A display optimization method and system for liquid crystal display

Abstract

The application relates to the technical field of electronic display display methods, in particular to a display optimization method and system for a liquid crystal display screen. The method comprises the following steps: acquiring current image frame data and previous image frame data, and calculating interframe difference based on a preset pixel difference threshold; performing threshold value judgment based on the interframe difference data to obtain motion area data; calculating a gray scale change rate according to the motion area data; performing threshold value interception on the gray scale change rate data to obtain response optimization target area data and non-target area data; continuously evaluating the response optimization target area data, and performing merging processing based on the continuity evaluation result to obtain a continuous rectangular target area group. Through accurate identification of the motion area and gray scale change calculation, temperature adaptive adjustment and pulse width modulation, the application realizes dynamic optimization of the liquid crystal display screen, and improves the definition and display effect of a motion picture.

Description

Technical Field

[0001] This invention relates to the field of electronic display display methods, and in particular to a display optimization method and system for liquid crystal displays. Background Technology

[0002] Liquid crystal displays (LCDs), as a mainstream display technology, are widely used in televisions, computer monitors, and mobile devices. Traditional LCD technology relies on a backlight to provide brightness and adjusts the transmittance by rotating liquid crystal molecules to display images. Early LCDs used a passive matrix driving method, which suffered from slow response speed and contrast issues. Subsequently, the development of active matrix technology (TFT-LCD) significantly improved display performance, making high-resolution, high-refresh-rate, and wider color gamut LCD products mainstream. However, due to the long response time of liquid crystal molecules, compared to self-emissive display technologies (such as OLED and Micro-LED), LCDs still face problems such as motion blur and ghosting in dynamic images, especially at high refresh rates and with fast-moving scenes, where display clarity is affected. Traditional overdrive algorithms typically use fixed thresholds or calculation methods based on static grayscale differences, which cannot adequately adapt to complex image content and environmental factors. Existing inter-frame overdrive processing often fails to accurately distinguish between moving and static areas, resulting in over-enhancement or artifacts in some images. Summary of the Invention

[0003] Therefore, it is necessary for the present invention to provide a display optimization method and system for liquid crystal displays to solve at least one of the above-mentioned technical problems.

[0004] To achieve the above objectives, a display optimization method for a liquid crystal display screen includes the following steps:

[0005] Step S1: Obtain the current image frame data and the previous image frame data, and calculate the inter-frame difference based on the preset pixel difference threshold; perform threshold judgment based on the inter-frame difference data to obtain the motion region data;

[0006] Step S2: Calculate the grayscale change rate based on the motion area data; perform threshold truncation on the grayscale change rate data to obtain the target area data and non-target area data for response optimization;

[0007] Step S3: Perform continuity assessment on the data of the target region for response optimization, and merge the data based on the continuity assessment results to obtain a group of continuous rectangular target regions;

[0008] Step S4: Obtain the current temperature data; calculate the grayscale difference of the continuous rectangular target area group based on the current temperature data to obtain the temporary overdrive voltage value;

[0009] Step S5: pulse width modulation is performed on the temporary overdrive voltage value, wherein the response optimization target region data is high-frequency pulse width modulated to generate an optimization driving signal, and the non-target region data is standard pulse width modulated to generate a standard driving signal;

[0010] Step S6: based on the optimization driving signal and the standard driving signal, the liquid crystal display screen is partitioned and compensated for driving control, and the partitioned driving control result is dynamically evaluated for definition to obtain display effect evaluation data.

[0011] The present application can accurately identify the image change region by obtaining the current image frame data and the previous image frame data and calculating the inter-frame difference based on the preset pixel difference threshold, so as to avoid unnecessary overdrive processing of the static picture. The motion region data is obtained by threshold judgment based on the inter-frame difference data, which effectively improves the identification ability of the dynamic scene and provides a reliable basis for subsequent gray scale change rate calculation. The gray scale change rate is calculated according to the motion region data, and the gray scale change rate data is threshold intercepted, so that the system can accurately distinguish the response optimization target region and the non-target region, ensure that the overdrive optimization is applied to the region that really needs to be enhanced, and avoid excessive driving or detail loss caused by misjudgment. The response optimization target region data is continuously evaluated, and the continuous rectangular target region group is obtained by merging based on the continuity evaluation result, which can improve the integrity of the motion region identification and reduce the edge flicker and discontinuous optimization phenomenon caused by scattered regions. The temporary overdrive voltage value is obtained by calculating the gray scale value difference of the continuous rectangular target region group according to the current temperature data, so that the overdrive calculation can adapt to the change of environmental temperature and avoid the misalignment of the driving signal caused by the influence of temperature on the liquid crystal response speed. The temporary overdrive voltage value is pulse width modulated, wherein the response optimization target region data is high-frequency pulse width modulated to generate an optimization driving signal, and the non-target region data is standard pulse width modulated to generate a standard driving signal, so as to provide more accurate overdrive effect in the key region while ensuring the stability of the non-target region and preventing picture distortion caused by excessive enhancement. Based on the optimization driving signal and the standard driving signal, the liquid crystal display screen is partitioned and compensated for driving control, so that the overdrive processing is more refined, the driving matching degree of different regions is improved, and the partitioned driving control result is dynamically evaluated for definition to obtain display effect evaluation data, so that the entire system can be adaptively adjusted according to the evaluation result to achieve better dynamic picture display effect, effectively reduce motion blur, and improve the definition of the motion picture.

[0012] Preferably, the present application also provides a display optimization system for a liquid crystal display screen for executing the display optimization method for a liquid crystal display screen described above, wherein the display optimization system for a liquid crystal display screen comprises:

[0013] The frame difference detection module is configured to acquire current image frame data and previous image frame data, calculate inter-frame difference based on a preset pixel difference threshold, and perform threshold judgment based on the inter-frame difference data to obtain motion region data.

[0014] The gray scale change calculation module is configured to calculate a gray scale change rate based on the motion region data, and perform threshold clipping on the gray scale change rate data to obtain response optimization target region data and non-target region data.

[0015] The target region merging module is configured to perform continuity evaluation on the response optimization target region data, and perform merging processing based on the continuity evaluation result to obtain a continuous rectangular target region group.

[0016] The temperature adaptive calculation module is configured to acquire current temperature data, and calculate a gray scale value difference of the continuous rectangular target region group based on the current temperature data to obtain a temporary overdrive voltage value.

[0017] The partition modulation driving module is configured to perform pulse width modulation on the temporary overdrive voltage value, wherein the response optimization target region data is subjected to high-frequency pulse width modulation to generate an optimized driving signal, and the non-target region data is subjected to standard pulse width modulation to generate a standard driving signal.

[0018] The definition evaluation module is configured to perform partition compensation driving control on the liquid crystal display screen based on the optimized driving signal and the standard driving signal, and perform dynamic definition evaluation on the partition driving control result to obtain display effect evaluation data.

[0019] The application can accurately distinguish the motion area and the static area, reduce unnecessary processing, and optimize the subsequent display effect by obtaining the current image frame data and the previous image frame data, calculating the inter-frame difference, and effectively identifying the dynamic area. The gray scale change rate in the motion area can be accurately calculated, and threshold interception can be performed to effectively separate the response optimization target area and the non-target area, thereby more accurately performing dynamic optimization processing. The continuous rectangular target area group is successfully formed by continuously evaluating and merging the response optimization target area data, reducing the complexity of area division, and providing a clear area segmentation basis for subsequent voltage regulation and optimization. The temporary overdrive voltage value is obtained by calculating the gray scale value difference according to the current temperature data, realizing the adaptive adjustment of temperature, and effectively ensuring the stable display effect of the liquid crystal display screen under different temperature conditions. The response optimization target area and the non-target area are respectively subjected to high-frequency and standard pulse width modulation to generate an optimized driving signal and a standard driving signal, ensuring the efficiency and stability of the display, and avoiding unnecessary power waste. The partition compensation driving control of the liquid crystal display screen is based on the optimized driving signal and the standard driving signal, and the dynamic definition of the partition driving control result is evaluated to accurately evaluate the display effect and provide accurate feedback data for the final display quality optimization. BRIEF DESCRIPTION OF DRAWINGS

[0020] Other features, objects, and advantages of the application will become more apparent from the following detailed description of non-limiting embodiments made with reference to the drawings:

[0021] Figure 1 A step flow diagram of a display optimization method for a liquid crystal display screen according to the application;

[0022] Figure 2 A detailed step flow diagram of step S1 in the method; Figure 1

[0023] A detailed step flow diagram of step S2 in the method. Figure 3 DETAILED DESCRIPTION Figure 1 The technical method of the application will be described in detail below with reference to the drawings. Obviously, the described embodiments are part of the embodiments of the application, not all embodiments. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor belong to the scope of protection of the application.

[0024] The technical method of the application will be described in detail below with reference to the drawings. Obviously, the described embodiments are part of the embodiments of the application, not all embodiments. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor belong to the scope of protection of the application.

[0025] ​In addition, the accompanying drawings are included to provide a further understanding of the present application, and are incorporated in and constitute a part of this specification. The drawings illustrate embodiments of the present application and, together with the description, serve to explain the principles of the present application. In the drawings:

[0026] It is to be understood that, although terms such as "first", "second", and so on can be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, without departing from the scope of the exemplary embodiments, a first element can be referred to as a second element, and similarly a second element can be referred to as a first element. The term "and / or" as used herein includes any and all combinations of one or more of the associated associated items.

[0027] To achieve the above object, there is provided Figures 1 to 3 The present application provides a display optimization method for a liquid crystal display, comprising the following steps:

[0028] Step S1: acquiring current image frame data and previous image frame data, calculating inter-frame difference based on a preset pixel difference threshold; performing threshold judgment based on the inter-frame difference data to obtain motion region data;

[0029] Step S2: calculating a gray scale change rate according to the motion region data; performing threshold clipping on the gray scale change rate data to obtain response optimization target region data and non-target region data;

[0030] Step S3: performing continuity evaluation on the response optimization target region data, and performing merging processing based on the continuity evaluation result to obtain a continuous rectangular target region group;

[0031] Step S4: acquiring current temperature data; calculating a gray scale value difference of the continuous rectangular target region group according to the current temperature data to obtain a temporary overdrive voltage value;

[0032] Step S5: performing pulse width modulation on the temporary overdrive voltage value, wherein the response optimization target region data is subjected to high-frequency pulse width modulation to generate an optimized driving signal, and the non-target region data is subjected to standard pulse width modulation to generate a standard driving signal;

[0033] Step S6: performing partition compensation driving control on the liquid crystal display based on the optimized driving signal and the standard driving signal, and performing dynamic definition evaluation on the partition driving control result to obtain display effect evaluation data.

