Display optimization method and system for liquid crystal display screen

Abstract

The invention relates to the technical field of display methods of electronic displays, 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 an inter-frame difference based on a preset pixel difference threshold; performing threshold judgment based on the inter-frame difference data to obtain motion area data; calculating a gray scale change rate according to the motion area data; performing threshold interception on the gray scale change rate data to obtain response optimization target area data and non-target area data; and performing continuity evaluation on the response optimization target area data, and performing merging processing based on a continuity evaluation result to obtain a continuous rectangular target area group. According to the invention, the dynamic optimization of the liquid crystal display screen is realized by accurately identifying the motion area and carrying out gray scale change calculation, temperature adaptation adjustment and pulse width modulation, and the definition and the display effect of a motion picture are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of display methods for electronic displays, and particularly to a display optimization method and system for liquid crystal display screens. Background Art

[0002] Liquid crystal display screens (LCDs), as the mainstream display technology, are widely used in the fields of televisions, computer monitors, and mobile devices. Traditional LCD technology relies on a backlight to provide brightness, and adjusts the light transmittance by the rotation of liquid crystal molecules to achieve image display. Early LCDs adopted a passive matrix driving method, which had problems such as slow response speed and contrast. Subsequently, the development of active matrix technology (TFT-LCD) has greatly improved the display performance, making LCD products with high resolution, high refresh rate, and wider color gamut become the mainstream. However, due to the relatively long response time of liquid crystal molecules, compared with self-emitting display technologies (such as OLED, Micro-LED), LCDs still face problems such as motion blur and smear in dynamic images, especially in high refresh rate and high-speed motion images, where the display clarity is affected. Traditional over-driving algorithms usually adopt fixed thresholds or calculation methods based on static gray-scale differences, and cannot fully adapt to complex image content and environmental factors. Existing inter-frame over-driving processing often fails to accurately distinguish between moving regions and static regions, resulting in over-enhancement or artifacts in some images. Summary of the Invention

[0003] Based on this, it is necessary for the present invention to provide a display optimization method and system for liquid crystal display screens to solve at least one of the above technical problems.

[0004] To achieve the above object, 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, calculate the inter-frame difference based on a preset pixel difference threshold; perform threshold judgment based on the inter-frame difference data to obtain motion region data;

[0006] Step S2: Calculate the gray-scale change rate according to the motion region data; perform threshold truncation on the gray-scale change rate data to obtain response optimization target region data and non-target region data;

[0007] Step S3: Evaluate the continuity of the response optimization target region data, and perform merging processing based on the continuity evaluation result to obtain a continuous rectangular target region group;

[0008] Step S4: Obtain the current temperature data; calculate the gray-scale value difference of the continuous rectangular target region group according to the current temperature data to obtain a temporary over-driving voltage value;

[0009] Step S5: Perform pulse width modulation on the temporary over-drive voltage value, where high-frequency pulse width modulation is performed on the data in the response optimization target area to generate an optimized drive signal, and standard pulse width modulation is performed on the non-target area data to generate a standard drive signal;

[0010] Step S6: Based on the optimized drive signal and the standard drive signal, perform partition compensation drive control on the liquid crystal display screen, and perform dynamic sharpness evaluation on the partition drive control result to obtain display effect evaluation data.

[0011] The present invention obtains the current image frame data and the previous image frame data, and calculates the inter-frame difference based on a preset pixel difference threshold, so that the system can accurately identify the image change area and avoid unnecessary over-drive processing of static pictures. By performing threshold judgment based on the inter-frame difference data to obtain the motion area data, the recognition ability of the dynamic scene is effectively improved, providing a reliable basis for subsequent calculation of the gray-scale change rate. Calculate the gray-scale change rate according to the motion area data, and perform threshold truncation on the gray-scale change rate data, so that the system can accurately distinguish the response optimization target area and the non-target area, ensure that the over-drive optimization acts on the areas that really need to be enhanced, and avoid over-driving or detail loss caused by misjudgment. Continuously evaluate the data in the response optimization target area, and perform merging processing based on the continuity evaluation result to obtain a continuous rectangular target area group, which can improve the integrity of motion area recognition and reduce edge flicker and discontinuous optimization phenomena caused by area dispersion. Obtain the current temperature data, and calculate the gray-scale value difference of the continuous rectangular target area group according to the current temperature data to obtain the temporary over-drive voltage value, so that the over-drive calculation can adapt to the ambient temperature change and avoid inaccurate drive signals caused by the influence of temperature on the liquid crystal response speed. Perform pulse width modulation on the temporary over-drive voltage value, where high-frequency pulse width modulation is performed on the data in the response optimization target area to generate an optimized drive signal, and standard pulse width modulation is performed on the non-target area data to generate a standard drive signal, so as to provide a more accurate over-drive 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 drive signal and the standard drive signal, perform partition compensation drive control on the liquid crystal display screen, making the over-drive processing more refined, improving the drive matching degree of different areas, and performing dynamic sharpness evaluation on the partition drive control result to obtain display effect evaluation data, ensuring that the entire system can perform adaptive adjustment according to the evaluation result, achieving a better dynamic picture display effect, effectively reducing motion blur, and improving the clarity of the motion picture.

