A method and system for adjusting brightness and darkness of a mobile phone display screen

Abstract

The application belongs to the field of display screen, and provides a light and dark adjusting method and system for mobile phone display screen, which comprises the following steps: pre-processing input LDR video frames by a fast guided filter to remove noise and artifacts generated by compression or sensors; expanding the brightness range of the input LDR video frames based on a global operator of mid-gray value mapping; while expanding the brightness range of the LDR video frames, iteratively removing false contours in the smooth transition area in the LDR video frames by a minimization algorithm based on iterative projection to a convex set; analyzing the LDR video frames without artifacts and their brightness channels to detect highlights and generate an expansion map, analyzing the expansion map and marking the highlight area, and fusing original brightness details by using a guided filter; and re-distributing the brightness of the LDR video frames after brightness expansion to the RGB color channels by using a Mantiuk formula; the application can realize good display effect when converting LDR to HDR.

Description

Technical Field

[0001] This invention relates to the field of displays, and more particularly to a method and system for adjusting the brightness of a mobile phone display. Background Technology

[0002] The development of High Dynamic Range (HDR) display technology has significantly improved the contrast and peak brightness of displays. HDR technology can capture and display a wide range of brightness values, from the deepest shadows to the brightest highlights. In the coming years, HDR displays, which can provide higher brightness and contrast than current models, are expected to become increasingly popular, especially in mobile devices such as smartphone displays. While HDR technology has developed rapidly in the past few years, Low Dynamic Range (LDR) content remains prevalent because a large amount of video content is currently recorded and stored in LDR format. Furthermore, although the HDR standard supports multimedia content with brightness levels up to 10,000 cd / m² (the standard measure of brightness), most HDR content is typically limited to a maximum brightness of around 1,000 cd / m². This limitation is consistent with the current capabilities of consumer-grade HDR displays, but the brightness is approximately five times that of current LDR. To accurately render 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 outlines, loss of detail, color desaturation, and temporal inconsistencies. In particular, existing conversion and adjustment methods are not adaptable to different displays, resulting in poor display quality. For example, underexposed / overexposed areas often lack detail, and when capturing scenes in LDR, areas with extremely bright or dark elements cannot be fully rendered, leading to 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 the intentional artistic grading selection, which aims to suppress certain parts of the dynamic range for aesthetic purposes. For example, in high-contrast scenes, due to the sensor's dynamic range limitations, it may not be possible to fully capture details in very bright areas (overexposed) or very dark areas (underexposed). Simultaneously, during the grading process, these details are intentionally enhanced or reduced to maintain consistency with artistic vision within the constraints of the limited dynamic range. Existing inverse tone mapping methods struggle to reconstruct the details lost in these areas, such as subtle textures, gradations of darkness, or high-brightness details not captured in the original LDR image, resulting in poor display quality in both bright and dark areas. 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 invention will become apparent from the following detailed description, or may be learned in part by practice of the invention.

[0005] According to one aspect of the present invention, a method for adjusting the brightness of a mobile phone display screen is disclosed, the method comprising:

[0006] The input LDR video frames are preprocessed by a fast guided filter to remove noise and artifacts caused by compression or sensors, while preserving edge details. The parameters of the fast guided filter include local window radius, regularization parameter and subsampling rate to manage smoothness and improve filtering efficiency.

[0007] The global operator based on mid-gray value mapping extends the brightness range of the input LDR video frame, specifically including: automatically calculating the mid-gray 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 multilinear regression; adjusting the mid-gray value output parameter using a weighted average method to reduce inter-frame brightness changes and suppress flicker artifacts.

[0008] While expanding the brightness range of the LDR video frame, false contours in the smooth transition region within the LDR video frame are iteratively removed using a minimization algorithm based on iterative projection to convex set.

[0009] The LDR video frames and their luminance channels without artifacts are analyzed to detect highlights and generate an extended map. The extended map is analyzed and the bright areas are marked. A guided filter is used to fuse the original luminance details to enhance the peak luminance of the bright areas.

[0010] The brightness of the LDR video frame after brightness expansion is redistributed to the RGB color channels using the Mantiuk formula to achieve the conversion of the LDR video to the HDR video frame. At the same time, the color loss during the HDR conversion process is compensated by setting the saturation enhancement parameter.

[0011] Furthermore, the extended function based on the aforementioned gray value mapping is expressed as follows:

[0012] ;

[0013] in and Represents at a given pixel point The brightness of the filtered LDR video frame and the output HDR video frame. , yes The maximum brightness value in the image.