[0034] In the embodiment of the present application, referring to Figure 1 As shown in the figure, it is a step flow diagram of the display optimization method for the liquid crystal display screen, and the display optimization method for the liquid crystal display screen comprises the following steps in the example:

[0035] Step S1: obtaining current image frame data and previous image frame data, calculating inter-frame difference based on a preset pixel difference threshold; performing threshold judgment based on the inter-frame difference data to obtain motion region data;

[0036] In the embodiment of the present application, the display control unit of the liquid crystal display screen obtains the image frame data F(t) at the current time t and the image frame data F(t-1) at the previous time t-1 from the frame buffer through the image processor, wherein the image frame data comprises a gray scale value matrix of MxN pixel points, and the gray scale value at each pixel point position (i, j) is F(t, i, j) and F(t-1, i, j) respectively; then the inter-frame difference D(i, j) = |F(t, i, j)-F(t-1, i, j)| is calculated for each pixel point position, and a preset pixel difference threshold Th_diff (the threshold is specifically set to 15% of the gray scale value range, that is, for an 8-bit gray scale liquid crystal display screen, Th_diff = 38) is judged; when D(i, j) > Th_diff, the pixel point is marked as a motion pixel point, and a motion region binary matrix M(i, j) is generated, wherein M(i, j) = 1 represents a motion pixel point, and M(i, j) = 0 represents a non-motion pixel point; then an 8-neighbor connected component labeling algorithm is used to label M(i, j), and the same region identifier L_k is assigned to adjacent motion pixel points; for each connected region L_k, when the number of pixel points contained exceeds the area threshold Th_area (set to 100 pixel points), the region is retained as an effective motion region; finally, the minimum bounding rectangle of the effective motion region is calculated to determine the top-left corner coordinates (x_k, y_k) and the width and height (w_k, h_k) of each motion region, forming a motion region data set R = {R_k}, wherein R_k = (x_k, y_k, w_k, h_k, L_k).

[0037] Step S2: calculating the gray scale change rate according to the motion region data; performing threshold cutting on the gray scale change rate data to obtain response optimization target region data and non-target region data;

[0038] In the embodiment of the present application, the display control unit first extracts the gray scale values of the current frame F(t, i, j) and the previous frame F(t-1, i, j) for all pixel point positions (i, j) in each motion region R_k based on the motion region data set R={R_k}, calculates the gray scale change rate GCR(i, j) of each pixel point, where GCR(i, j)=(F(t, i, j)-F(t-1, i, j)) / △t, and △t represents the time interval between two frames (set to 16.67 ms corresponding to a refresh rate of 60 Hz); then performs absolute value conversion on the calculated gray scale change rate to obtain |GCR(i, j)|; then sets the upper and lower threshold values as Th_upper=20 gray scale values / ms and Th_lower=5 gray scale values / ms, respectively, performs threshold clipping processing on the gray scale change rate data, marks the pixel point as a response optimization target point when |GCR(i, j)|≥Th_upper, generates a target region binary matrix T(i, j)=1; marks the pixel point as a transition region point when Th_lower≤|GCR(i, j)|<Th_upper, T(i, j)=0.5; marks the pixel point as a non-target region point when |GCR(i, j)|<Th_lower, T(i, j)=0; then uses a region growing algorithm to merge adjacent target region points and transition region points to form a response optimization target region set O={O_p}, where each target region O_p contains the upper left corner coordinates (x_p, y_p), width and height (w_p, h_p), and the gray scale change rate matrix GCR_p of the pixel points in the region; at the same time, the pixel point set with all T(i, j)=0 is defined as a non-target region set N={N_q}, where each non-target region N_q also contains position coordinates, size information, and gray scale change rate data; finally, the response optimization target region data O and the non-target region data N are obtained.

[0039] Step S3: performing continuity evaluation on the response optimization target region data, and performing merging processing based on the continuity evaluation result to obtain a continuous rectangular target region group;

[0040] In the embodiment of the present application, the display control unit receives the response optimization target region data O={O_p}, first applies a time continuity evaluation algorithm to each target region O_p, the algorithm calculates a continuity index CI_p by analyzing the existence of the region in the last 5 frames, and the specific method is: tracking 4 frames from the current frame t, detecting whether there is a target region overlapping with O_p position by more than 60% in each frame, if there is a region meeting the condition in the t-k frame, the contribution value of the frame is (5-k) / 5, adding the contribution values of all frames to obtain CI_p, the value range is [0, 3]; then set the continuity threshold Th_cont=1.5, when CI_p≥Th_cont, mark the region as a stable target region, otherwise mark it as a transient target region; then perform target region merging processing, use distance threshold Th_dist=20 pixels as the judgment basis, analyze the spatial proximity of all stable target regions, when the minimum Euclidean distance between two stable target regions O_i and O_j is less than Th_dist, calculate the minimum bounding rectangle of the two regions, form a new merged region, the top-left corner coordinates of the merged region are min(x_i,x_j,y_i,y_j), and the bottom-right corner coordinates are max(x_i+w_i,x_j+w_j,y_i+h_i,y_j+h_j); repeat the region merging process until all adjacent regions are processed, finally obtain the continuous rectangular target region group C={C_m}, wherein each region C_m contains rectangular coordinate information (x_m,y_m,w_m,h_m), the average gray scale change rate avg_GCR_m in the region and the region continuity index CI_m.

[0041] Step S4: obtaining current temperature data; calculating the gray value difference of the continuous rectangular target region group according to the current temperature data, obtaining a temporary overdrive voltage value;

[0042] In the embodiment of the present application, the display control unit collects current temperature data T(x, y) of each region of the liquid crystal panel through a temperature sensor array, the temperature sensor array contains 16 evenly distributed temperature measurement points, and the temperature distribution map of the entire panel is obtained through a linear interpolation algorithm; then the continuous rectangular target region group C={C_m} is mapped with the temperature distribution map, and the average temperature value avg_T_m in each target region C_m is calculated; then from the liquid crystal response characteristic lookup table LUT pre-stored in the controller ROM, the temperature correction coefficient α_m = LUT(avg_T_m) is extracted according to the average temperature value avg_T_m and the gray scale change rate avg_GCR_m in the target region, the lookup table is constructed based on the experimental data of the response time change characteristics of the liquid crystal material at different temperatures, for example, when the temperature is 25℃, α=1.0, when the temperature drops to 15℃, α=1.4, and when the temperature rises to 35℃, α=0.8; then for each pixel point (i, j) in each target region C_m, according to its current gray scale value F(t, i, j), target gray scale value F(t+1, i, j), temperature correction coefficient α_m and pixel response characteristic curve P(i, j) at pixel point position (i, j), the temporary overdrive voltage value OD(i, j) =Vn+α_m×P(i, j)×|F(t+1, i, j)-F(t, i, j)| is calculated, wherein Vn is the standard drive voltage value corresponding to 5V; the temporary overdrive voltage values OD(i, j) of all pixel points in each target region calculated are organized into an overdrive voltage matrix OD.

[0043] Step S5: pulse width modulation is performed on the temporary overdrive voltage value, wherein the response optimization target region data is high-frequency pulse width modulated to generate an optimized drive signal, and the non-target region data is standard pulse width modulated to generate a standard drive signal;

[0044] In the embodiment of the present application, the display control unit receives the temporary overdrive voltage matrix OD, and divides the display screen area into response optimization target area and non-target area for differential processing. Firstly, for each pixel point (i, j) in the response optimization target area, the control unit uses high-frequency pulse width modulation technology to increase the standard 60Hz driving frequency to 120Hz, and each original refresh cycle of 16.67ms is divided into two sub-cycles. In the first sub-cycle, the overdrive voltage value OD(i, j) is applied, and the pulse width is τ1(i, j)=4.17×(OD(i, j) / Vmax)ms. In the second sub-cycle, the standard driving voltage Vn is applied, and the pulse width is τ2(i, j)=4.17×(1-(OD(i, j)-Vn) / (Vmax-Vn))ms, where Vmax is the maximum driving voltage of the system, which is 10V. For each pixel point in the non-target area, the control unit uses standard 60Hz pulse width modulation, and the pulse width is τs(i, j)=8.33×(Vn / Vmax)ms, and the duty cycle is fixed at 50%. Then, the control unit generates the corresponding driving waveform for each pixel point, including voltage amplitude, pulse width and frequency information. For the target area pixel point, the optimized driving signal DS_opt(i, j)=(OD(i, j), τ1(i, j), Vn, τ2(i, j), 120Hz) is generated. For the non-target area pixel point, the standard driving signal DS_std(i, j)=(Vn, τs(i, j), 60Hz) is generated. Finally, the control unit organizes the driving signals of all pixel points into a driving signal matrix DS, which contains the optimized driving signal and the standard driving signal.

[0045] Step S6: Based on the optimized driving signal and the standard driving signal, the liquid crystal display screen is partitioned and compensated for driving control, and the dynamic definition evaluation of the partition driving control result is performed to obtain display effect evaluation data.

[0046] In the embodiment of the present application, the display control unit receives the driving signal matrix DS, and differentiates driving control of each region through the liquid crystal display screen driving circuit; first, the control unit divides the display screen into a 16x12 driving block grid, each block size is 120x90 pixels, and each block is marked according to the driving signal type; when the proportion of optimized driving signal pixel points in the block exceeds 70%, the entire block is marked as an optimized block, otherwise it is marked as a standard block; then, the control unit performs partition driving control according to the block type, and uses the optimized driving signal DS_opt generated in step S5 for the optimized block, and uses the standard driving signal DS_std for the standard block; subsequently, the control unit performs smoothing processing on the boundary region of adjacent blocks, and gradually changes the driving signal strength in the boundary region with a width of 5 pixels, and the specific method is to calculate the driving voltage value by distance weighting in the transition region, voltage value OD_boundary(i,j)=OD1x(1-d / 5)+OD2xd / 5, wherein d is the distance of the pixel point to the boundary, and OD1 and OD2 are the driving voltage values of the two blocks; then, the control unit performs dynamic definition evaluation of the driving control result, including four steps: first, collect the display image after the current optimization driving, denoted as Img_opt; then, calculate the edge difference Diff_edge between Img_opt and the previous frame image, specifically using the Sobel edge detection operator to extract the edge feature map of the two frames of images, and calculating the difference value; subsequently, use the motion region weighted root mean square error calculation WMSE, and give a higher weight 0.8 to the motion region and a weight 0.2 to the non-motion region; finally, the definition index Clarity=0.6xDiff_edge+0.4x(1-WMSE) is obtained by combining the edge difference and WMSE, and the score range is 0-1; the control unit records the definition index and the driving parameters of each block as display effect evaluation data, and stores it in the evaluation database.