[0012] Preferably, the present invention also provides a display optimization system for a liquid crystal display screen, which is used to execute the above-mentioned display optimization method for a liquid crystal display screen. The display optimization system for a liquid crystal display screen includes:

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

[0014] The grayscale change calculation module is used to calculate the grayscale change rate according to the motion area data; perform threshold truncation on the grayscale change rate data to obtain the response-optimized target area data and non-target area data;

[0015] The target area merging module is used to evaluate the continuity of the response-optimized target area data and perform merging processing based on the continuity evaluation result to obtain a continuous rectangular target area group;

[0016] The temperature adaptive calculation module is used to obtain the current temperature data; calculate the grayscale value difference of the continuous rectangular target area group according to the current temperature data to obtain a temporary overdrive voltage value;

[0017] The partition modulation driving module is used to perform pulse width modulation on the temporary overdrive voltage value, where high-frequency pulse width modulation is performed on the response-optimized target area data to generate an optimized driving signal, and standard pulse width modulation is performed on the non-target area data to generate a standard driving signal;

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

[0019] The present invention calculates the inter-frame difference by obtaining the current image frame data and the previous image frame data, effectively identifies the dynamic area, thus accurately distinguishes the moving area from the static area, reduces unnecessary processing, and optimizes the subsequent display effect. It can accurately calculate the grayscale change rate within the moving area and perform threshold truncation, effectively separating the response optimization target area from the non-target area, so as to perform more accurate dynamic optimization processing. By continuously evaluating the data of the response optimization target area and performing merging processing, a continuous rectangular target area group is successfully formed, reducing the complexity of area division and providing a clear area segmentation basis for subsequent voltage regulation and optimization. According to the current temperature data, the grayscale value difference is calculated to obtain the temporary overdrive voltage value, realizing the adaptive adjustment of temperature and effectively ensuring the stable display effect of the liquid crystal display under different temperature conditions. By performing high-frequency and standard pulse width modulation on the response optimization target area and the non-target area respectively, an optimized driving signal and a standard driving signal are generated, ensuring the efficiency and stability of the display, while avoiding unnecessary power consumption waste. Based on the optimized driving signal and the standard driving signal, the partition compensation driving control of the liquid crystal display is carried out, and the dynamic sharpness of the partition driving control result is evaluated, so as to accurately evaluate the display effect and provide accurate feedback data for the final display quality optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Other features, objects, and advantages of the present invention will become more apparent by reading the detailed description of the non-limiting embodiments with reference to the following drawings:

[0021] Figure 1 It is a schematic flowchart of the steps of a display optimization method for a liquid crystal display according to the present invention;

[0022] Figure 2 is Figure 1 a detailed schematic flowchart of step S1 in

[0023] Figure 3 is Figure 1 a detailed schematic flowchart of step S2 in DETAILED DESCRIPTION OF THE EMBODIMENTS

[0024] The technical method of the present invention will be clearly and completely described below with reference to the drawings. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those skilled in the art within the scope of the present invention without creative efforts based on the embodiments of the present invention belong to the scope of protection of the present invention.

[0025] In addition, the attached drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus repeated descriptions thereof will be omitted. Some of the block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor methods and / or microcontroller methods.

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

[0027] To achieve the above object, please refer to Figures 1 to 3 , the present invention provides a display optimization method for a liquid crystal display screen, and the method includes the following steps:

[0028] Step S1: Obtain the current image frame data and the previous image frame data, calculate the inter-frame difference based on a preset pixel difference threshold; perform threshold judgment based on the inter-frame difference data to obtain motion area data;

[0029] Step S2: Calculate the grayscale change rate according to the motion area data; perform threshold truncation on the grayscale change rate data to obtain response optimization target area data and non-target area data;

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

[0031] Step S4: Obtain the current temperature data; calculate the grayscale value difference of the continuous rectangular target area group according to the current temperature data to obtain a temporary overdrive voltage value;

[0032] Step S5: Perform pulse width modulation on the temporary overdrive voltage value, wherein perform high-frequency pulse width modulation on the response optimization target area data to generate an optimized drive signal, and perform standard pulse width modulation on the non-target area data to generate a standard drive signal;

[0033] Step S6: Perform partition compensation drive control on the liquid crystal display screen based on the optimized drive signal and the standard drive signal, and perform dynamic sharpness evaluation on the partition drive control result to obtain display effect evaluation data.

[0034] In an embodiment of the present invention, with reference to Figure 1 As shown, it is a schematic flow chart of the steps of a display optimization method for a liquid crystal display according to the present invention. In this example, the display optimization method for the liquid crystal display includes the following steps:

[0035] Step S1: Obtain the current image frame data and the previous image frame data, calculate the inter-frame difference based on a preset pixel difference threshold; perform threshold judgment based on the inter-frame difference data to obtain the motion area data;

[0036] In an embodiment of the present invention, the display control unit of the liquid crystal display 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. The image frame data includes a grayscale value matrix of MxN pixel points, and the grayscale values at each pixel point position (i, j) are F(t, i, j) and F(t - 1, i, j) respectively; then calculate the inter-frame difference D(i, j) = |F(t, i, j) - F(t - 1, i, j)| for each pixel point position, and make a judgment according to the preset pixel difference threshold Th_diff (this threshold is specifically set to 15% of the grayscale value range, that is, for an 8-bit grayscale liquid crystal display, Th_diff = 38); when D(i, j) > Th_diff, mark this pixel point as a moving pixel point to generate a motion area binary matrix M(i, j), where M(i, j) = 1 represents a moving pixel point and M(i, j) = 0 represents a non-moving pixel point; then use the 8-neighborhood connected component labeling algorithm to label the connected areas of M(i, j), and assign the same area identifier L_k to adjacent moving pixel points; for each connected area L_k, when the number of pixel points it contains exceeds the area threshold Th_area (set to 100 pixel points), retain this area as a valid motion area; finally, calculate the minimum bounding rectangle for the valid motion area to determine the upper left corner coordinates (x_k, y_k) and width and height (w_k, h_k) of each motion area, forming a motion area data set R = {R_k}, where R_k = (x_k, y_k, w_k, h_k, L_k).

