Image processing method and system for full reflection screen display

Abstract

The present invention relates to the field of image processing technology, and in particular to an image processing method and system for a fully reflective screen display, comprising the following steps: S1: receiving compressed image data inputted from the outside through an image input module, and decoding the input image data using a decoding algorithm; S2: performing spatial segmentation processing on the image data decoded by S1; S3: optimizing the light reflection effect of each block area using a light reflection adjustment algorithm; S4: optimizing and adjusting the light according to the motion characteristics of the scene; S5: dynamically adjusting the brightness and color contrast of the front light source of the fully reflective screen using an energy efficiency optimization algorithm; S6: outputting the image data processed by S1 to S5 to the fully reflective screen. The present invention improves the image display clarity of the fully reflective screen in complex light and dynamic scenes, while reducing energy consumption, through light reflection optimization and energy efficiency dynamic adjustment technology.

Description

Technical Field

[0001] The present invention relates to the field of image processing technology, and in particular to an image processing method and system for a total reflection screen display. Background Art

[0002] In recent years, full-reflection screen display technology has been widely used in smart devices. It uses the full reflection characteristics of light to improve the brightness, contrast and energy efficiency of the screen. By reducing the refraction and absorption of external light, the full-reflection screen can maintain clear image display effects in brighter environments and effectively reduce power consumption. This technology has broad application prospects in mobile devices, tablets and high-brightness displays. However, with the diversification and complexity of display requirements, especially in dynamic scenes and low-brightness environments, the existing full-reflection screen display technology still faces many challenges. Existing technologies make it difficult to balance light reflection, dynamic scene recognition, front light source control and energy consumption optimization while ensuring image quality, resulting in unstable display effects and high energy consumption.

[0003] The current full-reflection screen display system has the following technical difficulties: in dynamic scenes, fast-moving objects are prone to blurred image edges; under complex lighting conditions, the screen's light reflection is not adjusted enough, resulting in unclear image details; the front light source control mechanism cannot be adaptively adjusted in high-brightness or low-brightness scenes, resulting in excessive energy consumption or unclear display. Therefore, an image processing method and system for full-reflection screen display is urgently needed to solve the above problems. Summary of the invention

[0004] Based on the above purpose, the present invention provides an image processing method and system for a total reflection screen display.

[0005] A method for processing an image displayed on a total reflection screen, comprising the following steps:

[0006] S1: receiving external compressed image data through the image input module, and decoding the input image data using a decoding algorithm to convert the compressed image signal into a recognizable standard format;

[0007] S2: Perform spatial segmentation processing on the image data decoded by S1, and divide the image into multiple block areas based on the pixel density block algorithm, where each block area is independently identified according to its pixel density and image characteristics;

[0008] S3: Perform light reflection adjustment on each image area after S2 segmentation, and use a light reflection adjustment algorithm to optimize the light reflection effect of each segmented area based on the incident angle and total reflection angle of the reflected light;

[0009] S4: Use scene recognition algorithm to perform content analysis on the image processed by S3 to determine whether the current image is a dynamic scene. If it is a dynamic scene, optimize the light according to the motion characteristics of the scene, including correcting the light reflection at the edge of fast-moving objects;

[0010] S5: Based on the scene recognition results of S4, the energy efficiency optimization algorithm is used to dynamically adjust the brightness and color contrast of the front light source of the fully reflective screen. Specifically, the front light source intensity is automatically reduced in high-brightness scenes, and the front light source brightness is enhanced in low-light conditions.

[0011] S6: Output the image data processed by S1 to S5 to the full reflection screen.

[0012] Optionally, the S1 specifically includes:

[0013] S11: receiving compressed image data inputted from the outside through the image input module, wherein the compressed image data is transmitted through a high-speed serial interface, wherein the specific interface protocol includes HDMI, DP or USB-C, and temporarily storing the input data through a cache unit;

[0014] S12: In the image input module, the format of the received compressed image data is identified, and the specific format includes the standard format of H.264, H.265 or JPEG2000;

[0015] S13: according to the compression encoding format identified in S12, calling a corresponding decoding algorithm for decoding, the decoding process includes decompression and restoration of the data frame, the decoding algorithm corresponds to the compression format one by one, and is used to restore the image data to an uncompressed state;

[0016] S14: Convert the decoded image signal into a standardized image signal format, wherein the standard format is RGB or YUV.

[0017] Optionally, the S2 specifically includes:

[0018] S21: preprocessing the image data decoded by S1, including preliminary calculation of the pixel density of the image, and obtaining the distribution of the pixel density by calculating the ratio between the brightness of each pixel and the pixel area;

[0019] S22: setting a threshold range of pixel density, and dividing the image into a high pixel density area and a low pixel density area according to a preset density division standard;

[0020] S23: using a preset block algorithm, according to the pixel density threshold set in S22, the image data is divided into a plurality of block areas, wherein the block algorithm generates a plurality of block areas with different pixel densities by judging the change trend of the pixel density, so as to ensure that the image details are fully preserved;

[0021] S24: Independently identify each block area, and the independent identification is based on the extraction of image features, including the color distribution, edge information and texture features of the area; by uniquely numbering the color and texture features of each block area, it is ensured that different block areas can be independently identified and processed in subsequent processing steps.