[0047] The application can accurately identify the image change area, and avoid unnecessary overdrive processing of the static picture. The threshold value judgment based on the inter-frame difference data obtains the motion area data, effectively improves the identification ability of the dynamic scene, and provides a reliable basis for subsequent gray scale change rate calculation. The gray scale change rate is calculated according to the motion area data, and the gray scale change rate data is threshold intercepted, so that the system can accurately distinguish the response optimization target area and the non-target area, ensure that the overdrive optimization acts on the area that really needs to be enhanced, and avoid excessive driving or detail loss caused by misjudgment. The response optimization target area data is continuously evaluated, and the continuous rectangular target area group is obtained based on the continuity evaluation result, which can improve the integrity of the motion area identification, reduce the edge flicker and discontinuous optimization phenomenon caused by scattered areas. The current temperature data is obtained, and the gray scale value difference of the continuous rectangular target area group is calculated according to the current temperature data to obtain a temporary overdrive voltage value, so that the overdrive calculation can adapt to the change of environmental temperature, and the driving signal misalignment caused by the influence of temperature on the response speed of liquid crystal is avoided. The temporary overdrive voltage value is pulse width modulated, wherein the response optimization target area data is high-frequency pulse width modulated to generate an optimized driving signal, and the non-target area data is standard pulse width modulated to generate a standard driving signal, so as to provide more accurate overdrive effect in the key area, while ensuring the stability of the non-target area and preventing picture distortion caused by excessive enhancement. Based on the optimized driving signal and the standard driving signal, the liquid crystal display screen is partitioned and compensated for driving control, so that the overdrive processing is more refined, the driving matching degree of different areas is improved, and the dynamic definition evaluation result of the partition driving control result is obtained to ensure that the whole system can be adaptively adjusted according to the evaluation result, realize better dynamic picture display effect, effectively reduce motion blur, and improve the definition of motion picture.

[0048] Preferably, step S1 comprises the following steps:

[0049] Step S11: acquiring current image frame data and previous image frame data, and performing noise filtering processing to obtain a standardized image frame data set;

[0050] Step S12: performing pixel-level comparison calculation on the standardized image frame data set based on a preset pixel difference threshold to obtain pixel difference matrix data;

[0051] Step S13: performing adjacent pixel clustering on the pixel difference matrix data to obtain area difference data;

[0052] Step S14: performing binaryzation on the area difference data based on a preset motion judgment threshold to obtain preliminary motion area marker data;

[0053] Step S15: morphological dilation and corrosion operation is performed on the preliminary motion region marking data to obtain optimized motion region data;

[0054] Step S16: motion region edge data is extracted from the optimized motion region data;

[0055] Step S17: pixel expansion is performed on the motion region edge data to obtain motion region data.

[0056] In the embodiment of the present application, the display control unit first acquires the current image frame data and the previous image frame data through the display driver interface, and each frame of data contains 1920*1080 pixel points of RGB color values; then the display control unit performs two-stage noise filtering processing: in the first stage, a 3*3 Gaussian filter with the kernel parameter [0.0625, 0.125, 0.0625; 0.125, 0.25, 0.125; 0.0625, 0.125, 0.0625] is used to perform convolution operation on the two frames of images to remove high-frequency noise; in the second stage, brightness equalization processing is performed, the RGB value of each pixel point is converted to the YUV color space, only the Y component is retained as the brightness value, and a standardized image frame data set is generated; the display control unit calculates the difference value of each pixel position for the standardized current frame and the previous frame data, and the difference value formula is abs(Ycurrent(x,y)-Yprevious(x,y)), wherein Y represents the brightness value, and x and y are pixel coordinates; then a preset pixel difference threshold is set to 15 (the 8-bit brightness value range is 0-255), all pixel difference values are compared, a pixel difference matrix data is generated, and each element value in the matrix is the current difference value divided by the difference threshold; the display control unit performs an adjacent pixel clustering algorithm on the pixel difference matrix data, specifically uses the region growing method, takes the pixel with a difference value greater than 0.8 as a seed point, gradually expands and connects adjacent pixel points with a difference value greater than 0.5, and stops until it cannot continue to expand; each clustering region is assigned a unique identification number to form region difference data; the display control unit sets a preset motion judgment threshold to 100 pixel points, detects the number of pixel points contained in each clustering region in the region difference data, if the number exceeds the motion judgment threshold, marks all pixel points in the region as motion pixels (value 1), otherwise marks them as non-motion pixels (value 0), and generates preliminary motion region marking data; the display control unit applies morphological operation to the preliminary motion region marking data, first performs 2 times of expansion operation of a 3*3 structure element to fill small holes in the motion region, and then performs 1 time of corrosion operation of a 3*3 structure element to remove isolated noise points, to obtain optimized motion region data; the display control unit uses the Sobel edge detection operator to perform convolution operation on the optimized motion region data to extract the edge contour of the motion region, and the specific operation includes first applying the horizontal direction Sobel operator [1,2,1; 0,0,0; -1,-2,-1], then applying the vertical direction Sobel operator [1,0,-1; 2,0,-2; 1,0,-1], taking the square root of the sum of squares of the results of the two directions as the edge intensity, and then passing through a threshold of 0.The binarization processing of 5 obtains motion region edge data; the display control unit performs a pixel expansion operation on the motion region edge data, expands the width of 5 pixels outward, the expansion method is to fill the pixel with a value of 1 from each edge pixel point to eight directions (horizontal, vertical, diagonal line), the operation is repeated for 5 times, and finally the expanded edge data is combined with the optimized motion region data to obtain the final motion region data.

[0057] The present application can effectively reduce the error caused by the noise of the photosensitive element or the compression artifact by performing noise filtering processing on the current image frame data and the previous image frame data, and ensures the accuracy of subsequent calculation. The pixel level comparison calculation based on the preset pixel difference threshold enables the system to accurately detect the inter-frame change and avoid false judgment caused by slight brightness fluctuation or noise interference. The adjacent pixel clustering of the pixel difference data helps to enhance the motion feature extraction at the region level, improve the integrity of the motion region, and avoid the false judgment caused by isolated pixels. The region difference data is binarized based on the preset motion judgment threshold, so that the system can effectively distinguish the motion region and the static region, and reduce the fuzzy judgment in the motion recognition process. The morphological dilation and corrosion operation on the preliminary motion region marking data can smooth the region boundary, fill the gap caused by noise, and improve the stability and continuity of the motion region. The edge data of the optimized motion region is extracted, so that the subsequent processing can more accurately analyze the morphological features of the motion region, and help to improve the edge detail optimization capability. The pixel expansion of the motion region edge data can ensure that the coverage range of the motion region is more complete, reduce the boundary truncation problem, make the optimized motion region data more consistent with the real motion region, and ensure the accuracy of the subsequent overdrive processing.

[0058] Preferably, step S2 comprises the following steps:

[0059] Step S21: performing pixel-level traversal on the motion region data to obtain a motion region pixel coordinate set;

[0060] Step S22: extracting a current gray scale value matrix from the current image frame data based on the motion region pixel coordinate set;

[0061] Step S23: extracting a previous gray scale value matrix from the previous image frame data based on the motion region pixel coordinate set;

[0062] Step S24: performing difference operation on the current gray scale value matrix and the previous gray scale value matrix to obtain a gray scale difference matrix;

[0063] Step S25: performing ratio calculation based on the gray scale difference matrix and the current gray scale value matrix, and performing long-term effect evaluation to obtain gray scale change trend data;

[0064] Step S26: Smooth the gray scale change trend data to obtain gray scale change rate data;

[0065] Step S27: Compare and classify the gray scale change rate data by threshold to obtain preliminary target region marking data and non-target region data;

[0066] Step S28: Perform boundary refinement processing on the preliminary target region marking data to obtain optimized target region data;

[0067] Step S29: Perform response time gradient analysis on the optimized target region data to obtain response optimized target region data.

[0068] In the embodiment of the present application, the display control unit receives the motion region data (binary matrix, size 1920x1080) obtained in the previous step, traverses the matrix, and records the corresponding pixel coordinates (x, y) when the value is 1. The pixel coordinates in all motion regions are stored as a motion region pixel coordinate set. These coordinates are organized as a two-dimensional array structure for quick access in subsequent steps. Based on the motion region pixel coordinate set, the display control unit extracts the current image frame data. For each pixel (x, y) in the coordinate set, it queries the gray scale value in the current image frame. The gray scale value extraction method is to convert the RGB three channels to a single channel gray scale value according to the formula Gray=0.299×R+0.587×G+0.114×B to form a current gray scale value matrix, which only contains the gray scale values of the pixels in the motion region. The display control unit uses the same coordinate set and gray scale conversion method to extract the gray scale values of the corresponding pixels from the previous image frame data to form a previous gray scale value matrix. The display control unit performs a pixel-level difference operation on the current gray scale value matrix and the previous gray scale value matrix. The difference calculation formula is Diff(x, y)=Current(x, y)-Previous(x, y), and the gray scale difference matrix is obtained, which records the change amount of the gray scale value of each pixel in the motion region. The display control unit first calculates the gray scale change ratio Ratio(x, y)=Diff(x, y) / Current(x, y), and then performs long-term effect evaluation. This evaluation analyzes the gray scale change history of the same position pixel in the last 5 frames. The specific method is as follows: for each pixel in the current motion region, extract the gray scale values of the same position in the last 4 frames, calculate the cumulative change trend Trend(x, y)=∑(0≤i≤4)[w(i)×(Frame(t-i,x,y)-Frame(t-i-1,x,y))] and the weight coefficient w is [0.4, 0.3, 0.15, 0.1, 0.05]. According to the consistency of the cumulative trend and the current frame change, the gray scale change trend data is generated. The display control unit applies a 5x5 Gaussian smoothing filter to the gray scale change trend data. The filter kernel parameters are based on a standard deviation of 0.8 generate, perform two-dimensional convolution operation, eliminate local mutation, obtain smoothed gray scale change rate data; the display control unit sets the upper threshold 25 and the lower threshold 10, and classifies the gray scale change rate data into three levels: when the absolute value of the gray scale change rate is greater than the upper threshold, it is marked as a high-priority target area (value 2); when the absolute value of the gray scale change rate is between the upper and lower thresholds, it is marked as a low-priority target area (value 1); when the absolute value of the gray scale change rate is less than the lower threshold, it is marked as a non-target area (value 0), thereby obtaining preliminary target area marking data and non-target area data; the display control unit performs region boundary refinement processing, first applies an 8-neighborhood connected region marking algorithm to connect adjacent target area pixels into blocks, then applies an active contour algorithm to each block to align the boundary along the direction of the maximum gray scale gradient, accurately positioning the region boundary, and finally removes isolated blocks with an area less than 30 pixels to obtain optimized target area data; the display control unit performs response time gradient analysis on each block in the optimized target area data, calculates the theoretical response time of each pixel based on the gray scale starting value and target value by querying the built-in liquid crystal response time parameter table, marks the pixel as a response optimization candidate point when the response time exceeds 16 milliseconds (corresponding to a 60Hz refresh rate), and then based on spatial continuity, all connected response optimization candidate points are combined into response optimization target area data.