[0037] Step S2: Calculate the grayscale change rate according to the motion area data; perform threshold truncation on the grayscale change rate data to obtain the response optimization target area data and the non-target area data;

[0038] In the embodiment of the present invention, 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 positions (i, j) within each motion region R_k based on the motion region data set R = {R_k}, and calculates the gray-scale change rate GCR(i, j) = (F(t, i, j) - F(t-1, i, j)) / △t, where △t represents the time interval between two frames (set to 16.67 ms corresponding to a 60 Hz refresh rate); then performs an absolute value conversion on the calculated gray-scale change rate to obtain |GCR(i, j)|; next, sets the upper and lower threshold values to Th_upper = 20 gray-scale values / ms and Th_lower = 5 gray-scale values / ms respectively, and performs threshold truncation processing on the gray-scale change rate data. When |GCR(i, j)| ≥ Th_upper, marks this pixel as a response optimization target point and generates a target region binary matrix T(i, j) = 1; when Th_lower ≤ |GCR(i, j)| < Th_upper, marks this pixel as a transition region point, T(i, j) = 0.5; when |GCR(i, j)| < Th_lower, marks this pixel as a non-target region point, T(i, j) = 0; subsequently, 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 includes the upper left coordinate (x_p, y_p), width and height (w_p, h_p), and the gray-scale change rate matrix GCR_p of the pixels within the region; at the same time, defines the set of all pixels with T(i, j) = 0 as a non-target region set N = {N_q}, where each non-target region N_q also includes position coordinates, size information, and gray-scale change rate data; finally, obtains the response optimization target region data O and the non-target region data N.

[0039] Step S3: Continuously evaluate the response optimization target region data, and perform a merging process based on the continuity evaluation result to obtain a set of continuous rectangular target regions;

[0040] In an embodiment of the present invention, the display control unit receives the response optimization target area data O = {O_p}. First, a time continuity evaluation algorithm is applied to each target area O_p. This algorithm calculates the continuity index CI_p by analyzing the presence of the area in 5 consecutive frames. The specific method is as follows: Trace 4 frames forward from the current frame t, and detect whether there is a target area in each frame whose overlap rate with the position of O_p exceeds 60%. If there is an area that meets the condition in the (t - k)th frame, the contribution value of this frame is (5 - k) / 5. Add up the contribution values of all frames to obtain CI_p, and the value range is [0, 3]. Then, set the continuity threshold Th_cont = 1.5. When CI_p ≥ Th_cont, mark this area as a stable target area; otherwise, mark it as an instantaneous target area. Subsequently, perform target area merging processing. Use the distance threshold Th_dist = 20 pixels as the judgment basis to perform spatial proximity analysis on all stable target areas. When the minimum Euclidean distance between two stable target areas O_i and O_j is less than Th_dist, calculate the minimum bounding rectangle of these two areas to form a new merged area. The upper left corner coordinates of this merged area are min(x_i, x_j, y_i, y_j), and the lower right corner coordinates are max(x_i + w_i, x_j + w_j, y_i + h_i, y_j + h_j). Repeat the area merging process until all adjacent areas are processed. Finally, obtain the continuous rectangular target area group C = {C_m}, where each area C_m contains the rectangular coordinate information (x_m, y_m, w_m, h_m), the average grayscale change rate avg_GCR_m within the area, and the area continuity index CI_m.

[0041] Step S4: Obtain the current temperature data; calculate the grayscale value difference for the continuous rectangular target area group according to the current temperature data to obtain a temporary overdrive voltage value;

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

[0043] Step S5: Perform pulse width modulation on the temporary over-drive voltage values, where high-frequency pulse width modulation is performed on the response optimization target area data to generate an optimized drive signal, and standard pulse width modulation is performed on the non-target area data to generate a standard drive signal;

[0044] In the embodiments of the present invention, the display control unit receives the temporary over-drive voltage matrix OD, and divides the display screen area into a response optimization target area and a non-target area for differential processing. First, for each pixel point (i, j) in the response optimization target area, the control unit uses the high-frequency pulse width modulation technology to increase the standard 60Hz driving frequency to 120Hz. Each original refresh period of 16.67ms is divided into two sub-periods. In the first sub-period, the over-drive 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-period, 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 system maximum driving voltage of 10V. For each pixel point in the non-target area, the control unit uses the 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 corresponding driving waveforms for each pixel point, including voltage amplitude, pulse width, and frequency information. For the pixel points in the target area, the optimized driving signal DS_opt(i, j) = (OD(i, j), τ1(i, j), Vn, τ2(i, j), 120Hz) is generated. For the pixel points in the non-target area, 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 includes the optimized driving signal and the standard driving signal.

[0045] Step S6: Based on the optimized driving signal and the standard driving signal, perform partition compensation driving control on the liquid crystal display screen, and dynamically evaluate the clarity of the partition driving control result to obtain the display effect evaluation data.

[0046] In the embodiment of the present invention, the display control unit receives the driving signal matrix DS and performs differential driving control on each area through the liquid crystal display driving circuit. First, the control unit divides the display screen into a 16×12 driving block grid, with each block size being 120×90 pixels. Each block is marked according to the type of driving signal. 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, using the optimized driving signal DS_opt generated in step S5 for the optimized blocks and the standard driving signal DS_std for the standard blocks. Subsequently, the control unit performs smoothing processing on the boundary areas of adjacent blocks by implementing a gradual change in the driving signal intensity within a boundary area with a width of 5 pixels. The specific method is to calculate the driving voltage value by distance weighting within the transition area, and the voltage value OD_boundary(i,j) = OD1×(1 - d / 5) + OD2×d / 5, where d is the distance from the pixel point to the boundary, and OD1 and OD2 are the driving voltage values of the two adjacent blocks. Next, the control unit performs dynamic sharpness evaluation of the driving control result, including four steps: First, collect the currently displayed image after optimized driving, denoted as Img_opt. Then, calculate the edge difference Diff_edge between Img_opt and the previous frame image. Specifically, use the Sobel edge detection operator to extract the edge feature maps of the two frame images and calculate the difference value. Subsequently, calculate the weighted mean square error WMSE using weighted root mean square error for the motion area, assigning a higher weight of 0.8 to the motion area and a weight of 0.2 to the non-motion area. Finally, obtain the sharpness index Clarity = 0.6×Diff_edge + 0.4×(1 - WMSE), with the score range being 0 - 1. The control unit records the sharpness index and the driving parameters of each block as display effect evaluation data and stores them in the evaluation database.