[0014] 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.

[0015] Furthermore, when using the extended function of the grayscale mapping to expand the brightness, the following two conditions are defined:

[0016] For any value , ;

[0017] ;

[0018] Substitute the condition into the extended function of the gray value mapping to solve the condition:

[0019] ;

[0020] ;

[0021] The solutions for parameters b and c are:

[0022] ;

[0023] ;

[0024] The condition is ;

[0025] Wherein, parameter a defines the lower end of the curve of the grayscale mapping extension function, affecting the output contrast; parameter d defines the shape of the upper end of the curve, affecting the extension of highlights; parameter... Input the defined medium grayscale value, parameter To output the expected mid-grayscale value, and The anchor points of the curve are defined.

[0026] Furthermore, parameters It is calculated using basic features derived from the filtered LDR video frames, including geometric mean, contrast, and the percentage of overexposed pixels in the filtered LDR video frames.

[0027] Furthermore, the key parameters used in removing false contours from the LDR video frames are: the difference between two consecutive pixels within the smoothing region, the radius of the average filter, and the number of iterations.

[0028] Furthermore, when detecting the highlights of the LDR video frame and generating the extended map, the process includes:

[0029] A binary map is created by selecting pixels identified as highlights from the artifact-free LDR video frames, in which a pixel is set to 1 if it is determined to be a highlight, and 0 otherwise.

[0030] Furthermore, the criteria for determining whether a pixel is a highlight include:

[0031] Pixels with a brightness value greater than 222;

[0032] The RGB channel value exceeds 230 pixels.

[0033] Furthermore, the Mantiuk formula is expressed as:

[0034] ;

[0035] in, and These are the HDR extended brightness obtained during highlight enhancement and the filtered LDR video frame, respectively. Brightness at that location The filtered LDR video frames are in Color components at the location, These are the color components of the output HDR video frame. 's' is the color channel, and 's' is the color saturation parameter.

[0036] According to another aspect of the present invention, a brightness adjustment system for a mobile phone display screen is disclosed, the system comprising:

[0037] The artifact suppression module is used to preprocess the input LDR video frame through a fast guided filter to remove noise and artifacts caused by compression or sensor while preserving edge details. The parameters of the fast guided filter include local window radius, regularization parameter and subsampling rate to manage smoothness and improve filtering efficiency.

[0038] The dynamic range extension module is used to extend the brightness range of the input LDR video frame based on a global operator of mid-gray value mapping. Specifically, it includes: automatically calculating the mid-gray value output parameters, which are determined by multilinear regression using the statistical characteristics of the geometric mean brightness, contrast, and percentage of overexposed pixels of the LDR video frame; and adjusting the mid-gray value output parameters using a weighted average method to reduce inter-frame brightness variations and suppress flicker artifacts.

[0039] The dequantization module is used to iteratively remove false contours in the smooth transition region within the LDR video frame by using a minimization algorithm based on iterative projection to convex set while expanding the brightness range of the LDR video frame.

[0040] A 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 bright areas, and use a guided filter to fuse the original brightness details to enhance the peak brightness of the bright areas.

[0041] A saturation enhancement module is used to redistribute the brightness of the luminance-expanded LDR video frame to the RGB color channels using the Mantiuk formula, so as to realize the conversion of the LDR video to HDR video frame, and at the same time, to compensate for the color loss during the HDR conversion process by setting saturation enhancement parameters.

[0042] The technical solution of the present invention has the following beneficial effects:

[0043] It provides a comprehensive LDR to HDR conversion method for LDR video frames, adapting to the peak brightness of different displays, and can create HDR video frame sequences with high peak brightness capabilities; it can detect and enhance bright spots in HDR videos while staying within the parameter limitations of mobile phone displays; it can significantly improve the overall brightness of existing HDR content acquired on displays at lower brightness levels, thereby significantly improving visual quality. Attached Figure Description

[0044] Figure 1 This is a flowchart illustrating a method for adjusting the brightness of a mobile phone display screen in an embodiment of this specification.

[0045] Figure 2 This is a structural block diagram of a mobile phone display screen brightness adjustment system according to an embodiment of this specification. Detailed Implementation

[0046] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided to make the invention more comprehensive and complete, and to fully convey the concept of the exemplary embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a full understanding of embodiments of the invention. However, those skilled in the art will recognize that the technical solutions of the invention may be practiced with one or more of these specific details omitted, or other methods, components, apparatus, steps, etc., may be employed. In other instances, well-known technical solutions are not shown or described in detail to avoid obscuring various aspects of the invention.