[0022] Optionally, the S23 specifically includes:

[0023] S231: First, calculate the pixel density change of each pixel point, specifically using the gradient calculation formula:

[0024] ,in, Indicates that the image is at position The pixel density value at ; Represents the gradient value of pixel density; is the pixel density in the horizontal direction The rate of change on is the pixel density in the vertical direction The rate of change on the horizontal axis; The gradient calculation formula is used to calculate the horizontal direction of each pixel. and vertical direction Pixel density variation trend on ;

[0025] S232: Divide the image data into different density regions according to the pixel density gradient value calculated in S231; specifically, by setting a gradient threshold , to determine whether each pixel belongs to a high-density change area or a low-density change area; the judgment criteria are: When , the pixel belongs to the high-density change area; when When , the pixel belongs to the low-density change area;

[0026] S233: Based on the area divided in S232, a Flood Fill algorithm is used to determine the connectivity of adjacent pixels, and adjacent high-density change areas and low-density change areas are merged.

[0027] Optionally, the S3 specifically includes:

[0028] S31: For each block area, firstly calculate the incident angle and total reflection angle of the incident light;

[0029] S32: judging whether the current light meets the total reflection condition according to the incident angle and total reflection angle calculated in S31;

[0030] S33: For the light that meets the total reflection condition, the direction of the reflected light is adjusted using the total reflection optimization algorithm; for the light that does not meet the total reflection condition, the ratio of the transmitted light and the reflected light is adjusted using the refraction optimization algorithm by calculating the reflection coefficient and the refraction coefficient;

[0031] S34: Based on the reflected light direction and reflection coefficient calculated in S33, the light reflection effect of each block area is adjusted to ensure that the light reflection direction of the total reflection area is consistent with the target observation angle.

[0032] Optionally, the S4 specifically includes:

[0033] S41: Performing a preliminary analysis on the image processed by S3 using a scene recognition algorithm, wherein the scene recognition algorithm extracts motion information of each pixel in the image by comparing the pixel brightness changes between consecutive image frames; and determines the degree of motion in the image by performing a statistical analysis on the motion information of the entire image; if the motion values ​​of 80% of the pixels exceed a preset threshold, the image is determined to be a dynamic scene; if the motion values ​​of 80% of the pixels do not exceed the threshold, the image is determined to be a static scene;

[0034] S42: when the image is identified as a dynamic scene, extract the edge area of ​​the dynamic object, and identify the boundary of the object by performing edge detection on the brightness change of the object; the edge area detection is based on the gradient of the brightness change, and when the gradient change is large, the marked area is the edge of the object;

[0035] S43: Optimize light reflection at the edge of fast-moving objects in dynamic scenes; specifically, reduce the diffusion of reflected light at the edge of the object, and adjust the direction of light reflection to ensure that the edge of the object remains clear during fast movement.

[0036] Optionally, the S5 specifically includes:

[0037] S51: Based on the scene recognition result of S4, the overall brightness of the current image scene is analyzed, and the lighting condition of the current scene is determined by detecting the brightness value of each block area in the image and using the brightness value to calculate the average brightness of the entire scene; if the scene brightness is higher than a preset threshold, it is determined to be a high-brightness scene; if the scene brightness is lower than the preset threshold, it is determined to be a low-brightness or insufficiently lit scene;

[0038] S52: when it is determined that the current image is a high-brightness scene, the brightness of the front light source of the full-reflection screen is dynamically adjusted by using an energy efficiency optimization algorithm, so as to reduce the overall energy consumption by reducing the intensity of the front light source;

[0039] S53: When it is determined that the current image is of low brightness or insufficient light, the brightness of the front light source is automatically increased through an energy efficiency optimization algorithm to ensure that the image displayed on the screen is clear enough;

[0040] S54: While adjusting the brightness of the front light source, the energy efficiency optimization algorithm also dynamically adjusts the color contrast of the screen. For high-brightness scenes, the color contrast is appropriately reduced to prevent overexposure or color distortion; for low-brightness scenes, the color contrast is increased to enhance the depth and layering of the picture.

[0041] Optionally, the S52 specifically includes:

[0042] S521: When the current image is determined to be a high-brightness scene, first calculate the average brightness value of the current scene , the average brightness value is obtained by weighted average calculation of the brightness values ​​of each block area in the image;

[0043] S522: Based on the calculated average brightness value , set the adjustment target of the front light source brightness , the target front light source brightness is set based on the following principles: Exceeds the preset high brightness threshold , it will automatically trigger the front light source brightness reduction operation, specifically adjust the target The calculation is: ,in, is the maximum brightness value of the front light source; The preset high brightness scene threshold: is the maximum brightness value of the scene;

[0044] S523: Using energy efficiency optimization algorithm, according to the set front light source brightness target , dynamically adjust the brightness of the front light source of the fully reflective screen, specifically by adjusting the output power of the front light source driving circuit, gradually increasing the current front light source brightness Adjust to target value , the specific adjustment formula is:

[0045] ,in, Indicates the current time The brightness of the front light source at To adjust the rate coefficient, control the adjustment speed of the front light source brightness.