[0047] The present invention obtains the current image frame data and the previous image frame data, and calculates the inter-frame difference based on a preset pixel difference threshold, enabling the system to accurately identify the image change area and avoid unnecessary over-driving processing of static images. By performing threshold judgment on the inter-frame difference data to obtain the motion area data, the recognition ability of dynamic scenes is effectively improved, providing a reliable basis for subsequent calculation of the gray-scale change rate. The gray-scale change rate is calculated according to the motion area data, and the gray-scale change rate data is thresholded, enabling the system to accurately distinguish the response optimization target area from the non-target area, ensuring that the over-driving optimization acts on the areas that truly need to be enhanced, and avoiding over-driving or detail loss caused by misjudgment. The continuity of the response optimization target area data is evaluated, and merging processing is performed based on the continuity evaluation result to obtain a continuous rectangular target area group, which can improve the integrity of motion area recognition and reduce edge flicker and discontinuous optimization phenomena caused by dispersed 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 over-driving voltage value, enabling the over-driving calculation to adapt to environmental temperature changes and avoiding inaccurate driving signals caused by temperature affecting the liquid crystal response speed. Pulse width modulation is performed on the temporary over-driving voltage value, where high-frequency pulse width modulation is performed on the response optimization target area data to generate an optimized driving signal, and standard pulse width modulation is performed on the non-target area data to generate a standard driving signal, thereby providing a more accurate over-driving effect in key areas while ensuring the stability of non-target areas and preventing image distortion caused by excessive enhancement. The liquid crystal display is driven and controlled with partition compensation based on the optimized driving signal and the standard driving signal, making the over-driving processing more refined, improving the driving matching degree of different areas, and performing dynamic sharpness evaluation on the partition driving control result to obtain display effect evaluation data, ensuring that the entire system can perform adaptive adjustment according to the evaluation result to achieve a better dynamic picture display effect, effectively reducing motion blur and improving the clarity of motion pictures.

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

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

[0050] Step S12: Perform 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: Cluster adjacent pixels of the pixel difference matrix data to obtain regional difference data;

[0052] Step S14: Binarize the regional difference data based on a preset motion determination threshold to obtain preliminary motion area marking data;

[0053] Step S15: Perform morphological dilation and erosion operations on the preliminary motion area marked data to obtain optimized motion area data;

[0054] Step S16: Extract motion area edge data from the optimized motion area data;

[0055] Step S17: Perform pixel expansion on the motion area edge data to obtain motion area data.

[0056] In an embodiment of the present invention, the display control unit first obtains the current image frame data and the previous image frame data through the display driver interface. Each frame of data contains the RGB color values of 1920×1080 pixel points. Then, the display control unit performs a two-stage noise filtering process: in the first stage, a 3×3 Gaussian filter with kernel parameters [0.0625, 0.125, 0.0625; 0.125, 0.25, 0.125; 0.0625, 0.125, 0.0625] is used to perform a convolution operation on the two frames of images to remove high-frequency noise. In the second stage, a brightness equalization process is performed. The RGB values of each pixel point are converted to the YUV color space, and only the Y component is retained as the brightness value to generate a standardized image frame data set. The display control unit calculates the difference value at each pixel position for the standardized current frame and the previous frame data. The difference value formula is abs(Y current(x,y) - Y previous(x,y)), where 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), and all pixel difference values are compared to generate pixel difference matrix data. 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 using the region growing method. Pixels with a difference value greater than 0.8 are used as seed points, and adjacent pixels with a difference value greater than 0.5 are gradually expanded and connected until no further expansion is possible. Each clustering region is assigned a unique identification number to form region difference data. The display control unit sets a preset motion determination threshold to 100 pixel points and detects the number of pixel points contained in each clustering region in the region difference data. If the number exceeds the motion determination threshold, all pixel points in the region are marked as motion pixels (value is 1), otherwise they are marked as non-motion pixels (value is 0) to generate preliminary motion region marking data. The display control unit applies morphological operations to the preliminary motion region marking data. First, a dilation operation with a 3×3 structuring element is performed 2 times to fill small holes in the motion region, and then an erosion operation with a 3×3 structuring element is performed 1 time to remove isolated noise points to obtain optimized motion region data. The display control unit uses the Sobel edge detection operator to perform a convolution operation on the optimized motion region data to extract the edge contour of the motion region. The specific operations include first applying the horizontal Sobel operator [1, 2, 1; 0, 0, 0; -1, -2, -1], then applying the vertical Sobel operator [1, 0, -1; 2, 0, -2; 1, 0, -1], taking the square root of the sum of the squares of the results in the two directions as the edge intensity, and then passing through a threshold of 0.Perform binarization processing on 5 to obtain the edge data of the motion area; the display control unit performs a pixel expansion operation on the edge data of the motion area, expanding 5 pixels outward in width. The expansion method is to fill pixels with a value of 1 in eight directions (horizontal, vertical, diagonal) from each edge pixel point, and repeat this operation 5 times. Finally, merge the expanded edge data with the optimized motion area data to obtain the final motion area data.

[0057] Through noise filtering processing on the current image frame data and the previous image frame data, the present invention can effectively reduce errors caused by photosensitive element noise or compression artifacts, ensuring the accuracy of subsequent calculations. Based on a preset pixel difference threshold, pixel-level comparison calculations are performed, enabling the system to accurately detect inter-frame changes and avoid misjudgments caused by minor brightness fluctuations or noise interference. Clustering adjacent pixels of the pixel difference data helps enhance the extraction of motion features at the regional level, improve the integrity of the motion area, and avoid artifacts caused by misjudgments of isolated pixels. Binarization of the regional difference data based on a preset motion determination threshold enables the system to effectively distinguish the motion area from the static area, reducing fuzzy judgments during the motion recognition process. Performing morphological dilation and erosion operations on the preliminary motion area marker data can smooth the area boundary, fill gaps caused by noise, and improve the stability and coherence of the motion area. Extracting edge data from the optimized motion area enables subsequent processing to more accurately analyze the morphological features of the motion area, helping to improve the edge detail optimization ability. Performing pixel expansion on the edge data of the motion area can ensure a more complete coverage range of the motion area, reduce boundary truncation problems, make the optimized motion area data more conform to the real motion area, and ensure the accuracy of subsequent over-drive processing.