[0069] The present application can ensure the accuracy of subsequent calculations by traversing the motion region data at the pixel level and extracting the motion region pixel coordinate set, avoid redundant processing caused by global calculation, and improve calculation efficiency. Based on the motion region pixel coordinate set, the gray scale value matrices of the current and previous image frames are extracted, so that the calculation of gray scale change is based on the actual motion region, improving the relevance of the data. Difference operation is performed on the gray scale value matrices of the current and previous frames to accurately obtain the brightness change of each pixel point, providing a basis for further calculation. Based on the gray scale difference matrix and the current gray scale value matrix, the ratio is calculated, and combined with the long-term effect evaluation, so that the system can consider the historical trend of gray scale change, avoid misjudgment caused by short-term change, and improve the stability of motion detection. Smooth the gray scale change trend data to effectively suppress transient noise, ensure the continuity of the gray scale change rate data, and improve the reliability of the data. The gray scale change rate data is classified by threshold comparison, so that the target area and non-target area are more accurately distinguished, reducing the impact of misjudgment. The boundary refinement processing of the preliminary target area marking data can optimize the region edge to make it more consistent with the actual motion characteristics, avoiding calculation errors caused by fuzzy boundaries. Based on the response time gradient analysis, the target area data is optimized, so that the final response optimization target area can accurately correspond to the motion part that needs to be optimized, improving the accuracy of the overdrive processing.

[0070] Preferably, the continuity evaluation on the response optimization target region data in step S3 comprises:

[0071] performing pixel connectivity analysis on the response optimization target region data to obtain initial connected region marking data;

[0072] performing clustering processing on the initial connected region marking data to obtain target region clustering data, wherein a minimum region area limit of the clustering processing is less than or equal to 16 pixels;

[0073] performing region shape feature data extraction on the target region clustering data;

[0074] performing rectangle fitting calculation on the region shape feature data to obtain initial rectangular region data;

[0075] a fitting error in the rectangle fitting calculation is less than or equal to 15%, and a rotation angle limit is 0°, 45°, 90°, and 135°.

[0076] performing overlap degree calculation on the initial rectangular region data to obtain rectangular overlap degree data, wherein an overlap ratio threshold limit in the overlap degree calculation is less than or equal to 30%.

[0077] In the embodiment of the present application, the display control unit performs pixel connectivity analysis on the response optimization target region data, traverses each pixel point using a two-dimensional scanning algorithm, checks the 8-neighbor connectivity of each pixel marked as a response optimization candidate point, classifies mutually connected pixel points into the same label group, generates a unique region identifier, the identifier represents different connected regions in the form of an integer (increasing from 1), and finally forms initial connected region label data, which is a two-dimensional matrix, and the value of each element in the matrix is the identifier of the connected region to which the pixel belongs or 0 (indicating a non-response optimization region); the display control unit performs clustering processing on the initial connected region label data, first counts the number of pixels corresponding to each identifier to form a region area statistics table, then sets the minimum region area limit to 16 pixels, for regions with an area less than or equal to 16 pixels, the display control unit performs a K-means clustering algorithm, calculates the Euclidean distance of these small regions and surrounding large regions (with an area greater than 16 pixels), the distance calculation formula is D=sqrt((x1-x2)²+(y1-y2)²), where (x1, y1) and (x2, y2) are the centroid coordinates of the two regions, each small region is merged into the nearest large region, and target region clustering data is formed; the display control unit extracts region shape feature data from the target region clustering data, calculates the following feature parameters for each clustering region: boundary point set, centroid coordinates (cx, cy)=average(x, y), area A=count(pixels), perimeter P=count(boundary_pixels), compactness C=4π×A / P², principal axis direction θ=0.5*arctan(2μ11 / (μ20-μ02)), wherein μpq is a central moment of order (p, q), the characteristic parameters constitute the region shape feature data; the display control unit performs rectangular fitting calculation on the region shape feature data, limits the principal axis direction θ of each region to one of 0°, 45°, 90° and 135°, selects the standard angle closest to the original direction, and then constructs a rectangular boundary along the direction, the length and width of the rectangle are determined by the maximum projection length of the region in the principal axis direction and the vertical direction respectively, the ratio of the actual area covered by the rectangle to the original area is calculated, and the fitting error is ensured to be less than or equal to 15%, if the error exceeds the threshold, the boundary is adjusted, and finally the initial rectangular region data is obtained; the display control unit performs overlap calculation on the initial rectangular region data, for each pair of adjacent rectangular regions R1 and R2, the overlap area S_overlap=Area(R1∩R2) is calculated, and then the overlap ratio Overlap_ratio=S_overlap / min(Area(R1),Area(R2)) is calculated, the overlap ratio threshold is set to 30%, when Overlap_ratio is less than or equal to 30%, the two rectangular regions are retained; when Overlap_ratio is greater than 30%, the two rectangular regions are merged into one larger rectangle, and the boundary of the merged rectangle is the minimum circumscribed rectangle of the two original rectangles, thereby obtaining rectangular overlap data, which contains the overlap of each pair of rectangular regions and the merging decision information.

[0078] The application can effectively identify continuous pixel regions, improve the integrity of the target region, and avoid detection errors caused by isolated pixels by performing pixel connectivity analysis on the response optimization target region data. Based on the initial connected region marking data, clustering processing is performed, and the minimum region area is limited, so that only regions with sufficient significance are retained, thereby reducing the interference of irrelevant regions and improving the accuracy of target region screening. The region shape feature data is extracted from the target region clustering data, so that the subsequent rectangular fitting calculation can be based on the real morphological characteristics, and the fitting effect is improved. The region shape feature data is subjected to rectangular fitting calculation, and the fitting error and the rotation angle are limited, so that the generated rectangular region can better adapt to the pixel arrangement characteristics of the liquid crystal display screen, and the region positioning accuracy is improved. The overlap calculation is performed on the initial rectangular region data, and the overlap ratio threshold is limited, so that the excessively overlapped regions can be identified and further optimized, and unnecessary signal enhancement or information loss caused by improper region division is avoided.

[0079] Especially important is that the pixel connectivity analysis on the response optimization target region data comprises:

[0080] The response optimization target region data is subjected to binarization processing to obtain target region mask data;

[0081] The target region mask data is subjected to connected domain primary screening to obtain an initial connected marking matrix;

[0082] The initial connected marking matrix is subjected to boundary correction to obtain corrected connected region data;

[0083] The corrected connected region data is subjected to small region filtering to obtain initial connected region marking data.

[0084] In the embodiment of the present application, the display control unit performs binarization processing on the response optimization target region data, first sets a threshold T=0.5, traverses each element in the response optimization target region data matrix, sets the element to 1 when the element value is greater than the threshold T, otherwise sets it to 0, forms a two-dimensional matrix containing only 0 and 1, the element with a value of 1 in the matrix represents a pixel point that needs to be optimized in response time, and the element with a value of 0 represents a pixel point that does not need to be optimized, thereby obtaining target region mask data, the size of the mask data is the same as the original image frame, which is 1920*1080; the display control unit performs connected domain preliminary screening on the target region mask data, and uses a two-pass scanning algorithm to mark. In the first pass, scanning is performed from the top left corner by row, for each pixel with a value of 1, checking the 4-neighborhood pixels on the left and above that have been scanned, if all the neighborhood pixels are 0, assigning a new mark value to the current pixel, if there is a pixel with a value of 1 in the neighborhood, marking the current pixel with the same mark value as the adjacent marked pixel, and recording the equivalence relationship; in the second pass, according to the equivalence relationship table established in the first pass, merging the marks with equivalence relationship, ensuring that each connected region has a unique mark value, thereby obtaining an initial connected mark matrix; the display control unit performs boundary correction on the initial connected mark matrix, first calculates the boundary point set of each connected region, the boundary point is defined as a point whose at least one 8-neighborhood pixel does not belong to the current region, then applies a gradient vector flow algorithm to each boundary point, which is based on the gray level gradient field of the current image frame, iteratively adjusts the position of the boundary point, the iteration formula is P(t+1)=P(t)+αV(P(t)), where P(t) is the position of the boundary point at the t-th iteration, V is the gradient vector field, and α is the step size parameter set to 0.2, the iteration number is set to 10 times, ensuring that the boundary point is located at the maximum gray level gradient, thereby obtaining corrected connected region data; the display control unit filters small regions from the corrected connected region data, first counts the number of pixels in each connected region as the area of the region, then sets a minimum area threshold Amin=8 pixels, for a connected region with an area less than Amin, calculates the number of boundary contact pixels with a neighboring large region (area greater than or equal to Amin), if the proportion of contact pixels to the perimeter of the small region is greater than 40%, the small region is merged into the neighboring large region, if the contact proportion is less than or equal to 40%, the mark value of the region is set to 0, i.e. removed from the response optimization target region, after small region filtering, the mark values of the remaining connected regions are renumbered to ensure continuous mark values, thereby obtaining initial connected region mark data.

[0085] The application makes the features of the target region more prominent by binarizing the response optimization target region data, which is helpful for subsequent connectivity analysis and region extraction. The initial connectivity screening based on the target region mask data can quickly identify the connected regions, improve the efficiency of region extraction, and reduce the interference of isolated noise. The boundary correction of the initial connected marking matrix makes the extracted target region have more accurate boundary profile, avoiding the morphological distortion caused by edge breakage or noise. The small region filtering of the corrected connected region data can effectively remove noise interference and irrelevant small regions, ensuring that the final extracted connected region is more stable and meets the optimization requirements.