[0046] Optionally, the S6 specifically includes:

[0047] S561: according to the display requirements of the full reflection screen, a standard image format conversion module is used to convert the image data into an output format compatible with the full reflection screen, and the specific format includes an RGB format or a YUV format;

[0048] S562: The format-converted image data is output to the full-reflection screen via a high-bandwidth transmission interface, wherein the specific transmission interface includes HDMI, DisplayPort or LVDS.

[0049] An image processing system for a fully reflective screen display, used to implement the above-mentioned image processing method for a fully reflective screen display, comprises the following modules:

[0050] Image input module: used for receiving compressed image data input from the outside, and decoding the image data, and the decoded image data is transmitted to the image processing module;

[0051] Image processing module: used to process the decoded image data transmitted by the image input module; the image processing module includes an image block processing unit, a light reflection adjustment unit and a dynamic scene recognition unit;

[0052] The image block processing unit is used to perform spatial segmentation on the decoded image data and perform block division based on pixel density and image features;

[0053] The light reflection adjustment unit is used to optimize and adjust the light reflection effect of each block area according to the incident angle and total reflection angle of the reflected light;

[0054] The dynamic scene recognition unit is used to recognize the image content and determine whether it is a dynamic scene;

[0055] Front light source control module: used to dynamically adjust the front light source brightness and color contrast of the full reflection screen according to the processing results output by the image processing module;

[0056] Image output module: used to output the optimized image data of the image processing module to the full reflection screen through a standard interface to ensure real-time transmission and display of image signals.

[0057] Beneficial effects of the present invention:

[0058] The present invention solves the problem of unclear image display in complex lighting environments caused by the existing total reflection screen by adopting a light reflection optimization algorithm and dynamic scene recognition technology. By accurately calculating and adjusting the incident light and the total reflection angle, the light reflection path can be effectively optimized, and reflection distortion can be reduced to ensure that the image maintains clear details and moderate contrast in a high-brightness environment. At the same time, when processing fast-moving objects, the motion features in the image are dynamically identified and the light reflection direction is adjusted, thereby avoiding the common image edge blur problem in the prior art and improving the display quality in dynamic scenes.

[0059] The present invention dynamically adjusts the brightness and color contrast of the front light source of the screen through an energy efficiency optimization algorithm, effectively reduces the intensity of the front light source in high-brightness scenes, thereby reducing unnecessary energy consumption; and enhances the brightness of the front light source in low-brightness scenes to ensure that the image is still clearly visible in a low-light environment. This optimization strategy not only greatly improves the energy efficiency utilization of the screen display, but also ensures the image display quality under different lighting conditions. It is particularly suitable for energy-sensitive applications such as mobile devices. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0061] Figure 1 is a schematic diagram of an image processing method according to an embodiment of the present invention;

[0062] Figure 2 FIG. 4 is a schematic diagram of an image processing system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0063] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. At the same time, it is explained here that in order to make the embodiments more detailed, the following embodiments are the best and preferred embodiments, and those skilled in the art may also adopt other alternatives to implement some known technologies; and the accompanying drawings are only for more specific description of the embodiments, and are not intended to specifically limit the present invention.

[0064] It should be noted that the references to "one embodiment", "embodiment", "exemplary embodiments", "some embodiments" and the like in the specification indicate that the embodiments described may include specific features, structures or characteristics, but not every embodiment may include the specific features, structures or characteristics. In addition, when a specific feature, structure or characteristic is described in conjunction with an embodiment, it should be within the knowledge of a person skilled in the art to implement such feature, structure or characteristic in conjunction with other embodiments (whether or not explicitly described).

[0065] In general, a term can be understood, at least in part, from its use in context. For example, depending, at least in part, on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in the singular sense, or can be used to describe a combination of features, structures, or characteristics in the plural sense. Additionally, the term "based on" can be understood as not necessarily intended to convey an exclusive set of factors, but can instead, depending, at least in part, on the context, allow for the presence of other factors that are not necessarily explicitly described.

[0066] like Figure 1 As shown, a method for processing an image displayed on a full-reflection screen comprises the following steps:

[0067] S1: receiving external compressed image data through the image input module, and decoding the input image data using a decoding algorithm to convert the compressed image signal into a recognizable standard format;

[0068] S2: Perform spatial segmentation processing on the image data decoded by S1, and divide the image into multiple block areas based on the pixel density block algorithm, where each block area is independently identified according to its pixel density and image features for subsequent light optimization processing;

[0069] S3: Perform light reflection adjustment on each image area after S2 segmentation. Based on the incident angle and total reflection angle of the reflected light, a light reflection adjustment algorithm is used to optimize the light reflection effect of each segmented area. During the adjustment process, light refraction distortion is avoided and the display effect of image details in the area is improved.