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

[0059] Step S21: Perform pixel-level traversal on the motion area data to obtain the motion area pixel coordinate set;

[0060] Step S22: Extract the current grayscale value matrix from the current image frame data based on the motion area pixel coordinate set;

[0061] Step S23: Extract the previous grayscale value matrix from the previous image frame data based on the motion area pixel coordinate set;

[0062] Step S24: Perform a difference operation on the current grayscale value matrix and the previous grayscale value matrix to obtain the grayscale difference matrix;

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

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

[0065] Step S27: Compare and classify the grayscale change rate data through a threshold to obtain preliminary target area marking data and non-target area data;

[0066] Step S28: Refine the boundaries of the preliminary target area marking data to obtain optimized target area data;

[0067] Step S29: Analyze the response time gradient of the optimized target area data to obtain response-optimized target area data.

[0068] In the embodiment of the present invention, the display control unit receives the motion area data (binary matrix, with a size of 1920×1080) obtained in the previous step, traverses the matrix, and when the value is 1, records the corresponding pixel coordinates (x, y). The pixel coordinates within all motion areas are stored as a motion area pixel coordinate set, and these coordinates are organized into a two-dimensional array structure for quick access in subsequent steps; based on the motion area pixel coordinate set, the display control unit extracts the current image frame data. For each pixel point (x, y) in the coordinate set, it queries the grayscale value of this point in the current image frame. The grayscale value extraction method is to convert the RGB three channels into a single-channel grayscale value according to the formula Gray = 0.299×R + 0.587×G + 0.114×B, forming the current grayscale value matrix, which only contains the grayscale values of the pixel points within the motion area; the display control unit uses the same coordinate set and grayscale conversion method to extract the grayscale values of the corresponding pixel points from the previous image frame data, forming the previous grayscale value matrix; the display control unit performs a pixel-level difference operation on the current grayscale value matrix and the previous grayscale value matrix. The difference calculation formula is Diff(x, y) = Current(x, y) - Previous(x, y), obtaining the grayscale difference matrix, which records the change amount of the grayscale value of each pixel point within the motion area; the display control unit first calculates the grayscale change ratio Ratio(x, y) = Diff(x, y) / Current(x, y), and then performs a long-term effect evaluation. This evaluation analyzes the grayscale change history of the pixel points at the same position within 5 consecutive frames. The specific method is as follows: for each pixel point in the current motion area, it extracts the grayscale values of this position in the previous 4 frames, calculates the cumulative change trend Trend(x, y) = ∑(0≤i≤4)[w(i)×(Frame(t - i, x, y) - Frame(t - i - 1, x, y))], where the weight coefficient w is [0.4, 0.3, 0.15, 0.1, 0.05], and generates grayscale change trend data according to the consistency between the cumulative trend and the change in the current frame; the display control unit applies a 5×5 Gaussian smoothing filter to the grayscale change trend data, and the filter kernel parameters are based on the standard deviation 0.8 Generate and perform a two-dimensional convolution operation to eliminate local mutations and obtain smoothed gray-scale change rate data; the display control unit sets an upper threshold of 25 and a lower threshold of 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 regional boundary refinement processing. First, apply an 8-neighborhood connected region marking algorithm to connect adjacent target area pixels into blocks, then apply an active contour algorithm to each block to align the boundary along the maximum of the gray-scale gradient direction, accurately locate the regional boundary, and finally remove 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. By querying the built-in liquid crystal response time parameter table, calculate the theoretical response time of each pixel based on the starting gray-scale value and the target value. When the response time exceeds 16 milliseconds (corresponding to a 60Hz refresh rate), mark the pixel as a response optimization candidate point, and then based on spatial continuity, form all connected response optimization candidate points into response optimization target area data.

[0069] The present invention can ensure the accuracy of subsequent calculations, avoid redundant processing caused by global calculations, and improve calculation efficiency by traversing the motion area data at the pixel level and extracting the pixel coordinate set of the motion area. Based on the pixel coordinate set of the motion area, the gray-scale value matrices of the current and previous image frames are respectively extracted, so that the calculation of gray-scale changes is based on the actual motion area, improving the pertinence of the data. By performing a difference operation on the gray-scale value matrices of the current and previous frames, the brightness change of each pixel point can be accurately obtained, providing a basis for further calculations. Based on the gray-scale difference matrix and the current gray-scale value matrix, a ratio calculation is performed, and combined with long-term effect evaluation, the system can consider the historical trend of gray-scale changes, avoid misjudgments caused by short-term changes, and improve the stability of motion detection. Smoothing the gray-scale change trend data can effectively suppress transient noise, ensure the continuity of the gray-scale change rate data, and improve data reliability. Classifying the gray-scale change rate data by threshold comparison makes the distinction between the target area and the non-target area more accurate, reducing the impact caused by misjudgments. Performing boundary refinement processing on the preliminary target area marking data can optimize the regional edge, making it more in line with the actual motion characteristics and avoiding calculation errors caused by blurred boundaries. Optimizing the target area data based on response time gradient analysis enables the finally obtained response optimization target area to accurately correspond to the motion part that needs to be optimized, improving the accuracy of over-drive processing.

[0070] Preferably, the continuity evaluation of the response optimization target area data in step S3 includes:

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

[0072] Performing clustering processing on the initial connected area marking data to obtain target area clustering data, where the minimum area limit for clustering processing is less than or equal to 16 pixels;

[0073] Extracting regional shape feature data from the target area clustering data;

[0074] Performing rectangular fitting calculation on the regional shape feature data to obtain initial rectangular area data;

[0075] The fitting error in the rectangular fitting calculation is less than or equal to 15%, and the rotation angle limit is four directions of 0°, 45°, 90°, and 135°;

[0076] Performing overlap degree calculation on the initial rectangular area data to obtain rectangular overlap degree data, where the overlap ratio threshold limit in the overlap degree calculation is less than or equal to 30%.