[0047] Furthermore, the accompanying drawings are merely illustrative of the invention. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0048] In one implementation, such as Figure 1 As shown, this specification provides a method for adjusting the brightness of a mobile phone display screen. The subject executing this method can be a computer, server, tablet computer, mobile phone, etc. Specifically, the method may include the following steps S101~S104:

[0049] In step S101, the input LDR video frame is preprocessed by a fast guided filter to remove noise and artifacts caused by compression or sensors, while preserving edge details. The parameters of the fast guided filter include local window radius, regularization parameter and subsampling rate to manage smoothness and improve filtering efficiency.

[0050] LDR video frames inherently contain noise and artifacts, a characteristic often overlooked when display brightness and dynamic range are limited. Most artifacts originate from compression algorithms, and some from the original camera sensor during acquisition. Compression algorithms sacrifice artifacts at lower dynamic ranges to reduce data size. Therefore, filtering LDR video frames to reduce these artifacts and noise before extending dynamic range is crucial to prevent artifacts from worsening during dynamic range enhancement. This can be achieved using time-efficient guided filters, particularly fast guided filters. Guided filters possess strong edge-aware image filtering capabilities, removing or reducing noise and artifacts while preserving subtle details and textures. Specifically, the edge-preserving smoothing function of fast guided filters can quickly and effectively remove artifacts from input LDR video frames. Fast guided filters have three parameters controlling artifact denoising and processing speed: the local window radius, a regularization parameter managing smoothness, and a subsampling ratio to accelerate the filtering process. Careful adjustment of the first two parameters allows precise control of the filter's strength, adjusting the final appearance of the processed video frame to the desired specifications.

[0051] In step S102, the brightness range of the input LDR video frame is expanded based on the global operator of the mid-gray value mapping. Specifically, this includes: automatically calculating the mid-gray value output parameters, using the statistical characteristics of the geometric mean brightness, contrast and overexposed pixel percentage of the LDR video frame, and determining them through multilinear regression; and adjusting the mid-gray value output parameters using a weighted average method to reduce inter-frame brightness variations and suppress flicker artifacts.

[0052] The dynamic range extension function, proposed to enhance visual effects, effectively maintains peak brightness while adjusting the intermediate grayscale value (i.e., overall perceived brightness) to a comfortable level. The intermediate grayscale value, often simply referred to as "mid-gray," represents the perceptual midpoint between the extremes of black and white on the brightness scale. The extension function based on mid-grayscale mapping is expressed as follows:

[0053] ;

[0054] in and Represents at a given pixel point The brightness of the filtered LDR video frame and the output HDR video frame. , yes The maximum brightness value in [the range]. 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.

[0055] When using the grayscale mapping extension function to expand the brightness, the following two conditions are defined:

[0056] For any value , ;

[0057] ;

[0058] Substitute the condition into the extended function of the gray value mapping to solve the condition:

[0059] ;

[0060] ;

[0061] The solutions for parameters b and c are:

[0062] ;

[0063] ;

[0064] The condition is ;

[0065] Here, parameter 'a' defines the lower end of the curve of the grayscale mapping extension function, affecting the output contrast, while parameter 'd' defines the upper shape of the curve, affecting the extension of highlights. Typically, in inverse tone mapping, a 'd' value greater than 1 is needed to appropriately stretch highlights. Similarly, an 'a' value close to 1 preserves shadows, while significantly larger 'a' values ​​(a >> 1) compress in the output. Specifically, a slightly higher 'a' value can be used to strike a balance between enhancing and preserving shadows in the input LDR video frame and the output HDR video frame. Input the defined medium grayscale value, parameter To output the expected mid-grayscale value, and The anchor points of the curve are defined, and represent the mid-grayscale value defined by L and the output, respectively. The expected grayscale value.

[0066] parameter This is set to the mid-grayscale 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. Meanwhile, the parameter... This determines the mid-grayscale value of the expected HDR video frame, which essentially controls its overall brightness.

[0067] Medium grayscale output value It is calculated using basic features derived from the filtered LDR video frames, including geometric mean, contrast, and the percentage of overexposed pixels in the filtered LDR video frames.

[0068] ;

[0069] It is the geometric mean. It's about contrast. This represents 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, and their values ​​affect... Size.