[0070] S4: Use scene recognition algorithm to analyze the content of the image processed by S3 to determine whether the current image is a dynamic scene. If it is a dynamic scene, optimize the light according to the motion characteristics of the scene, including correcting the light reflection at the edge of fast-moving objects to ensure that the image remains clear in dynamic scenes;

[0071] S5: Based on the scene recognition results of S4, the energy efficiency optimization algorithm is used to dynamically adjust the brightness and color contrast of the front light source of the fully reflective screen. Specifically, the front light source intensity is automatically reduced in high-brightness scenes to reduce energy consumption, and the front light source brightness is enhanced in insufficient light to ensure the picture display effect;

[0072] S6: The image data processed by S1 to S5 is output to the fully reflective screen. The output image is processed by light optimization and energy efficiency, and has the characteristics of high contrast, low energy consumption and clear details.

[0073] S1 specifically includes:

[0074] S11: receiving compressed image data inputted from the outside through the image input module, the image data being transmitted through a high-speed serial interface, the specific interface protocol including HDMI, DP or USB-C, and temporarily storing the input data through a cache unit;

[0075] S12: In the image input module, the format of the received compressed image data is identified, and the compression format includes a standard format of H.264, H.265 or JPEG2000;

[0076] S13: according to the compression encoding format identified in S12, calling a corresponding decoding algorithm for decoding, the decoding process includes decompression and restoration of the data frame, the decoding algorithm corresponds to the compression format one by one, and is used to restore the image data to an uncompressed state;

[0077] S14: Convert the decoded image signal into a standardized image signal format, the standard format is RGB or YUV, to ensure compatibility with subsequent image processing; through the above steps, the integrity of image data transmission, the accuracy of decoding and the recognizability of the standard format can be ensured, laying a solid technical foundation for subsequent image optimization processing.

[0078] S2 specifically includes:

[0079] S21: Preprocess the image data decoded by S1, including preliminary calculation of the pixel density of the image, and obtain the distribution of the pixel density by calculating the ratio between the brightness of each pixel and the pixel area; the pixel density is calculated based on the brightness value of each pixel and the average brightness value of its neighboring pixels, and the calculation formula is as follows: ,in, is the pixel density, Indicates the image The pixel brightness value at the coordinate position, is the average brightness value of the neighborhood around the pixel, is the number of pixels in the neighborhood; through this formula, the brightness change degree of each pixel relative to its neighborhood is calculated, and then the density information of the pixel is obtained. The pixel density distribution of the entire image is obtained by performing pixel-by-pixel calculations on the entire image;

[0080] S22: setting a threshold range of pixel density, and dividing the image into a high pixel density area and a low pixel density area according to a preset density division standard, so as to perform subsequent block processing according to different image contents;

[0081] S23: using a preset block algorithm, according to the pixel density threshold set in S22, the image data is divided into a plurality of block areas, the block algorithm generates a plurality of block areas with different pixel densities by judging the change trend of the pixel density, so as to ensure that the image details are fully preserved;

[0082] S24: Independently identify each block area, and the independent identification is based on the extraction of image features, including the color distribution, edge information and texture features of the area; by uniquely numbering the color and texture features of each block area, ensure that different block areas can be independently identified and processed in subsequent processing steps; the above steps perform a preliminary calculation of pixel density through a pixel brightness value calculation formula, and combine the independent identification method of image features to make the image block processing more accurate, providing accurate data support for subsequent light reflection adjustment.

[0083] The preset block algorithm used in S23 specifically includes:

[0084] S231: First, calculate the pixel density change of each pixel point, specifically using the gradient calculation formula:

[0085] ,in, Indicates that the image is at position The pixel density value at ; Represents the gradient value of pixel density; is the pixel density in the horizontal direction The rate of change on is the pixel density in the vertical direction The rate of change on the horizontal axis; The gradient calculation formula is used to calculate the horizontal direction of each pixel. and vertical direction Pixel density variation trend on ;

[0086] S232: Divide the image data into different density regions according to the pixel density gradient value calculated in S231; specifically, by setting a gradient threshold , to determine whether each pixel belongs to a high-density change area or a low-density change area; the judgment criteria are: When , the pixel belongs to the high-density change area; when When , the pixel belongs to the low-density change area;

[0087] S233: Based on the area divided in S232, a Flood Fill algorithm is used to determine the connectivity of adjacent pixels, and adjacent high-density change areas and low-density change areas are merged.