[0086] Preferably, the merging processing based on the continuity evaluation result in step S3 comprises:

[0087] The rectangular overlap degree data is filtered based on an overlap threshold value, and when the rectangular overlap degree data is greater than the overlap threshold value, the rectangular region data corresponding to the rectangular overlap degree data is merged to obtain merged rectangular region data;

[0088] The overlap threshold value is limited to between 30% and 50%, if the rectangular overlap degree data is less than 30% overlap degree, it will lead to unrelated regions being merged by mistake, and if the rectangular overlap degree data is greater than 50% overlap degree, it will lead to regions that are obviously related cannot be merged;

[0089] The merged rectangular region data is subjected to pixel boundary expansion to obtain expanded boundary rectangular region data;

[0090] The expanded boundary rectangular region data is subjected to pixel alignment processing to obtain aligned rectangular region data;

[0091] The aligned rectangular region data is subjected to spatial position analysis and grouping processing to obtain a continuous rectangular target region group.

[0092] In the embodiment of the present application, the display control unit filters the rectangular overlap data based on the overlap threshold value, and sets the overlap threshold value to 40%. The threshold value is the optimal value selected in the range of 30%-50%. The system confirms in the test process that when the overlap threshold value is lower than 30%, the irrelevant regions are easily merged by mistake, resulting in excessive fusion; and when the overlap threshold value is higher than 50%, the obviously related regions cannot be merged, resulting in fragmentation. The display control unit iterates all rectangular pairs, calculates the overlap Oij of each rectangular pair Mi and Mj, that is, Oij=Area(Mi∩Mj) / min(Area(Mi),Area(Mj)), and when Oij is greater than 40%, a merging operation is performed: the upper left corner coordinates of the new rectangle are min(Mi.left, Mj.left) and min(Mi.top, Mj.top), and the lower right corner coordinates are max(Mi.right, Mj.right) and max(Mi.bottom, Mj.bottom), and Mi and Mj are removed from the rectangular list, and the newly merged rectangle is added to the list. This process is repeated until there is no rectangular pair that meets the merging condition, and the merged rectangular region data is obtained. The display control unit performs pixel boundary expansion on the merged rectangular region data. First, the boundary pixel gray scale gradient of each rectangular region is calculated, and the gray scale gradient calculation formula is G(x, y)=√((Gray(x+1, y)-Gray(x-1, y))²+(Gray(x, y+1)-Gray(x, y-1))²). Then, the expansion parameter δ is set to 3 pixels, and the four boundaries of each rectangle are expanded by δ pixels outward. However, the following conditions must be met during the expansion process: the gray scale gradient G(x, y) of the pixels in the expanded region is less than the threshold value Gthreshold=15, the expansion does not exceed 10% of the original rectangular side length, and the expanded rectangle does not overlap with other unmerged rectangles. Thus, the expanded boundary rectangular region data is obtained. The display control unit performs pixel alignment processing on the expanded boundary rectangular region data. Based on the pixel grid of the current display screen, the rectangular region coordinates are aligned and adjusted. First, the upper left corner coordinates (x1, y1) and the lower right corner coordinates (x2, y2) are respectively rounded down and rounded up to ensure that all related pixels are covered. Then, according to the sub-pixel arrangement structure of the display screen, the x-coordinate of the upper left corner is adjusted to a multiple of 8, and the y-coordinate is adjusted to a multiple of 4. The right lower corner coordinates are also adjusted accordingly to ensure that the rectangular region can be aligned with the data block of the display screen driving circuit at the hardware level, thereby improving the processing efficiency. Thus, the aligned rectangular region data is obtained. The display control unit analyzes and processes the aligned rectangular region data in groups. First, a spatial index structure (such as an R-tree) is established, and all rectangular regions are inserted into the structure. Then, a spatial clustering algorithm is executed. For each rectangular region Mi, the spatial proximity regions (distance less than 5% of the display screen width) are queried, and the relative position relationship and shape similarity of each region are calculated. The similarity calculation formula is S(Mi, Mj)=0.6x(1-|Wi-Wj| / max(Wi,Wj))+0.4x(1-|Hi-Hj| / max(Hi,Hj)), wherein Wi and Hi are the width and height of the rectangle Mi, respectively, and the two rectangles are assigned to the same group when the similarity S(Mi, Mj) is greater than 0.75 and the spacing of the two rectangles in the horizontal or vertical direction is less than 2 times the smaller rectangle side length, thereby forming a continuous rectangular target region group.

[0093] The present application ensures that the merging process is only for regions with high relevance by screening the rectangular overlap data based on an overlap threshold, thereby avoiding display distortion caused by false merging, while preventing the influence of an excessively high threshold limit on the fusion of relevant regions. Reasonably setting the overlap threshold range optimizes the accuracy of region merging and ensures that the final extracted target region meets the display optimization requirements. Expanding the pixel boundary of the merged rectangular region data makes the region boundary smoother, reduces target loss caused by boundary truncation, and improves the stability of subsequent calculations. Through pixel alignment processing, the rectangular region is consistent with the display grid, improving the calculation accuracy of the display signal and optimizing the driving control effect. Spatial position analysis and grouping processing are performed on the aligned rectangular region data, making the structure of the continuous target region more reasonable and ensuring that the final optimization result has better integrity and consistency in the display picture.

[0094] Especially important is that the screening of the rectangular overlap data based on the overlap threshold comprises:

[0095] Screening the rectangular overlap data set based on a preset overlap threshold to obtain rectangular overlap data that meets the merging condition;

[0096] Rectangular region data matching based on the rectangular overlap data that meets the merging condition to obtain a group of rectangular region data to be merged;

[0097] Boundary calculation on the group of rectangular region data to be merged to obtain merged rectangular region data.

[0098] In the embodiment of the present application, the display control unit filters the rectangular overlap degree dataset based on the preset overlap threshold value. First, the preset overlap threshold value T=40% is set, which is verified to effectively balance the merging accuracy and region integrity. The display control unit traverses each record in the rectangular overlap degree dataset, which contains the overlap degree values Oij of all rectangular pairs (Ri, Rj). It checks whether each overlap degree value Oij is greater than the preset overlap threshold value T. When Oij>T, the rectangular pair is marked as meeting the merging condition, and the identifier of the rectangular pair and the corresponding overlap degree value are recorded to form the rectangular overlap degree data that meets the merging condition. The data structure contains triplets (i, j, Oij), indicating that the overlap degree of the rectangular Ri and Rj is Oij and meets the merging condition. The display control unit performs rectangular region data matching based on the rectangular overlap degree data that meets the merging condition. First, an undirected graph G=(V, E) is constructed, where the vertex set V contains all the identifiers of the rectangles, and the edge set E contains the rectangular pairs that meet the merging condition. The weight of the edge is the corresponding overlap degree value. Then, the maximum spanning tree algorithm (such as Kruskal's algorithm) is applied. On the premise of maintaining the connectivity of the graph, the edges with the largest overlap degree are selected for connection to avoid forming loops and ensure that each rectangle is merged with at most one rectangle with the largest overlap degree, preventing over-fusion caused by chain merging. Finally, the to-be-merged rectangular region data group is obtained, which consists of multiple disjoint rectangular pair sets. The rectangles in each set will be merged into a larger rectangle. The display control unit calculates the boundaries of the to-be-merged rectangular region data group. For each to-be-merged rectangular set {R1, R2,..., Rn}, the minimum circumscribed rectangle is calculated as follows: the top-left corner coordinates (x1, y1) = min(R1.x1, R2.x1,..., Rn.x1), min(R1.y1, R2.y1,..., Rn.y1), and the bottom-right corner coordinates (x2, y2) = max(R1.x2, R2.x2,..., Rn.x2), max(R1.y2, R2.y2,..., Rn.y2). Then, it checks whether the size of the merged rectangle meets the display control unit's limit conditions on the size of the rectangle: the aspect ratio is not more than 5:1 or 1:5, and the area is not more than 1 / 8 of the original image frame area. If the limit is exceeded, the recursive bisection method is applied to divide the to-be-merged set into two subsets, and the minimum circumscribed rectangle is calculated for each subset. This process is repeated until all merged rectangles meet the limit conditions. Finally, the merged rectangular region data is obtained, which contains the boundary coordinates of all merged rectangles and the corresponding list of original rectangular identifiers.

[0099] The present application effectively ensures that only the rectangular regions meeting the merging condition participate in subsequent merging processing by screening the rectangular overlap data set based on a preset overlap threshold, avoids the false merging of irrelevant regions, and thus improves the accuracy of region matching. The rectangular region data matching is performed based on the rectangular overlap data meeting the merging condition, so that the region merging is more in line with the actual display requirements and avoids unnatural display or information loss caused by matching errors. The boundary calculation on the to-be-merged rectangular region data set helps to accurately determine the boundary of the merged region, improves the display effect after the region merging, and optimizes the continuity and stability of the display region.

[0100] Preferably, step S4 comprises the following steps:

[0101] Step S41: acquiring current temperature data; performing mapping calculation on the current temperature data to obtain a liquid crystal temperature compensation coefficient;

[0102] Step S42: performing difference calculation on the current gray scale value and the target gray scale value of each region in the continuous rectangular target region group to obtain gray scale difference data;

[0103] Step S43: performing index query on the gray scale conversion lookup table based on the gray scale difference data and the temperature compensation parameter to obtain a basic overdrive voltage value;

[0104] Step S44: performing dynamic response characteristic adjustment and mode optimization on the basic overdrive voltage value to obtain a temporary overdrive voltage value.