[0070] in:

[0071] ;

[0072] ;

[0073] ;

[0074] in It is the average brightness value, and the maximum brightness value is the maximum brightness value in the filtered LDR video frame. It is the total number of pixels. It is a small constant to avoid undefined values. This is the total number of overexposed pixels. Overexposed pixels are defined as 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 both dark and bright areas, which are considered outliers.

[0075] The geometric mean, representing a parameter of the perceived overall brightness of the input image, has the highest positive correlation with the mid-grayscale value in the output. This highlights the impact of perceived brightness on mid-grayscale adjustment during dynamic range extension. To prevent flickering in the inverse tone-mapped HDR video frame sequence due to sudden changes in estimated mid-grayscale values ​​between frames, the mid-grayscale output value used to extend the dynamic range of the current frame is adjusted using a weighted average, as shown below:

[0076] ;

[0077] in This represents the mid-grayscale output value used to extend the dynamic range of the previous frame. It is a mid-grayscale output value calculated based on experience. It is a weight value, which can be used as a "damping" factor; a larger value indicates better performance. It can suppress sudden changes in mid-grayscale output, thereby preventing flicker artifacts in the resulting HDR video frame sequence.

[0078] In step S103, while expanding the brightness range of the LDR video frame, false contours in the smooth transition region within the LDR video frame are iteratively removed using a minimization algorithm based on iterative projection to convex sets.

[0079] The key parameters used in removing false contours from the LDR video frames are: the difference between two consecutive pixels within the smoothing region, the radius of the average filter, and the number of iterations.

[0080] Specifically, step S103 is used to remove "false contours" or "banding artifacts" commonly found in smooth transition regions within LDR video frames. A fast iterative false contour removal method can be employed, treating 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). In this method, the contour removal method works in conjunction with a dynamic range expansion function; that is, false contour removal and dynamic range expansion 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, pixel values ​​are filtered using a low-pass filter (first operator), and the resulting values ​​are clamped (second operator) to remain within quantization boundaries. The low-pass filter is a two-dimensional averaging filter.

[0081] The contour removal method is defined by three key parameters: the difference between two consecutive pixels within the smooth region, the radius of the averaging filter, and the number of iterations. The perception of a smooth transition between two consecutive pixels in an image depends on several factors; for a standard 8-bit LDR video frame image, a typical difference threshold ranges from 1 to 5 units. However, this is only illustrative, and the optimal range can be determined through practical debugging.

[0082] In step S104, the artifact-free LDR video frame and its luminance channel are analyzed to detect highlights and generate an extended map. The extended map is analyzed and the bright areas are marked. A guided filter is used to fuse the original luminance details to enhance the peak luminance of the bright areas.

[0083] The primary goal of the specular enhancement step is to restore high-brightness areas to a higher output brightness relative to mid-grayscale points, within the capabilities of the display system. The specular enhancement step specifically targets the identification and enhancement of highlights, aiming to amplify them to higher brightness. This is achieved by identifying highlight locations in the current LDR video frame and specifying the required enhancement level for each pixel. Specifically, artifact-free LDR video frames and their luminance channels are first analyzed to detect highlights and generate an extended map.

[0084] The process of detecting highlights in the LDR video frame and generating an extended map includes: creating a binary map by selecting pixels identified as highlights from the artifact-free LDR video frame, wherein in the binary map, 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 an LDR video frame is 255, the determination of a pixel as a highlight is based on the following criteria:

[0085] Pixels with a brightness value greater than 222; a brightness value of 222 is used to detect clipping regions that are considered to be highlights. These regions are caused by the limited dynamic range of LDR video frames, indicating that the brightness level exceeds the display's capabilities and details may be lost.

[0086] Pixels with RGB channel values ​​exceeding 230. This standard helps in accurately locating highlights characterized by color saturation. Using this threshold helps identify pixels associated with specular highlights and light sources that display color saturation.

[0087] To compute the extended image, the structure of the fast guided filter can be used to transfer filtering properties, namely its ability to transfer structural information from the guide image to the target image. Specifically, the binary image of the highlights is filtered using the LDR luminance extracted from the artifact-free input LDR video frame as the guide image, ensuring that the details and subtle gradients present in the original LDR luminance are effectively incorporated into the binary image, thus enhancing its accuracy and detail.

[0088] 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 the conversion of the LDR video to the HDR video frame. At the same time, the color loss during the HDR conversion process is compensated by setting the saturation enhancement parameter.