[0088] The specific process of the Flood Fill algorithm is as follows:

[0089] Select the starting point: From the initial pixel Start, where is the starting pixel point selected in the image, located at the coordinate position ;

[0090] Determine adjacent pixels: for the starting point The neighboring pixels , to determine whether it meets the connectivity conditions, the judgment criteria are: When and belong to the same connected region; among them, Represents pixel Pixel density; Represents pixel Pixel density; is the preset pixel density difference threshold, which determines whether adjacent pixels can be classified into the same region;

[0091] Recursive expansion: If adjacent pixels If the connectivity condition is met, it is added to the current block area, and the same judgment is repeated for its adjacent pixels until no adjacent pixels that meet the condition can be found;

[0092] Complete the block division: perform FloodFill algorithm processing on all pixel points to generate independent block areas; the above steps describe in detail the specific process of calculating the pixel density change trend, area division and block generation by combining the Flood Fill algorithm and the density gradient formula, and optimize the block division by judging the density difference of adjacent pixels, which effectively improves the accuracy of image processing and the operability of subsequent light reflection adjustment.

[0093] S3 specifically includes:

[0094] S31: For each block area, first calculate the incident angle and total reflection angle of the incident light, where the incident angle It refers to the incident angle of light relative to the surface of the block area, and the calculation formula is: ,in, Represents the normal vector of the surface of the block area; Represents the direction vector of the incident light; and is the magnitude of the vector; the total reflection angle The refractive index of the material and the refractive index of the external medium The calculation formula is: ,in, Represents the refractive index of the total reflection screen; represents the refractive index of the external medium (usually the refractive index of air);

[0095] S32: According to the incident angle and total reflection angle calculated in S31, it is determined whether the current light meets the total reflection condition; the specific judgment criteria are: When , the light is totally reflected; when When , the light is partially reflected and partially refracted;

[0096] S33: For the light that meets the total reflection condition, the direction of the reflected light is adjusted using the total reflection optimization algorithm; specifically, firstly according to the normal vector and the direction of the incident light, calculate the direction vector of the reflected light , the calculation formula is as follows: ,in, is the direction vector of the reflected light; is the direction vector of the incident light; is the normal vector of the surface of the block area; for the light that does not meet the total reflection condition, the refraction optimization algorithm is used to adjust the ratio of the transmitted light and the reflected light, and the adjustment is made by calculating the reflection coefficient and the refraction coefficient. The formula is: ; ,in, is the reflection coefficient, is the refractive index, is the refraction angle, calculated according to Snell's law: ;

[0097] S34: Based on the reflected light direction and reflection coefficient calculated in S33, adjust the light reflection effect of each block area to ensure that the light reflection direction of the total reflection area is consistent with the target observation angle; the above steps ensure that the light reflection of each block area meets the optical requirements of the total reflection screen through accurate calculation and adjustment of the light reflection direction, reflection and refraction ratio, thereby improving the image display effect.

[0098] S4 specifically includes:

[0099] S41: Performing a preliminary analysis on the image processed by S3 using a scene recognition algorithm. The scene recognition algorithm extracts motion information of each pixel in the image by comparing the pixel brightness changes between consecutive image frames; and determines the degree of motion in the image by performing a statistical analysis on the motion information of the entire image; if the motion values ​​of 80% of the pixels exceed a preset threshold, the image is determined to be a dynamic scene; if the motion values ​​of 80% of the pixels do not exceed the threshold, the image is determined to be a static scene;

[0100] S42: When the image is identified as a dynamic scene, the edge area of ​​the dynamic object is extracted, and the boundary of the object is identified by performing edge detection on the brightness change of the object; the detection of the edge area is based on the gradient of the brightness change, and when the gradient change is large, the marked area is the edge of the object; this process ensures accurate identification of the edge area of ​​the fast-moving object;

[0101] S43: Optimize light reflection at the edge of fast-moving objects in dynamic scenes; specifically, reduce the diffusion of reflected light at the edge of objects, and adjust the direction of light reflection to ensure that the edge of the object remains clear during fast motion, avoiding blurring caused by light distortion.

[0102] The steps to determine whether the current image is a dynamic scene are as follows:

[0103] First, the global motion vector field of the image is extracted. The global motion vector field is determined by comparing the pixel motion differences between image frames. The calculation formula is: ,in, Indicates location The pixel at time The brightness value of Indicates the rate of change of brightness between image frames; is the motion vector size of the image at that pixel;

[0104] Then, by calculating the motion vector field of each pixel in the entire image, it is determined whether the image is a dynamic scene; if the motion vector field of most pixels is Exceeding the preset threshold , it is determined to be a dynamic scene; when When , the image is a dynamic scene; when , the image is a static scene.

[0105] The steps to optimize light adjustment are as follows:

[0106] If the image is identified as a dynamic scene, the motion features are further analyzed to extract the edge area of ​​the fast-moving object; the edge extraction of the object uses the edge detection algorithm to calculate the gradient value of the object edge , the formula is as follows: ,in, For location The pixel brightness value at ; Indicates that the pixel is in the horizontal direction The rate of change of brightness on Indicates that the pixel is in the vertical direction The rate of change of brightness on is the gradient value of the edge; when the edge gradient value Exceeds the preset edge threshold When , it is marked as the edge pixel of the object;

[0107] According to the edge area of ​​the identified fast-moving object, the light reflection in the area is optimized and adjusted. Specifically, at the edge of the object, the diffusion of the reflected light is reduced for the high-frequency change area of ​​the light. By adjusting the direction vector of the reflected light , to avoid light scattering caused by rapid movement of objects, the formula is as follows: ,in, is the optimized reflected light direction vector; L is the incident light direction vector; is the normal vector of the block area.

