition, the above-mentioned figures are only schematic illustrations of the processes included in the method according to an exemplary embodiment of the present invention, and are not intended to be limiting. It is easy to understand that the processes shown in the above-mentioned figures do not indicate or limit the time sequence of these processes. In addition, it is also easy to understand that these processes can be performed synchronously or asynchronously, for example, in multiple modules.

[0043] Those skilled in the art will readily appreciate other embodiments of the invention after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art that are not disclosed in the present invention. The specification and embodiments are to be considered exemplary only, and the true scope and spirit of the invention are indicated by the claims.

Claims

1. A method for adjusting the brightness of a mobile phone display screen, characterized in that: The method comprises: Preprocessing the input LDR video frame by a fast guided filter to remove noise and artifacts caused by compression or sensor while preserving edge details, wherein the parameters of the fast guided filter include a local window radius, a regularization parameter, and a subsampling rate to manage smoothness and improve filtering efficiency; Expanding the brightness range of the input LDR video frame based on a global operator of mid-grey value mapping, specifically comprising: automatically calculating a mid-grey value output parameter, using the statistical characteristics of the geometric mean brightness, contrast and percentage of overexposed pixels of the LDR video frame, and determining it through multi-linear regression; using a weighted average method to adjust the mid-grey value output parameter to reduce the brightness variation between frames to suppress flicker artifacts; While diffusing the brightness range of the LDR video frame, iteratively removing false contours in smooth transition areas within the LDR video frame by a minimization algorithm based on iterative projection to a convex set; Analyzing the artifact-free LDR video frame and its brightness channel to detect highlights and generate an extended map, analyzing the extended map and marking highlight areas, and using a guided filter to fuse original brightness details to enhance peak brightness of the highlight areas; The Mantiuk formula is used to redistribute the brightness of the LDR video frame after brightness expansion to the RGB color channels to achieve the conversion of the LDR video to the HDR video frame, and the color loss in the HDR conversion process is compensated by setting the saturation enhancement parameter.

2. A method for adjusting brightness of a mobile phone display screen according to claim 1, characterized in that: The expansion function based on the middle gray value mapping is expressed as: ； in and Represents at a given pixel The brightness of the filtered LDR video frame and the output HDR video frame, , yes The maximum brightness value in .

3. A method for adjusting brightness of a mobile phone display screen according to claim 2, characterized in that: It is determined based on the expected peak brightness of the output HDR video frame or the peak brightness capability of the HDR display screen.

4. A method for adjusting brightness of a mobile phone display screen according to claim 2, characterized in that: When using the expansion function of the middle gray value mapping to expand the brightness, the following two conditions are defined: For any value , ; ； Substitute the condition into the expansion function of the mid-grey value map to solve the condition: ； ； The solution for parameters b and c is: ； ； The condition is ; Among them, parameter a defines the lower end of the curve of the expansion function of the middle gray value mapping, affecting the output contrast, parameter d defines the upper shape of the curve, affecting the expansion of the highlight, and parameter For the defined mid-gray value input, the parameter is the expected mid-gray value output, and Defines the anchor point of the curve.

5. A method for adjusting brightness of a mobile phone display screen according to claim 4, characterized in that: parameter is calculated using basic features derived from the filtered LDR video frame, including geometric mean, contrast, and the percentage of overexposed pixels in the filtered LDR video frame.

6. A method for adjusting brightness of a mobile phone display screen according to claim 1, characterized in that: When removing the false contours of the LDR video frame, the key parameters used are: the difference between two consecutive pixels in the smoothing area, the radius of the average filter, and the number of iterations.

7. A method for adjusting brightness of a mobile phone display screen according to claim 1, characterized in that: When detecting the highlight of the LDR video frame and generating an extended image, it includes: A binary map is created by selecting pixels identified as highlights from the artifact-free LDR video frame, in which a pixel value is set to 1 if it is determined to be a highlight and to 0 if it is not.

8. A method for adjusting brightness of a mobile phone display screen according to claim 7, characterized in that: When determining whether a pixel is a highlight, the judgment conditions include: Pixels with brightness values ​​greater than 222; Pixels whose RGB channel values ​​exceed 230.

9. The method for adjusting brightness of a mobile phone display screen according to claim 1, characterized in that: The Mantiuk formula is expressed as: ； in, and They are the HDR extended brightness obtained during highlight enhancement and the LDR video frame after filtering. The brightness at is the LDR video frame after filtering The color component at is the color component of the output HDR video frame, is the color channel and s is the color saturation parameter.

10. A brightness adjustment system for a mobile phone display screen, characterized in that: The system comprises: An artifact suppression module, the artifact suppression module is used to pre-process the input LDR video frame through a fast guided filter to remove noise and artifacts caused by compression or sensor while retaining edge details, wherein the parameters of the fast guided filter include a local window radius, a regularization parameter and a subsampling rate to manage smoothness and improve filtering efficiency; A dynamic range extension module, the dynamic range extension module is used to expand the brightness range of the input LDR video frame based on the global operator of the mid-grey value mapping, specifically including: automatically calculating the mid-grey value output parameter, using the statistical characteristics of the geometric mean brightness, contrast and overexposed pixel percentage of the LDR video frame, and determining it through multi-linear regression; using the weighted average method to adjust the mid-grey value output parameter to reduce the brightness variation between frames to suppress flicker artifacts; A dequantization module, the dequantization module is used to iteratively remove false contours in a smooth transition area in the LDR video frame by a minimization algorithm based on iterative projection to a convex set while diffusing the brightness range of the LDR video frame; A brightness enhancement module, the brightness enhancement module is used to analyze the artifact-free LDR video frame and its brightness channel to detect highlights and generate an extended map, analyze the extended map and mark the highlight area, and use a guided filter to fuse the original brightness details to enhance the peak brightness of the highlight area; The saturation enhancement module is used to redistribute the brightness of the LDR video frame after brightness expansion to the RGB color channels using the Mantiuk formula to achieve the conversion of the LDR video to the HDR video frame, and at the same time compensate for the color loss in the HDR conversion process by setting the saturation enhancement parameters.

Images