[0089] The Mantiuk formula is expressed as follows:

[0090] ;

[0091] in, and These are the HDR extended brightness obtained during highlight enhancement and the filtered LDR video frame, respectively. Brightness at that location The filtered LDR video frames are in Color components at the location, These are the color components of the output HDR video frame. 's' 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 frames.

[0092] Based on the same line of thought, such as Figure 2 As shown, an exemplary embodiment of the present invention also provides a brightness adjustment system for a mobile phone display screen, the system comprising:

[0093] The artifact suppression module 201 is used to preprocess the input LDR video frame through a fast guided filter to remove noise and artifacts caused by compression or sensors, while preserving edge details. The parameters of the fast guided filter include local window radius, regularization parameter and subsampling rate to manage smoothness and improve filtering efficiency.

[0094] The dynamic range extension module 202 is used to extend the brightness range of the input LDR video frame based on a global operator of mid-gray value mapping. Specifically, it includes: automatically calculating the mid-gray value output parameters, using the statistical characteristics of the geometric mean brightness, contrast and overexposed pixel percentage of the LDR video frame, and determining them through multilinear regression; and adjusting the mid-gray value output parameters using a weighted average method to reduce inter-frame brightness changes and suppress flicker artifacts.

[0095] The dequantization module 203 is used to iteratively remove false contours in the smooth transition region within the LDR video frame by using a minimization algorithm based on iterative projection to convex set while expanding the brightness range of the LDR video frame.

[0096] The brightness enhancement module 204 is used to analyze the LDR video frame and its brightness channel without artifacts to detect highlights and generate an extended map, analyze the extended map and mark the bright areas, and use a guided filter to fuse the original brightness details to enhance the peak brightness of the bright areas.

[0097] The saturation enhancement module 205 is used to redistribute the brightness of the luminance of the luminance-expanded LDR video frame to the RGB color channels using the Mantiuk formula, so as to realize the conversion of the LDR video to the HDR video frame, and at the same time, to compensate for the color loss during the HDR conversion process by setting saturation enhancement parameters.

[0098] 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 displays and can create HDR video frame sequences with high peak brightness capabilities; it can detect and enhance bright spots in HDR videos while staying within the parameter limitations of mobile phone displays; it can significantly improve the overall brightness of existing HDR content acquired on displays at lower brightness levels, thereby significantly improving visual quality.

[0099] From the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions of the embodiments of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, portable hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, terminal device, or network device, etc.) to execute the method according to the exemplary embodiments of the present invention.

[0100] Furthermore, the above figures are merely illustrative representations of the processes included in the method according to exemplary embodiments of the present invention, and are not intended to be limiting. It is readily understood that the processes shown in the above figures do not indicate or limit the temporal order of these processes. Additionally, it is readily understood that these processes may be executed synchronously or asynchronously, for example, in multiple modules.

[0101] Other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of 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 not disclosed herein. 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 includes: The input LDR video frames are preprocessed by a fast guided filter to remove noise and artifacts caused by compression or sensors, while preserving edge details. The parameters of the fast guided filter include local window radius, regularization parameter and subsampling rate to manage smoothness and improve filtering efficiency. The global operator based on mid-grayscale mapping extends the brightness range of the input LDR video frame, specifically including: automatically calculating mid-grayscale output parameters, which are determined by multilinear regression using the statistical characteristics of the geometric mean brightness, contrast, and overexposed pixel percentage of the LDR video frame; adjusting the mid-grayscale output parameters using a weighted averaging method to reduce inter-frame brightness variations and suppress flicker artifacts; the extension function based on the mid-grayscale mapping is expressed as: ； in and Represents at a given pixel point The brightness of the filtered LDR video frame and the output HDR video frame. , yes The maximum brightness value in the middle. 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; when using the grayscale mapping extension function to extend the brightness, the following two conditions are defined: For any value , ; ； Substitute the condition into the extended function of the gray value mapping to solve the condition: ； ； The solutions for parameters b and c are: ； ； The condition is ; Wherein, parameter a defines the lower end of the curve of the grayscale mapping extension function, affecting the output contrast; parameter d defines the shape of the upper end of the curve, affecting the extension of highlights; parameter... Input the defined medium grayscale value, parameter To output the expected mid-grayscale value, and The anchor points of the curve are defined, and the parameters are... It is calculated using basic features derived from the filtered LDR video frame, which include geometric mean, contrast, and the percentage of overexposed pixels in the filtered LDR video frame; While expanding the brightness range of the LDR video frame, false contours in the smooth transition region within the LDR video frame are iteratively removed using a minimization algorithm based on iterative projection to convex set. The LDR video frame and its luminance channel, after iterative removal of false contours and artifacts, are analyzed to detect highlights and generate an extended map. The extended map is analyzed and the bright areas are marked. A guided filter is used to fuse the original luminance details to improve the peak luminance of the bright areas. The Mantiuk formula is used to redistribute the brightness of the luminance-expanded LDR video frame to the RGB color channels to achieve the conversion from LDR video to HDR video frame. Simultaneously, a saturation enhancement parameter is set to compensate for color loss during the HDR conversion process. The Mantiuk formula is expressed as: ； in, and These are the HDR extended brightness obtained during highlight enhancement and the filtered LDR video frame, respectively. Brightness at that location The filtered LDR video frames are in Color components at the location, These are the color components of the output HDR video frame. 's' is the color channel, and 's' is the color saturation parameter.