[0108] S5 specifically includes:

[0109] S51: Based on the scene recognition result of S4, the overall brightness of the current image scene is analyzed, and the lighting condition of the current scene is determined by detecting the brightness value of each block area in the image and using the brightness value to calculate the average brightness of the entire scene; if the scene brightness is higher than a preset threshold, it is determined to be a high-brightness scene; if the scene brightness is lower than the preset threshold, it is determined to be a low-brightness or insufficiently lit scene;

[0110] S52: When it is determined that the current image is a high-brightness scene, the front light source brightness of the full-reflection screen is dynamically adjusted using an energy efficiency optimization algorithm, and the overall energy consumption is reduced by reducing the intensity of the front light source, thereby maintaining the clarity of the picture while reducing unnecessary power consumption; this step ensures that in an environment with sufficient light, the screen can effectively utilize natural light without the need to increase the brightness of the front light source, thereby achieving the purpose of reducing energy consumption;

[0111] S53: when it is determined that the current image is of low brightness or insufficient light, the brightness of the front light source is automatically increased through the energy efficiency optimization algorithm to ensure that the image displayed on the screen is clear enough. The front light source enhancement operation gradually increases the brightness value of the front light source until the preset target brightness level is reached, thereby compensating for the brightness defect caused by insufficient ambient light and ensuring that the user can clearly view the screen content. The specific adjustment process is consistent with step S52;

[0112] S54: While adjusting the brightness of the front light source, the energy efficiency optimization algorithm also dynamically adjusts the color contrast of the screen. For high-brightness scenes, the color contrast is appropriately reduced to prevent overexposure or color distortion. For low-brightness scenes, the color contrast is increased to enhance the depth and layering of the picture, ensuring that the visual effect of the image is consistent under different brightness conditions.

[0113] The S52 uses an energy efficiency optimization algorithm to dynamically adjust the brightness of the front light source of the fully reflective screen, including:

[0114] S521: When the current image is determined to be a high-brightness scene, first calculate the average brightness value of the current scene The average brightness value is obtained by weighted average calculation of the brightness values ​​of each block area in the image; it is used for subsequent adjustment of the brightness of the front light source;

[0115] S522: Based on the calculated average brightness value , set the adjustment target of the front light source brightness , the target front light source brightness is set based on the following principles: Exceeds the preset high brightness threshold , it will automatically trigger the front light source brightness reduction operation, specifically adjust the target The calculation is: ,in, is the maximum brightness value of the front light source; The preset high brightness scene threshold is: is the maximum brightness value of the scene;

[0116] S523: Using energy efficiency optimization algorithm, according to the set front light source brightness target , dynamically adjust the brightness of the front light source of the fully reflective screen, specifically by adjusting the output power of the front light source driving circuit, gradually increasing the current front light source brightness Adjust to target value , the specific adjustment formula is:

[0117] ,in, Indicates the current time The brightness of the front light source at To adjust the rate coefficient, control the adjustment speed of the front light source brightness.

[0118] S6 specifically includes:

[0119] S561: according to the display requirements of the full reflection screen, a standard image format conversion module is used to convert the image data into an output format compatible with the full reflection screen, and the specific format includes an RGB format or a YUV format;

[0120] S562: The format-converted image data is output to the fully reflective screen through a high-bandwidth transmission interface. The specific transmission interfaces include HDMI, DisplayPort or LVDS (low-voltage differential signal). These interfaces can ensure high-speed transmission of large amounts of image signals while ensuring data integrity and real-time performance. The choice of transmission channel depends on the interface compatibility and bandwidth requirements between the screen and the processor.

[0121] like Figure 2 As shown, an image processing system for a fully reflective screen display is used to implement the above-mentioned image processing method for a fully reflective screen display, and includes the following modules:

[0122] Image input module: used to receive compressed image data from the outside and decode the image data. The decoded image data is transmitted to the image processing module. The image input module is connected to the external data source through a standard transmission interface (HDMI, DisplayPort, USB-C), and has format detection and preliminary caching functions to ensure data integrity and real-time performance.

[0123] Image processing module: used to process the decoded image data transmitted by the image input module; the image processing module includes an image block processing unit, a light reflection adjustment unit and a dynamic scene recognition unit;

[0124] The image block processing unit is used to perform spatial segmentation on the decoded image data and perform block division based on pixel density and image features;

[0125] The light reflection adjustment unit is used to optimize and adjust the light reflection effect of each block area according to the incident angle and total reflection angle of the reflected light;

[0126] The dynamic scene recognition unit is used to recognize the image content and determine whether it is a dynamic scene;

[0127] Front light source control module: used to dynamically adjust the front light source brightness and color contrast of the full reflection screen according to the processing results output by the image processing module;

[0128] Image output module: used to output the optimized image data of the image processing module to the full reflection screen through a standard interface to ensure real-time transmission and display of image signals.