[0077] In the embodiment of the present invention, the display control unit performs pixel connectivity analysis on the response optimization target area data, traverses each pixel point using a two-dimensional scanning algorithm, and for each pixel marked as a response optimization candidate point, checks its 8-neighborhood connectivity. The mutually connected pixel points are grouped into the same marked group to generate a unique area identifier, which represents different connected areas in integer form (starting from 1 and incrementing). Finally, the initial connected area marked data is formed. This data is a two-dimensional matrix, and the value of each element in the matrix is the identifier of the connected area to which the pixel belongs or 0 (indicating a non-response optimization area). The display control unit performs clustering processing on the initial connected area marked data. First, it counts the number of pixels corresponding to each identifier to form an area area statistics table. Then, it sets the minimum area limit to 16 pixels. For areas with an area less than or equal to 16 pixels, the display control unit executes the K-means clustering algorithm to calculate the Euclidean distance between these small areas and the surrounding large areas (areas 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 areas respectively. Each small area is merged into the large area with the closest distance to form the target area clustering data. The display control unit extracts area shape feature data from the target area clustering data, and calculates the following feature parameters for each clustering area: a set of boundary points, centroid coordinates (cx, cy) = average(x, y), area A = count(pixels), perimeter P = count(boundary_pixels), compactness C = 4π × A / P^2, and major axis direction θ = 0.5×arctan(2μ11 / (μ20 - μ02)), where μpq is the central moment of order (p,q), and these characteristic parameters constitute the regional shape feature data; the display control unit performs rectangular fitting calculation on the regional shape feature data. Based on the principal axis direction θ of each region, which is restricted to one of the four directions: 0°, 45°, 90°, and 135°, the standard angle closest to the original direction is selected, and then a rectangular boundary is constructed along this direction. The length and width of the rectangle are determined by the maximum projection lengths of the region in the principal axis direction and the perpendicular direction respectively. Calculate the ratio of the actual area covered by the rectangle to the area of the original region, ensuring that the fitting error is less than or equal to 15%. If the error exceeds the threshold, boundary adjustment is performed, and finally the initial rectangular region data is obtained; the display control unit calculates the overlap degree of the initial rectangular region data. For each pair of adjacent rectangular regions R1 and R2, calculate their overlapping area S_overlap = Area(R1 ∩ R2), and then calculate the overlap ratio Overlap_ratio = S_overlap / min(Area(R1), Area(R2)). Set the overlap ratio threshold to 30%. When Overlap_ratio is less than or equal to 30%, retain the two rectangular regions; when Overlap_ratio is greater than 30%, merge the two rectangular regions into a larger rectangle, and the boundary of the merged rectangle is the minimum circumscribed rectangle of the two original rectangles, thus obtaining the rectangular overlap degree data, which contains the overlapping situation and merge decision information of each pair of rectangular regions.

[0078] The present invention can effectively identify continuous pixel regions through pixel connectivity analysis of the response optimization target region data, improve the integrity of the target region, and avoid detection errors caused by isolated pixels. Clustering processing is performed based on the initial connected region marking data, and the minimum region area is limited, so that only sufficiently significant regions are retained, thereby reducing the interference of irrelevant regions and improving the accuracy of target region screening. Extracting regional shape feature data from the target region clustering data enables subsequent rectangular fitting calculations to be based on real morphological features and improves the fitting effect. Performing rectangular fitting calculation on the regional shape feature data and limiting the fitting error and rotation angle enables the generated rectangular region to better adapt to the pixel arrangement characteristics of the liquid crystal display screen and improves the regional positioning accuracy. Calculating the overlap degree of the initial rectangular region data and limiting the overlap ratio threshold enables overly overlapping regions to be identified and further optimized, avoiding unnecessary signal enhancement or information loss caused by improper region division.

[0079] Particularly importantly, the pixel connectivity analysis of the response optimization target region data includes:

[0080] Performing binarization processing on the response optimization target region data to obtain target region mask data;

[0081] Perform a preliminary screening of connected components on the target region mask data to obtain an initial connected component labeling matrix;

[0082] Perform boundary correction on the initial connected component labeling matrix to obtain corrected connected region data;

[0083] Perform small region filtering on the corrected connected region data to obtain initial connected region labeling data.

[0084] In an embodiment of the present invention, the display control unit performs binarization processing on the response optimization target area data. First, a threshold T = 0.5 is set, and each element in the response optimization target area data matrix is traversed. When the element value is greater than the threshold T, it is set to 1; otherwise, it is set to 0, forming a two-dimensional matrix containing only 0 and 1. The elements with a value of 1 in this matrix represent the pixel points that need to optimize the response time, and the elements with a value of 0 represent the pixel points that do not need to be optimized. Thus, the target area mask data is obtained, and the size of this mask data is the same as the original image frame, which is 1920×1080. The display control unit performs initial screening of connected components on the target area mask data and uses the two-pass algorithm for marking. In the first pass, starting from the upper left corner, it scans row by row. For each pixel point with a value of 1, it checks the 4-neighborhood pixels that have been scanned on its left and above. If the neighborhood pixels are all 0, a new label value is assigned to the current pixel. If there are pixels with a value of 1 in the neighborhood, the current pixel is marked with the same label value as its adjacent labeled pixel, and the equivalence relationship is recorded. In the second pass, according to the equivalence relationship table established in the first pass, the labels with equivalent relationships are merged to ensure that each connected component has a unique label value, thus obtaining the initial connected label matrix. The display control unit performs boundary correction on the initial connected label matrix. First, the boundary point set of each connected component is calculated. The boundary point is defined as a point where at least one 8-neighborhood pixel does not belong to the current area. Then, the gradient vector flow algorithm is applied to each boundary point. This algorithm is based on the gray-level gradient field of the current image frame and iteratively adjusts the position of the boundary point. The iterative 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, and the number of iterations is set to 10 times to ensure that the boundary point is located at the maximum of the gray-level gradient, thus obtaining the corrected connected component data. The display control unit performs small area filtering on the corrected connected component data. First, the number of pixels in each connected component is counted as the area of the region. Then, a minimum area threshold Amin = 8 pixels is set. For a connected component with an area smaller than Amin, the number of boundary contact pixels with its adjacent large region (area greater than or equal to Amin) is calculated. If the proportion of the contact pixels in the perimeter of the small region is greater than 40%, the small region is merged into the adjacent large region. If the contact proportion is less than or equal to 40%, the label value of this region is set to 0, that is, removed from the response optimization target area. After completing the small area filtering, the label values of the remaining connected components are renumbered to ensure that the label values are continuous, thus obtaining the initial connected component label data.