2. The method for adjusting the brightness of a mobile phone display screen according to claim 1, characterized in that, The key parameters used in removing false contours from the LDR video frames are: the difference between two consecutive pixels within the smoothing region, the radius of the average filter, and the number of iterations.

3. The method for adjusting the brightness of a mobile phone display screen according to claim 1, characterized in that, Detecting highlights in the LDR video frame and generating an extended map includes: A binary map is created by selecting pixels identified as highlights from the LDR video frames after iterative removal of false contours and artifact-free conditions. In this binary map, if a pixel is determined to be a highlight, its pixel value is set to 1, and if not, it is set to 0.

4. The method for adjusting the brightness of a mobile phone display screen according to claim 3, characterized in that, When determining whether a pixel is a highlight, the criteria include: Pixels with a brightness value greater than 222; The RGB channel value exceeds 230 pixels.

5. A brightness adjustment system for a mobile phone display screen, characterized in that, The system includes: The artifact suppression module is used to preprocess the input LDR video frame through a fast guided filter to remove noise and artifacts caused by compression or sensor while preserving edge details. The parameters of the fast guided filter include local window radius, regularization parameter and subsampling rate to manage smoothness and improve filtering efficiency. The dynamic range expansion module is used to expand the brightness range of the input LDR video frame based on a global operator of mid-gray value mapping. Specifically, it includes: automatically calculating mid-gray value output parameters, which are determined through multilinear regression using the statistical characteristics of the geometric mean brightness, contrast, and overexposed pixel percentage of the LDR video frame; adjusting the mid-gray value output parameters using a weighted averaging method to reduce inter-frame brightness variations and suppress flicker artifacts; and expressing the expansion function based on the mid-gray value mapping as follows: ； in and Represents at a given pixel point The brightness of the filtered LDR video frame and the output HDR video frame. , yes The maximum brightness value in the middle. 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; when using the grayscale mapping extension function to extend the brightness, the following two conditions are defined: For any value , ; ； Substitute the condition into the extended function of the gray value mapping to solve the condition: ； ； The solutions for parameters b and c are: ； ； The condition is ; Wherein, parameter a defines the lower end of the curve of the grayscale mapping extension function, affecting the output contrast; parameter d defines the shape of the upper end of the curve, affecting the extension of highlights; parameter... Input the defined medium grayscale value, parameter To output the expected mid-grayscale value, and The anchor points of the curve are defined, and the parameters are... It is calculated using basic features derived from the filtered LDR video frame, which include geometric mean, contrast, and the percentage of overexposed pixels in the filtered LDR video frame; The dequantization module is used to expand the brightness range of the LDR video frame while iteratively removing false contours in the smooth transition region within the LDR video frame using a minimization algorithm based on iterative projection to convex set. A brightness enhancement module is used to analyze the LDR video frame and its brightness channel after iterative removal of false contours to detect highlights and generate an extended map, analyze the extended map and mark the bright areas, and use a guided filter to fuse the original brightness details to enhance the peak brightness of the bright areas. A saturation enhancement module is used to redistribute the brightness of the luminance-expanded LDR video frame to the RGB color channels using the Mantiuk formula, thereby achieving the conversion from LDR video to HDR video frames. Simultaneously, it compensates for color loss during the HDR conversion process by setting saturation enhancement parameters. The Mantiuk formula is expressed as: ； in, and These are the HDR extended brightness obtained during highlight enhancement and the filtered LDR video frame, respectively. Brightness at that location The filtered LDR video frames are in Color components at the location, These are the color components of the output HDR video frame. 's' is the color channel, and 's' is the color saturation parameter.

Images