[0129] The present invention covers any substitution, modification, equivalent method and scheme made on the essence and scope of the present invention. In order to make the public have a thorough understanding of the present invention, specific details are described in detail in the following preferred embodiments of the present invention, but those skilled in the art can fully understand the present invention without the description of these details. In addition, in order to avoid unnecessary confusion about the essence of the present invention, well-known methods, processes, procedures, components and circuits are not described in detail.

[0130] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for processing images displayed on a fully reflective screen, characterized in that: The following steps are involved: S1: receiving external compressed image data through the image input module, and decoding the input image data using a decoding algorithm to convert the compressed image signal into a recognizable standard format; S2: Perform spatial segmentation processing on the image data decoded by S1, and divide the image into multiple block areas based on the pixel density block algorithm, where each block area is independently identified according to its pixel density and image characteristics; S3: Perform light reflection adjustment on each image area after S2 segmentation, and use a light reflection adjustment algorithm to optimize the light reflection effect of each segmented area based on the incident angle and total reflection angle of the reflected light; S4: Use scene recognition algorithm to analyze the content of the image processed by S3 to determine whether the current image is a dynamic scene. If it is a dynamic scene, optimize the light according to the motion characteristics of the scene, including correcting the light reflection at the edge of fast-moving objects; S5: Based on the scene recognition results of S4, the energy efficiency optimization algorithm is used to dynamically adjust the brightness and color contrast of the front light source of the fully reflective screen. Specifically, the front light source intensity is automatically reduced in high-brightness scenes, and the front light source brightness is enhanced in low-light conditions. S6: Output the image data processed by S1 to S5 to the full reflection screen.

2. The image processing method for a total reflection screen display according to claim 1, characterized in that: The S1 specifically includes: S11: receiving compressed image data inputted from the outside through the image input module, wherein the compressed image data is transmitted through a high-speed serial interface, wherein the specific interface protocol includes HDMI, DP or USB-C, and temporarily storing the input data through a cache unit; S12: In the image input module, the format of the received compressed image data is identified, and the specific format includes the standard format of H.264, H.265 or JPEG2000; S13: according to the compression encoding format identified in S12, calling a corresponding decoding algorithm for decoding, the decoding process includes decompression and restoration of the data frame, the decoding algorithm corresponds to the compression format one by one, and is used to restore the image data to an uncompressed state; S14: Convert the decoded image signal into a standardized image signal format, wherein the standard format is RGB or YUV.

3. The image processing method for a total reflection screen display according to claim 1, characterized in that: The S2 specifically includes: S21: preprocessing the image data decoded by S1, including preliminary calculation of the pixel density of the image, and obtaining the distribution of the pixel density by calculating the ratio between the brightness of each pixel and the pixel area; S22: setting a threshold range of pixel density, and dividing the image into a high pixel density area and a low pixel density area according to a preset density division standard; S23: using a preset block algorithm, according to the pixel density threshold set in S22, the image data is divided into a plurality of block areas, wherein the block algorithm generates a plurality of block areas with different pixel densities by judging the change trend of the pixel density, so as to ensure that the image details are fully preserved; S24: Independently identify each block area, and the independent identification is based on the extraction of image features, including the color distribution, edge information and texture features of the area; by uniquely numbering the color and texture features of each block area, it is ensured that different block areas can be independently identified and processed in subsequent processing steps.

4. The image processing method for a total reflection screen display according to claim 3, characterized in that: The S23 specifically includes: S231: First, calculate the pixel density change of each pixel point, specifically using the gradient calculation formula: ,in, Indicates that the image is at position The pixel density value at ; Represents the gradient value of pixel density; is the pixel density in the horizontal direction The rate of change on is the pixel density in the vertical direction The rate of change on the horizontal axis; The gradient calculation formula is used to calculate the horizontal direction of each pixel. and vertical direction Pixel density variation trend on ; S232: Divide the image data into different density regions according to the pixel density gradient value calculated in S231; specifically, by setting a gradient threshold , to determine whether each pixel belongs to a high-density change area or a low-density change area; the judgment criteria are: When , the pixel belongs to the high-density change area; when When , the pixel belongs to the low-density change area; S233: Based on the area divided in S232, a Flood Fill algorithm is used to determine the connectivity of adjacent pixels, and adjacent high-density change areas and low-density change areas are merged.

5. The image processing method for a total reflection screen display according to claim 1, characterized in that: The S3 specifically includes: S31: For each block area, firstly calculate the incident angle and total reflection angle of the incident light; S32: judging whether the current light meets the total reflection condition according to the incident angle and total reflection angle calculated in S31; S33: For the light that meets the total reflection condition, the direction of the reflected light is adjusted using the total reflection optimization algorithm; for the light that does not meet the total reflection condition, the ratio of the transmitted light and the reflected light is adjusted using the refraction optimization algorithm by calculating the reflection coefficient and the refraction coefficient; S34: Based on the reflected light direction and reflection coefficient calculated in S33, the light reflection effect of each block area is adjusted to ensure that the light reflection direction of the total reflection area is consistent with the target observation angle.