[0085] By performing binarization processing on the data of the response optimization target area, the features of the target area are made more prominent, which helps subsequent connectivity analysis and area extraction. Based on the target area mask data, a preliminary screening of connected components can quickly identify connected areas, improve the efficiency of area extraction, and reduce the interference of isolated noise. By correcting the boundaries of the initial connected label matrix, the extracted target area has a more accurate boundary contour, avoiding morphological distortion caused by edge breakage or noise. By filtering small areas from the corrected connected area data, noise interference and irrelevant small areas can be effectively removed, ensuring that the finally extracted connected area is more stable and meets the optimization requirements.

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

[0087] Screen the rectangle overlap degree data based on the overlap threshold. When the rectangle overlap degree data is greater than the overlap threshold, the rectangle area data corresponding to the rectangle overlap degree data is merged to obtain the merged rectangle area data;

[0088] The overlap threshold is limited to be between 30% and 50%. If the rectangle overlap degree data is less than 30% overlap, it will cause irrelevant areas to be wrongly merged. If the rectangle overlap degree data is greater than 50% overlap, it will cause significantly relevant areas to be unable to be merged;

[0089] Perform pixel boundary expansion on the merged rectangle area data to obtain the expanded boundary rectangle area data;

[0090] Perform pixel alignment processing on the expanded boundary rectangle area data to obtain the aligned rectangle area data;

[0091] Perform spatial position analysis and grouping processing on the aligned rectangle area data to obtain a continuous rectangle target area group.

[0092] In an embodiment of the present invention, the display control unit filters the rectangle overlap degree data based on an overlap threshold. The overlap threshold is set to 40%, which is the optimal value selected within the range of 30% - 50%. During the system testing, it is confirmed that when the overlap threshold is lower than 30%, irrelevant regions are easily mis-merged, resulting in over-fusion; when the overlap threshold is higher than 50%, significantly relevant regions cannot be merged, resulting in fragmentation. The display control unit traverses all pairs of rectangles, calculates the overlap degree Oij of each pair of rectangles Mi and Mj as Oij = Area(Mi ∩ Mj) / min(Area(Mi), Area(Mj)). When Oij is greater than 40%, a merge 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). Then, Mi and Mj are removed from the rectangle list, and the newly merged rectangle is added to the list. This process is repeated until there are no rectangle pairs that meet the merge conditions, obtaining the merged rectangle region data. The display control unit performs pixel boundary expansion on the merged rectangle region data. First, it calculates the boundary pixel gray level gradient of each rectangle region. The gray level 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, an expansion parameter δ = 3 pixels is set, and each of the four boundaries of each rectangle is expanded outward by δ pixels. However, during the expansion process, the following conditions need to be met: the gray level gradient G(x, y) of the pixels within the expansion region is less than the threshold Gthreshold = 15, the expansion does not exceed 10% of the original rectangle side length, and the expanded rectangle does not overlap with other un-merged rectangles, thereby obtaining the expanded boundary rectangle region data. The display control unit performs pixel alignment processing on the expanded boundary rectangle region data, aligning and adjusting the rectangle region coordinates based on the pixel grid of the current display screen. First, the upper left corner coordinates (x1, y1) and the lower right corner coordinates (x2, y2) of the rectangle are rounded down and up respectively to ensure coverage of all relevant pixels. 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, the y coordinate is adjusted to a multiple of 4, and the lower right corner coordinates are adjusted accordingly to ensure that the rectangle region can be aligned with the data block of the display screen driving circuit at the hardware level, improving the processing efficiency, thereby obtaining the aligned rectangle region data. The display control unit performs spatial position analysis and grouping processing on the aligned rectangle region data. First, a spatial index structure (such as an R-tree) is established, and all rectangle regions are inserted into this structure. Then, a spatial clustering algorithm is executed. For each rectangle region Mi, its spatial neighboring 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) = 0.6×(1 - |Wi - Wj| / max(Wi, Wj)) + 0.4×(1 - |Hi - Hj| / max(Hi, Hj)), where Wi and Hi are the width and height of rectangle Mi respectively. When the similarity S(Mi, Mj) is greater than 0.75 and the distance between the two rectangles in the horizontal or vertical direction is less than 2 times the side length of the smaller rectangle, these two rectangles are assigned to the same group, thereby forming a group of continuous rectangle target regions.

[0093] In the present invention, by screening the rectangle overlap degree data based on an overlap threshold, it is ensured that the merging process is only performed on regions with relatively high correlation, thereby avoiding display distortion caused by incorrect merging and preventing the influence of an overly high threshold limit on the fusion of relevant regions. The overlap threshold range is reasonably set to optimize the accuracy of region merging, ensuring that the finally extracted target regions meet the requirements of display optimization. Pixel boundary expansion is performed on the merged rectangle region data to make the region boundaries smoother, reduce target loss caused by boundary truncation, and improve the stability of subsequent calculations. Through pixel alignment processing, the rectangle regions are made consistent with the display grid, improving the calculation accuracy of display signals and optimizing the driving control effect. Spatial position analysis and grouping processing are performed on the aligned rectangle region data to make the structure of continuous target regions more reasonable, ensuring better integrity and consistency of the final optimization result in the display screen.

[0094] Particularly importantly, the screening of the rectangle overlap degree data based on the overlap threshold includes:

[0095] Screening the rectangle overlap degree data set based on a preset overlap threshold to obtain rectangle overlap degree data that meets the merging conditions;

[0096] Performing rectangle region data matching based on the rectangle overlap degree data that meets the merging conditions to obtain a group of rectangle region data to be merged;

[0097] Performing boundary calculation on the group of rectangle region data to be merged to obtain the merged rectangle region data.