[0105] In the embodiment of the present application, the display control unit acquires current temperature data, reads real-time temperature value through the temperature sensor integrated on the frame of the liquid crystal panel, the sampling precision is 0.1 ℃, the sampling frequency is 1 time per frame, the analog signal output by the sensor is converted into digital quantity through 12-bit ADC, and the temperature original data is obtained; then the current temperature data is mapped and calculated, according to the temperature-viscosity characteristic curve of the liquid crystal material, the temperature value T is mapped to the liquid crystal temperature compensation coefficient α, the mapping formula is α = 1 + k × (T-T0) 2, wherein T0 is the nominal working temperature of the liquid crystal 25 ℃, k is the temperature coefficient -0.0015 / ℃ 2, when the temperature is lower than T0, the activity of the liquid crystal molecules slows down, the response time increases, α > 1; when the temperature is higher than T0, the activity of the liquid crystal molecules accelerates, the response time decreases, α < 1, and thus the liquid crystal temperature compensation coefficient is obtained; the display control unit carries out difference calculation on the current gray scale value and the target gray scale value of each region in the continuous rectangular target region group, first reads the pixel value in the corresponding rectangular region in the current frame data and the next frame data from the frame buffer, converts the RGB value into the gray scale value, the conversion formula is Gray = 0.299 × R + 0.587 × G + 0.114x B, then calculate the gray level difference of each pixel point ΔGray = Next_Gray - Current_Gray, statistical analysis of the difference value in each rectangular region, calculate the average difference μ, standard deviation σ and difference distribution histogram, according to the histogram distribution characteristics of the rectangular region is divided into three categories: rising area (ΔGray> 0), falling area (ΔGray<0) and mixed area (ΔGray distribution across 0), thus obtaining the gray level difference data; display control unit based on gray level difference data and temperature compensation parameter index query gray scale conversion lookup table, gray scale conversion lookup table is a three-dimensional matrix LUT[Start_Gray][End_Gray][Temp_Index], storage of different starting gray value, target gray value and temperature conditions of the theoretical overdrive voltage value, for each rectangular area of the dominant gray level difference type, query the corresponding overdrive voltage value, query method is: for rising area, query V_up = LUT[Current_Gray][Next_Gray][Temp_Index] x α; for falling area, query V_down = LUT[Current_Gray][Next_Gray][Temp_Index] x α; for mixed area, respectively calculate the overdrive voltage value of the rising and falling part, then according to the area proportion weighted average, thus obtaining the basic overdrive voltage value; display control unit for dynamic response characteristic adjustment and mode optimization of the basic overdrive voltage value, first according to the motion characteristics of the current display content, such as speed, acceleration and direction continuity, the basic overdrive voltage value is corrected, the correction formula is V_adjusted = V_base x (1 + β x Speed + γ x Accel), wherein β is the speed coefficient 0.05 / (pixel / frame), γ is the acceleration coefficient 0.02 / (pixel / frame²); then analyze the display content type, the overdrive mode is optimized to one of the four preset modes: standard mode (balanced response time and overshoot), game mode (minimize response time, allow larger overshoot), video mode (optimize gray level transition smoothness) and text mode (minimize overshoot, improve text clarity), each mode corresponds to different compensation parameter set, by applying the selected mode parameter set to V_adjusted for final adjustment, get temporary overdrive voltage value.

[0106] The present application can obtain and map the current temperature data, accurately obtain the liquid crystal temperature compensation coefficient, ensure the influence of temperature fluctuation on the liquid crystal display performance is effectively compensated, and improve the consistency and stability of the display. The difference between the current gray scale value and the target gray scale value of each region in the continuous rectangular target region group is calculated to ensure the accurate grasp of the gray scale difference between different regions and provide reliable data basis for the subsequent adjustment of the overdrive voltage value. The gray scale conversion lookup table is indexed and queried based on the gray scale difference data and the temperature compensation parameter to obtain accurate basic overdrive voltage value for the specific needs of each region, ensuring the accurate matching of the overdrive voltage. The dynamic response characteristic adjustment and mode optimization of the basic overdrive voltage value make the temporary overdrive voltage value more suitable for the display needs of different regions, thereby optimizing the display effect and reducing the blur or ghosting phenomenon in the dynamic picture.

[0107] Preferably, step S5 comprises the following steps:

[0108] Step S51: performing voltage range limiting processing on the temporary overdrive voltage value to obtain a safe voltage value;

[0109] Step S52: performing pulse width calculation on the response optimization target region data based on the safe voltage value to obtain target region pulse width modulation parameters;

[0110] Step S53: performing drive waveform conversion on the target region pulse width modulation parameters to obtain the optimized drive signal of the target region;

[0111] Step S54: performing standard voltage value calculation on the non-target region data to obtain a standard region voltage value;

[0112] Step S55: performing standard pulse width modulation based on the standard region voltage value to obtain standard region pulse width modulation parameters;

[0113] Step S56: performing drive waveform conversion on the standard region pulse width modulation parameters to obtain the standard drive signal of the standard region.

[0114] In the embodiment of the present application, the display control unit performs voltage range limiting processing on the temporary overdrive voltage value, first determines that the voltage output range of the liquid crystal driving chip is Vmin=0V to Vmax=5V, then performs truncation limiting on the temporary overdrive voltage value V_temp, sets V_temp to Vmin when V_tempVmax, sets V_temp to Vmax, then performs voltage slope limiting, calculates the voltage change rate dV / dt of the pixels at the same position in adjacent two frames, when the change rate exceeds the threshold value 2V / frame, applies a voltage gradient smoothing algorithm for limiting, ensures smooth transition of voltage change, avoids image artifacts caused by voltage jump, finally applies voltage stability check, analyzes the voltage change trend in the last 5 frames, eliminates oscillation phenomenon, thereby obtaining a safe voltage value; the display control unit calculates the pulse width based on the safe voltage value and the response optimization target region data, first establishes a voltage-pulse width mapping table PWM_Table, which describes the pulse width modulation parameters corresponding to different voltage values, then performs table lookup conversion on the safe voltage value V_safe to obtain the initial pulse width value PWM_init=PWM_Table[V_safe], then performs local adjustment according to the pixel position and the surrounding pixel values, when the pixel is at a high-contrast edge, applies an edge enhancement algorithm to appropriately increase the pulse width and enhance the edge sharpness; when the pixel is in a smooth transition area, applies a smoothing algorithm to reduce the pulse width change and keep the color transition natural, finally quantizes the pulse width to convert the continuous value into an 8-bit quantized value (0-255), thereby obtaining the target region pulse width modulation parameter; the display control unit converts the target region pulse width modulation parameter into a driving waveform, first generates a basic driving waveform template according to the driving mode of the liquid crystal display screen, then modifies the duty cycle of the waveform based on the pulse width modulation parameter to generate positive and negative polarity driving waveforms, then adjusts the timing of the waveform to ensure that the rising edge and falling edge of the driving signal are at the best time respectively, reduces signal cross interference, finally applies an overshoot compensation technique to add a short high-voltage pulse at the beginning of the waveform to accelerate the initial response of the liquid crystal molecules, thereby obtaining the optimized driving signal of the target region; the display control unit calculates the standard voltage value of the non-target region data, first reads the RGB data of the non-target region pixels from the frame buffer, performs gray scale conversion, then queries the standard gray scale-voltage mapping table Standard_LUT to obtain the standard voltage value V_std=Standard_LUT[Gray], then applies gamma correction to perform nonlinear adjustment on the voltage value according to the gamma characteristic curve of the display screen to ensure linear change of visual brightness, finally applies panel uniformity compensation to fine-tune the voltage values of different regions according to the position characteristic map of the liquid crystal panel to compensate for the brightness unevenness caused by panel manufacturing errors, thereby obtaining the standard region voltage value;The display control unit performs standard pulse width modulation based on the standard region voltage value, uses the same voltage-pulse width mapping table PWM_Table as in step S52 to perform table lookup conversion on the standard region voltage value V_std to obtain a standard pulse width value PWM_std=PWM_Table[V_std], then adjusts the pulse width by applying the display color mode parameter to realize different color expression styles, and finally quantizes the pulse width by 8 bits, thereby obtaining a standard region pulse width modulation parameter; the display control unit performs driving waveform conversion on the standard region pulse width modulation parameter, first generates a standard waveform template based on the standard driving mode of the liquid crystal display screen, then modifies the waveform duty cycle according to the pulse width modulation parameter to generate positive and negative polarity driving waveforms, then performs alternating current driving polarity inversion setting to ensure that each pixel point inverts polarity between consecutive frames to avoid image retention caused by direct current bias, and finally sorts the waveform data according to the scanning timing of the display screen, thereby obtaining a standard driving signal of the standard region, which will be sent to the liquid crystal panel together with the optimized driving signal of the target region through the display driving IC to complete the driving optimization of the entire display picture.

[0115] The application ensures that the voltage value is within a safe range by limiting the voltage range of the temporary overdrive voltage value, avoids damage or display abnormalities of the liquid crystal display screen caused by excessively high or low voltage, and improves the stability and safety of the system. Based on the safe voltage value, the pulse width of the response optimization target region data is calculated to accurately obtain the pulse width modulation parameter of the target region, thereby providing a necessary basis for generating the optimized driving signal. By converting the driving waveform of the target region pulse width modulation parameter, an optimized driving signal suitable for the display requirements of the target region can be generated, which improves the display effect of the dynamic picture and reduces the ghosting and blurring phenomenon. The standard voltage value of the non-target region data is calculated to ensure that the display signal of the non-target region meets the standard requirements, thereby ensuring the display stability of the non-target region. Based on the standard region voltage value, the standard pulse width modulation is performed to obtain the standard region pulse width modulation parameter, which effectively ensures that the display effect of the non-target region will not be affected. By converting the driving waveform of the standard region pulse width modulation parameter, a standard driving signal suitable for the standard region can be generated to ensure the normal display of all regions of the liquid crystal display screen and ensure the balance and consistency of the overall display effect.

[0116] Preferably, the step S6 includes:

[0117] The control region of the liquid crystal display screen is divided based on the optimized driving signal and the standard driving signal to obtain region driving mapping data.

[0118] The regional driving mapping data is time-sequenced to obtain partition driving time sequence data, wherein the minimum time interval in the time-sequencing process is limited to be greater than or equal to 100 microseconds;

[0119] Based on the partition driving time sequence data, different voltage values are loaded to each sub-region of the liquid crystal display screen to obtain regional differentiation driving voltage values;

[0120] The regional differentiation driving voltage values are subjected to temperature factor compensation calculation to obtain corrected driving voltage values;

[0121] The temperature detection accuracy in the temperature factor compensation calculation is limited to ±1°C, the temperature compensation interval is limited to 5-45°C, and the temperature compensation coefficient update frequency is 1 time per second;

[0122] Based on the corrected driving voltage values, the voltage gradient of the pixels at the region boundary is adjusted to obtain boundary smooth transition data;

[0123] The boundary smooth transition data is subjected to driving signal generation and output control to obtain final partition driving control signals, wherein the signal update frequency of the final partition driving control signals is synchronized with the frame rate, and the signal type is limited within 4 standard waveform types;

[0124] Based on the final partition driving control signals, the liquid crystal response time is monitored in real time to obtain partition driving control results.