6. The image processing method for a total reflection screen display according to claim 1, characterized in that: The S4 specifically includes: S41: Performing a preliminary analysis on the image processed by S3 using a scene recognition algorithm, wherein the scene recognition algorithm extracts motion information of each pixel in the image by comparing the pixel brightness changes between consecutive image frames; and determines the degree of motion in the image by performing a statistical analysis on the motion information of the entire image; if the motion values ​​of 80% of the pixels exceed a preset threshold, the image is determined to be a dynamic scene; if the motion values ​​of 80% of the pixels do not exceed the threshold, the image is determined to be a static scene; S42: when the image is identified as a dynamic scene, extract the edge area of ​​the dynamic object, and identify the boundary of the object by performing edge detection on the brightness change of the object; the edge area detection is based on the gradient of the brightness change, and when the gradient change is large, the marked area is the edge of the object; S43: Optimize light reflection at the edge of fast-moving objects in dynamic scenes; specifically, reduce the diffusion of reflected light at the edge of the object, and adjust the direction of light reflection to ensure that the edge of the object remains clear during fast movement.

7. The image processing method for a total reflection screen display according to claim 1, characterized in that: The S5 specifically includes: S51: Based on the scene recognition result of S4, the overall brightness of the current image scene is analyzed, and the lighting condition of the current scene is determined by detecting the brightness value of each block area in the image and using the brightness value to calculate the average brightness of the entire scene; if the scene brightness is higher than a preset threshold, it is determined to be a high-brightness scene; if the scene brightness is lower than the preset threshold, it is determined to be a low-brightness or insufficiently lit scene; S52: when it is determined that the current image is a high-brightness scene, the brightness of the front light source of the full-reflection screen is dynamically adjusted by using an energy efficiency optimization algorithm, so as to reduce the overall energy consumption by reducing the intensity of the front light source; S53: When it is determined that the current image is of low brightness or insufficient light, the brightness of the front light source is automatically increased through an energy efficiency optimization algorithm to ensure that the image displayed on the screen is clear enough; S54: While adjusting the brightness of the front light source, the energy efficiency optimization algorithm also dynamically adjusts the color contrast of the screen. For high-brightness scenes, the color contrast is appropriately reduced to prevent overexposure or color distortion; for low-brightness scenes, the color contrast is increased to enhance the depth and layering of the picture.

8. The image processing method for total reflection screen display according to claim 7, characterized in that: The S52 specifically includes: S521: When the current image is determined to be a high-brightness scene, first calculate the average brightness value of the current scene , the average brightness value is obtained by weighted average calculation of the brightness values ​​of each block area in the image; S522: Based on the calculated average brightness value , set the adjustment target of the front light source brightness , the target front light source brightness is set based on the following principles: Exceeds the preset high brightness threshold , it will automatically trigger the front light source brightness reduction operation, specifically adjust the target The calculation is: ,in, is the maximum brightness value of the front light source; The preset high brightness scene threshold: is the maximum brightness value of the scene; S523: Using energy efficiency optimization algorithm, according to the set front light source brightness target , dynamically adjust the brightness of the front light source of the fully reflective screen, specifically by adjusting the output power of the front light source driving circuit, gradually increasing the current front light source brightness Adjust to target value , the specific adjustment formula is: ,in, Indicates the current time The brightness of the front light source at To adjust the rate coefficient, control the adjustment speed of the front light source brightness.

9. The image processing method for a total reflection screen display according to claim 1, characterized in that: The S6 specifically includes: S561: according to the display requirements of the full reflection screen, a standard image format conversion module is used to convert the image data into an output format compatible with the full reflection screen, and the specific format includes an RGB format or a YUV format; S562: The format-converted image data is output to the full-reflection screen via a high-bandwidth transmission interface, wherein the specific transmission interface includes HDMI, DisplayPort or LVDS.

10. An image processing system for a total reflection screen display, used to implement an image processing method for a total reflection screen display as claimed in any one of claims 1 to 9, characterized in that: Includes the following modules: Image input module: used for receiving compressed image data input from the outside, and decoding the image data, and the decoded image data is transmitted to the image processing module; Image processing module: used to process the decoded image data transmitted by the image input module; the image processing module includes an image block processing unit, a light reflection adjustment unit and a dynamic scene recognition unit; The image block processing unit is used to perform spatial segmentation on the decoded image data and perform block division based on pixel density and image features; The light reflection adjustment unit is used to optimize and adjust the light reflection effect of each block area according to the incident angle and total reflection angle of the reflected light; The dynamic scene recognition unit is used to recognize the image content and determine whether it is a dynamic scene; Front light source control module: used to dynamically adjust the front light source brightness and color contrast of the full reflection screen according to the processing results output by the image processing module; Image output module: used to output the optimized image data of the image processing module to the full reflection screen through a standard interface to ensure real-time transmission and display of image signals.

Images