[0125] In the embodiment of the present application, based on the optimization of the driving signal and the standard driving signal for the partition driving control of the liquid crystal display screen, first, the pixel mapping method is used to map and divide the control area corresponding to the optimization of the driving signal and the standard driving signal. By establishing the correlation between the pixel coordinates and the driving signal, the area driving mapping data is generated. The area driving mapping data is processed by the data processing module for timing sequence sorting. According to the requirement that the minimum time interval is greater than or equal to 100 microseconds, the driving signal of each sub-area is executed for time axis re-distribution, and the partition driving timing data is generated, so as to ensure that the loading timing of the driving signal of each sub-area meets the hardware control requirement. Based on the partition driving timing data, the driving control unit loads the voltage value of each sub-area of the liquid crystal display screen, uses the independent voltage control circuit, applies the accurate matching driving voltage to each sub-area, and thus forms the area differential driving voltage value. Subsequently, the area differential driving voltage value enters the temperature compensation calculation module, is corrected in real time according to the current temperature detection data, the temperature detection accuracy is set to ±1°C, the temperature compensation interval is set to 5-45°C, and the driving voltage is dynamically adjusted according to the temperature compensation coefficient update frequency of 1 time per second, so as to ensure the voltage compensation accuracy under different temperature environments. The corrected driving voltage value is transmitted to the boundary pixel voltage adjustment unit, the pixel voltage of the adjacent sub-area is calculated for gradient, and the digital filtering algorithm is used for smoothing the voltage gradient, so as to generate the boundary smooth transition data, and ensure that the gray scale change between different driving areas remains stable. Subsequently, the boundary smooth transition data is converted into the final partition driving control signal by the signal processing module, the signal update frequency is synchronized with the frame rate of the liquid crystal display screen, the driving signal type is set to not more than 4 standard waveform types, so as to adapt to different gray scale transition requirements. The final partition driving control signal is transmitted to the liquid crystal display screen driving circuit through the high-speed data bus, the liquid crystal response time is monitored in real time, the partition driving control result is generated, and the next frame of partition driving signal is adjusted based on the feedback data.

[0126] The application ensures accurate control of the display area by mapping and dividing the control area of the liquid crystal display based on the optimized driving signal and the standard driving signal, and lays a foundation for the optimization of subsequent driving signals. The region driving mapping data is processed in time sequence, effectively optimizing the driving time sequence of each region, ensuring the stable performance of the liquid crystal display under high refresh rate, and the minimum limit of the time sequence interval is 100 microseconds, which helps to avoid the tearing and lag phenomenon. Based on the partition driving time sequence data, different voltage values are loaded to each sub-region of the liquid crystal display, and the generated region differentiation driving voltage value enables each display area to provide appropriate voltage according to the actual demand, thereby improving the dynamic response of the display. Through temperature factor compensation calculation on the region differentiation driving voltage value, the corrected driving voltage value is obtained, which effectively avoids the negative impact of temperature change on the display effect, and the temperature compensation accuracy is limited within ±1°C, ensuring the stability and accuracy of the driving voltage. Based on the corrected driving voltage value, the pixel voltage gradient of the region boundary is adjusted, successfully realizing the smooth transition of the boundary, avoiding the obvious unevenness or flicker phenomenon of the display edge, and improving the overall quality of the display effect. The driving signal generation and output control are performed on the boundary smooth transition data, so that the final partition driving control signal can be updated synchronously with the frame rate, and the signal type is limited within 4 standard waveforms, thereby ensuring the stable output and accuracy of the driving signal. Through real-time monitoring of the liquid crystal response time based on the final partition driving control signal, the partition driving control result is obtained, ensuring the dynamic response ability of the liquid crystal display and the high-quality implementation of the display effect.

[0127] Preferably, the dynamic definition evaluation of the partition driving control result in step S6 comprises:

[0128] Based on the partition driving control result, the display area of the liquid crystal display after partition driving is collected in real time to obtain region response curve data;

[0129] Based on the region response curve data, the rise time and fall time of different gray scale conversions are measured to obtain a region response time matrix;

[0130] The gray scale conversion type is limited within 16 typical conversion types, the rise / fall time measurement range is limited to 10%-90% of the standardized brightness range, and the measurement error is limited to ±0.5 milliseconds;

[0131] The region response time matrix is calculated based on a visual persistence effect model to obtain pixel blur width data, wherein the visual persistence time of the visual persistence effect model calculation is limited to 8-16 milliseconds;

[0132] Based on the pixel blur width data, the sharpness of the target region edge is analyzed to obtain an edge sharpness score;

[0133] Target region position change trajectory tracking is performed based on the partition driving control result, and motion trajectory definition data is obtained;

[0134] Uniformity of adjacent region luminance transition is calculated based on the partition driving control result, and luminance transition smoothness score is obtained;

[0135] Color restoration precision is evaluated and calculated based on the partition driving control result, and color fidelity data is obtained, wherein the number of reference color points is less than or equal to 8 standard color points;

[0136] Contrast difference is calculated based on the partition driving control result, and dynamic contrast score is obtained;

[0137] Edge sharpness score, motion trajectory definition data, luminance transition smoothness score, color fidelity data and dynamic contrast score are weighted and fused to obtain a comprehensive quality prediction value;

[0138] Global display effect level is divided based on the comprehensive quality prediction value, and display effect evaluation data is obtained.

[0139] In the embodiment of the present application, the process of dynamic definition evaluation of the partition driving control result first adopts high-precision optical sensors to collect the real-time optical response of the display area after the partition driving of the liquid crystal display screen, uses high-speed sampling circuit to record the change of light intensity, and generates area response curve data. The area response curve data is input into the signal processing module, the rising time and falling time of different gray scale conversion are calculated by digital differential algorithm, the area response time matrix is formed, the gray scale conversion type is set to 16 typical conversion types, the measurement range of response time is limited to 10%-90% of the standardized brightness range, and the measurement error is controlled within ±0.5 milliseconds. The pixel blur width data is generated by calculating the visual persistence effect model based on the area response time matrix, the visual persistence time is limited to 8-16 milliseconds, and the influence of visual persistence on dynamic picture definition is analyzed by combining the time integral method. Based on the pixel blur width data, the sharpness of the target area edge is analyzed, the gradient calculation method is used to extract the edge pixel brightness change rate, and the edge sharpness score is calculated. The partition driving control result is further input into the trajectory analysis module, the motion vector is calculated by analyzing the position change of the target area of the continuous frame, and the motion trajectory definition data is obtained. The adjacent area brightness transition calculation adopts the spatial filtering method, the brightness gradient uniformity is analyzed, and the brightness transition smoothness score is generated. The color restoration accuracy evaluation is based on the standard color matching algorithm, the color difference between the driving display result and the eight standard color points is calculated, and the color fidelity data is obtained. The dynamic contrast score calculation adopts the local contrast analysis method, the final dynamic contrast score is obtained by statistical distribution of the maximum and minimum brightness ratio of the area. The edge sharpness score, motion trajectory definition data, brightness transition smoothness score, color fidelity data and dynamic contrast score are input into the quality evaluation unit, the weighted fusion calculation method is used to calculate the comprehensive quality prediction value, the global display effect level threshold is set combined with the display screen specification parameter, and the display effect evaluation data is finally divided.

[0140] The application can obtain area response curve data by collecting real-time optical response of the display area after the liquid crystal display screen is driven by the partition driving control result, so as to accurately understand the dynamic response characteristics of the display area. The rise time and fall time of different gray scale conversion are measured based on the area response curve data, and the area response time matrix is obtained, which effectively helps to identify the delay problem in the gray scale change and ensures that the response speed is within the predetermined time range. The gray scale conversion type is limited within 16 typical conversion types, and the rise / fall time is measured within the 10%-90% normalized brightness range, which ensures the accuracy of the measurement, and the error is limited within ±0.5 milliseconds, providing high-precision response time data. The pixel blur width data can be accurately obtained by calculating the visual persistence effect model based on the area response time matrix, which provides a basis for further display optimization. The edge sharpness score is obtained by performing sharpness analysis on the target area edge based on the pixel blur width data, thereby optimizing the edge definition in the display effect. The motion trajectory clarity data can be obtained by tracking the target area position change trajectory, which effectively improves the clarity of the dynamic picture. The calculation of the uniformity of the luminance transition between adjacent areas further optimizes the transition effect between the display areas, and the luminance transition smoothness score is obtained, which reduces the visual discontinuity. The color restoration accuracy is evaluated to ensure the restoration accuracy and authenticity of the color, and the number of reference color points is limited within 8 standard color points to ensure the accuracy and authenticity of the color. In addition, the calculation of the contrast difference helps to optimize the contrast problem in the display effect, and the dynamic contrast score is obtained. Finally, the comprehensive quality prediction value is obtained by weighted fusion calculation of the edge sharpness score, the motion trajectory clarity data, the luminance transition smoothness score, the color fidelity data and the dynamic contrast score, which further classifies the global level of the display effect, thereby obtaining detailed display effect evaluation data, which provides an effective basis for subsequent optimization and adjustment.

[0141] Preferably, the application further provides a display optimization system for a liquid crystal display screen, which is used to execute the display optimization method for a liquid crystal display screen described above, and the display optimization system for a liquid crystal display screen comprises:

[0142] A frame difference detection module is configured to obtain current image frame data and previous image frame data, calculate inter-frame difference based on a preset pixel difference threshold, and obtain motion area data based on threshold judgment of the inter-frame difference data.

[0143] A gray scale change calculation module is configured to calculate a gray scale change rate based on the motion area data, and obtain response optimization target area data and non-target area data by threshold cutting of the gray scale change rate data.

[0144] The target area merging module is configured to perform continuity evaluation on the response optimization target area data, and perform merging processing based on the continuity evaluation result to obtain a continuous rectangular target area group.

[0145] The temperature self-adaptive calculation module is configured to obtain current temperature data, and perform gray scale value difference calculation on the continuous rectangular target area group according to the current temperature data to obtain a temporary overdrive voltage value.

[0146] The partition modulation driving module is configured to perform pulse width modulation on the temporary overdrive voltage value, wherein the response optimization target area data is subjected to high-frequency pulse width modulation to generate an optimization driving signal, and the non-target area data is subjected to standard pulse width modulation to generate a standard driving signal.

[0147] The definition evaluation module is configured to perform partition compensation driving control on the liquid crystal display screen based on the optimization driving signal and the standard driving signal, and perform dynamic definition evaluation on the partition driving control result to obtain display effect evaluation data.

[0148] Therefore, from any viewpoint, the embodiments should be considered as being exemplary and non-limiting, the scope of the present application not being limited by the above description, and all the variations falling within the meaning and the scope of the equivalent elements of the patent file are intended to be comprised in the present application.

[0149] The above description is merely a specific implementation of the present application, enabling those skilled in the art to understand or implement the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to these embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A display optimization method for a liquid crystal display screen, characterized in that, Includes the following steps: Step S1: Obtain the current image frame data and the previous image frame data, and calculate the inter-frame difference based on the preset pixel difference threshold; Thresholding is performed based on inter-frame difference data to obtain motion region data; Step S2: Calculate the grayscale change rate based on the motion area data; Thresholding is applied to the grayscale change rate data to obtain the target area data and non-target area data for response optimization. Step S3: Perform continuity assessment on the data of the target region for response optimization, and merge the data based on the continuity assessment results to obtain a group of continuous rectangular target regions; Step S4: Obtain the current temperature data; calculate the grayscale difference of the continuous rectangular target area group based on the current temperature data to obtain the temporary overdrive voltage value; Step S5: Pulse width modulation is applied to the temporary overdrive voltage value, wherein high-frequency pulse width modulation is applied to the data in the target region of response optimization to generate an optimized drive signal, and standard pulse width modulation is applied to the data in the non-target region to generate a standard drive signal. Step S6: Based on the optimized drive signal and the standard drive signal, perform partition compensation drive control on the LCD screen, and perform dynamic sharpness evaluation on the partition drive control results to obtain display effect evaluation data.

2. The display optimization method for a liquid crystal display screen according to claim 1, characterized in that, Step S1 includes the following steps: Step S11: Obtain the current image frame data and the previous image frame data, and perform noise filtering to obtain a standardized image frame dataset; Step S12: Perform pixel-level comparison calculations on the standardized image frame dataset based on a preset pixel difference threshold to obtain pixel difference matrix data; Step S13: Cluster adjacent pixels in the pixel difference matrix data to obtain regional difference data; Step S14: Binarize the regional difference data based on the preset motion determination threshold to obtain preliminary motion region labeling data; Step S15: Perform morphological dilation and erosion operations on the preliminary motion region labeling data to obtain optimized motion region data; Step S16: Extract motion region edge data from the optimized motion region data; Step S17: Expand the edge data of the motion region by pixels to obtain the motion region data.

3. The display optimization method for a liquid crystal display screen according to claim 1, characterized in that, Step S2 includes the following steps: Step S21: Perform pixel-level traversal on the motion region data to obtain the set of pixel coordinates of the motion region; Step S22: Extract the current grayscale value matrix from the current image frame data based on the pixel coordinate set of the moving region; Step S23: Extract the previous grayscale value matrix from the previous image frame data based on the pixel coordinate set of the moving region; Step S24: Perform a difference operation on the current grayscale value matrix and the previous grayscale value matrix to obtain the grayscale difference matrix; Step S25: Calculate the ratio based on the gray level difference matrix and the current gray level value matrix, and evaluate the long-term effect to obtain gray level change trend data; Step S26: Smooth the grayscale change trend data to obtain grayscale change rate data; Step S27: Perform threshold comparison and classification on the grayscale change rate data to obtain preliminary target area labeled data and non-target area data; Step S28: Perform boundary refinement processing on the initial target area marking data to obtain optimized target area data; Step S29: Perform response time gradient analysis on the optimized target region data to obtain the optimized target region data.

4. The display optimization method for a liquid crystal display screen according to claim 1, characterized in that, Step S3, which involves evaluating the continuity of data in the target region for response optimization, includes: Pixel connectivity analysis is performed on the target region data for response optimization to obtain initial connected region labeling data; Clustering is performed on the initial connected component labeled data to obtain the target region clustered data, wherein the minimum region area for clustering is limited to less than or equal to 16 pixels; Extracting region shape feature data from clustered data of the target region; Rectangular fitting calculations are performed on the region shape feature data to obtain initial rectangular region data; The fitting error in the rectangular fitting calculation is less than or equal to 15%, and the rotation angle is limited to four directions: 0°, 45°, 90°, and 135°. The overlap of the initial rectangular region data is calculated to obtain the rectangular overlap data. The overlap ratio threshold in the overlap calculation is limited to less than or equal to 30%.

5. The display optimization method for a liquid crystal display screen according to claim 4, characterized in that, The merging process based on the continuity evaluation results described in step S3 includes: The rectangular overlap data is filtered based on the overlap threshold. When the rectangular overlap data is greater than the overlap threshold, the rectangular region data corresponding to the rectangular overlap data is merged to obtain the merged rectangular region data. The overlap threshold is limited to between 30% and 50%. If the overlap of the rectangles is less than 30%, irrelevant areas will be incorrectly merged. If the overlap of the rectangles is greater than 50%, obviously related areas will not be merged. The merged rectangular region data is expanded by pixel boundaries to obtain expanded boundary rectangular region data. Perform pixel alignment processing on the extended boundary rectangular region data to obtain aligned rectangular region data; The aligned rectangular region data is then subjected to spatial location analysis and grouped to obtain continuous rectangular target region groups.

6. The display optimization method for a liquid crystal display screen according to claim 1, characterized in that, Step S4 includes the following steps: Step S41: Obtain the current temperature data; perform mapping calculations on the current temperature data to obtain the liquid crystal temperature compensation coefficient; Step S42: Calculate the difference between the current grayscale value and the target grayscale value of each region in the continuous rectangular target region group to obtain grayscale difference data; Step S43: Based on the grayscale difference data and temperature compensation parameters, perform an index lookup on the grayscale conversion lookup table to obtain the basic overdrive voltage value; Step S44: Adjust the dynamic response characteristics and optimize the mode of the basic overdrive voltage value to obtain the temporary overdrive voltage value.

7. The display optimization method for a liquid crystal display screen according to claim 1, characterized in that, Step S5 includes the following steps: Step S51: Perform voltage range limiting processing on the temporary overdrive voltage value to obtain a safe voltage value; Step S52: Calculate the pulse width of the target region data based on the safe voltage value to obtain the pulse width modulation parameters of the target region; Step S53: Perform drive waveform conversion on the pulse width modulation parameters of the target region to obtain the optimized drive signal for the target region; Step S54: Calculate the standard voltage value for the non-target area data to obtain the standard area voltage value; Step S55: Perform standard pulse width modulation based on the standard region voltage value to obtain the standard region pulse width modulation parameters; Step S56: Perform drive waveform conversion on the pulse width modulation parameters of the standard region to obtain the standard drive signal of the standard region.

8. The display optimization method for a liquid crystal display screen according to claim 1, characterized in that, Step S6, which describes the partition driving control of the liquid crystal display screen based on optimized driving signals and standard driving signals, includes: The control area of ​​the LCD screen is mapped and divided based on the optimized drive signal and the standard drive signal to obtain the area drive mapping data. The region-driven mapping data is processed by time-series sorting to obtain partition-driven time-series data, wherein the minimum time interval in the time-series sorting process is limited to greater than or equal to 100 microseconds. Based on the partition driving timing data, different voltage values ​​are applied to each sub-region of the LCD screen to obtain the region-differentiated driving voltage values. Temperature factor compensation calculations are performed on the regionally differentiated driving voltage values ​​to obtain corrected driving voltage values. The temperature detection accuracy in the temperature factor compensation calculation is limited to ±1°C, the temperature compensation range is limited to 5-45°C, and the temperature compensation coefficient is updated once per second. Based on the corrected driving voltage value, the pixel voltage gradient of the region boundary is adjusted to obtain boundary smooth transition data; The boundary smooth transition data is driven by signal generation and output control to obtain the final partition drive control signal. The signal update frequency of the final partition drive control signal is synchronized with the frame rate, and the signal type is limited to 4 standard waveform types. The partition drive control result is obtained by real-time monitoring of the LCD response time based on the final partition drive control signal.

9. The display optimization method for a liquid crystal display screen according to claim 8, characterized in that, Step S6, which involves performing a dynamic clarity evaluation on the partition drive control results, includes: Based on the partition drive control results, the real-time optical response of the display area after partition drive of the LCD screen is acquired to obtain the area response curve data. The rise time and fall time of different grayscale transitions are measured based on the regional response curve data to obtain the regional response time matrix; The grayscale conversion types are limited to 16 typical conversion types, the rise / fall time measurement range is limited to 10%-90% of the normalized brightness range, and the measurement error is limited to ±0.5 milliseconds; The visual persistence effect model is used to calculate the region response time matrix to obtain pixel blur width data. The visual persistence time in the calculation of the visual persistence effect model is limited to 8-16 milliseconds. Sharpness analysis of the target region edge is performed based on pixel blur width data to obtain an edge sharpness score; Based on the results of partition-driven control, the trajectory of the target area position change is tracked to obtain motion trajectory clarity data; Based on the results of the partition-driven control, the uniformity of the brightness transition between adjacent regions is calculated to obtain a brightness transition smoothness score. The color reproduction accuracy is evaluated and calculated based on the partition drive control results to obtain color fidelity data, wherein the number of reference color points is less than or equal to 8 standard color points; The contrast difference is calculated based on the partition drive control results to obtain a dynamic contrast score; The edge sharpness score, motion trajectory clarity data, brightness transition smoothness score, color fidelity data, and dynamic contrast score are weighted and fused to obtain a comprehensive quality prediction value. The global display effect level is divided based on the comprehensive quality prediction value, and the display effect evaluation data is obtained.

10. A display optimization system for a liquid crystal display screen, characterized in that, For performing the display optimization method for a liquid crystal display screen as described in claim 1, the display optimization system for the liquid crystal display screen includes: The frame difference detection module is used to acquire the current image frame data and the previous image frame data, calculate the inter-frame difference based on a preset pixel difference threshold, and perform threshold judgment based on the inter-frame difference data to obtain motion region data. The grayscale change calculation module is used to calculate the grayscale change rate based on the motion area data; and to perform threshold truncation on the grayscale change rate data to obtain the response optimization target area data and non-target area data. The target region merging module is used to perform continuity evaluation on the target region data of response optimization, and to perform merging processing based on the continuity evaluation results to obtain a continuous rectangular target region group; The temperature adaptive calculation module is used to acquire the current temperature data; based on the current temperature data, it calculates the grayscale difference of the continuous rectangular target area group to obtain the temporary overdrive voltage value. The partitioned modulation drive module is used to perform pulse width modulation on the temporary overdrive voltage value. Specifically, high-frequency pulse width modulation is performed on the data of the response optimization target area to generate an optimized drive signal, and standard pulse width modulation is performed on the data of the non-target area to generate a standard drive signal. The sharpness evaluation module is used to perform partition compensation drive control on the LCD screen based on optimized drive signals and standard drive signals, and to perform dynamic sharpness evaluation on the partition drive control results to obtain display effect evaluation data.

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