[0098] In the embodiments of the present invention, the display control unit filters the rectangular overlap degree dataset based on a preset overlap threshold. First, a preset overlap threshold T = 40% is set, and this threshold value has been verified to effectively balance the merging accuracy and regional integrity. The display control unit traverses each record in the rectangular overlap degree dataset, which contains the overlap degree values Oij of all rectangle pairs (Ri, Rj). It checks whether each overlap degree value Oij is greater than the preset overlap threshold T. When Oij > T, the rectangle pair is marked as meeting the merging condition, and the identifier of the rectangle pair and the corresponding overlap degree value are recorded to form the rectangular overlap degree data that meets the merging condition. This data structure contains a triple (i, j, Oij), indicating that the overlap degree of rectangles 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 the identifiers of all rectangles, and the edge set E contains the rectangle 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 keeping the graph connected, the edges with the largest overlap degree are selected for connection to avoid forming loops, ensuring that each rectangle is merged with at most one rectangle with the largest overlap degree to prevent excessive fusion caused by chain merging. Finally, a set of rectangular region data to be merged is obtained. This data set consists of multiple non-overlapping rectangle pair sets, and the rectangles within each set will be merged into a larger rectangle. The display control unit calculates the boundaries of the set of rectangular region data to be merged. For each set of rectangles to be merged {R1, R2,..., Rn}, its minimum bounding rectangle is calculated. The calculation method is: the upper left corner coordinates (x1, y1) = min(R1.x1, R2.x1,..., Rn.x1), min(R1.y1, R2.y1,..., Rn.y1), and the lower 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 size limit conditions of the display control unit for rectangles: the aspect ratio does not exceed 5:1 or 1:5, and the area does not exceed 1 / 8 of the area of the original image frame. If the limit is exceeded, the recursive binary method is applied to divide the set to be merged into two subsets, and their minimum bounding rectangles are calculated respectively 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 list of corresponding original rectangle identifiers.

[0099] The present invention screens the rectangular overlap degree data set based on a preset overlap threshold, effectively ensuring that only rectangular regions meeting the merging conditions participate in subsequent merging processing, avoiding mis-merging of irrelevant regions, and thus improving the accuracy of region matching. Matching the rectangular region data based on the rectangular overlap degree data meeting the merging conditions makes the region merging more in line with the actual display requirements, avoiding unnatural display or information loss caused by incorrect matching. Calculating the boundaries of the rectangular region data groups to be merged helps to accurately determine the boundaries of the merged regions, improves the display effect after region merging, and optimizes the coherence and stability of the display regions.

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

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

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

[0103] Step S43: Perform index query on the gray scale conversion look-up table based on the gray scale difference data and the temperature compensation parameter to obtain the basic over-drive voltage value;

[0104] Step S44: Adjust the dynamic response characteristics and optimize the mode of the basic over-drive voltage value to obtain the temporary over-drive voltage value.

[0105] In an embodiment of the present invention, the display control unit obtains current temperature data, reads the real-time temperature value through a temperature sensor integrated on the border of the liquid crystal panel, with a sampling accuracy of 0.1 °C and a sampling frequency of once per frame. The analog signal output by the sensor is converted into a digital quantity through a 12-bit ADC to obtain the original temperature data; then, mapping calculation is performed on the current temperature data. 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, and the mapping formula is α = 1 + k×(T - T0)2, where T0 is the nominal working temperature of the liquid crystal, 25 °C, and k is the temperature coefficient, -0.0015 / °C2. When the temperature is lower than T0, the activity of liquid crystal molecules slows down, the response time increases, and α > 1; when the temperature is higher than T0, the activity of liquid crystal molecules accelerates, the response time decreases, and α < 1, thus obtaining the liquid crystal temperature compensation coefficient; the display control unit calculates the difference between the current gray scale value and the target gray scale value of each region in the continuous rectangular target region group. First, it reads the pixel values in the corresponding rectangular region in the current frame data and the next frame data from the frame buffer, and converts the RGB values into gray scale values. The conversion formula is Gray = 0.299×R + 0.587×G + 0.114×B, and then calculate the grayscale difference ΔGray = Next_Gray - Current_Gray for each pixel. Statistically analyze the difference values within each rectangular region, calculate the average difference μ, standard deviation σ, and the difference distribution histogram. Divide the rectangular regions into three categories according to the histogram distribution characteristics: rising region (ΔGray > 0), falling region (ΔGray < 0), and mixed region (ΔGray distribution straddles 0), thus obtaining the grayscale difference data. The display control unit performs an index query on the grayscale conversion lookup table based on the grayscale difference data and temperature compensation parameters. The grayscale conversion lookup table is a three-dimensional matrix LUT[Start_Gray][End_Gray][Temp_Index], which stores the theoretical overdrive voltage values under different starting grayscale values, target grayscale values, and temperature conditions. For the dominant grayscale difference type of each rectangular region, query the corresponding overdrive voltage value. The query method is as follows: for the rising region, query V_up = LUT[Current_Gray][Next_Gray][Temp_Index] × α; for the falling region, query V_down = LUT[Current_Gray][Next_Gray][Temp_Index] × α; for the mixed region, calculate the overdrive voltage values for the rising and falling parts respectively, and then perform a weighted average according to the area ratio to obtain the basic overdrive voltage value. The display control unit adjusts the dynamic response characteristics and optimizes the mode of the basic overdrive voltage value. First, according to the motion characteristics of the current display content, such as motion speed, acceleration, and direction continuity, correct the basic overdrive voltage value. The correction formula is V_adjusted = V_base × (1 + β × Speed + γ × Accel), where β is the speed coefficient 0.05 / (pixel / frame), and γ is the acceleration coefficient 0.02 / (pixel / frame²). Then analyze the display content type and optimize the overdrive mode to one of four preset modes: standard mode (balanced response time and overshoot), game mode (minimize response time, allow greater overshoot), video mode (optimize grayscale transition smoothness), and text mode (minimize overshoot, improve text clarity). Each mode corresponds to a different set of compensation parameters. Finally, adjust V_adjusted by applying the parameter set of the selected mode to obtain the temporary overdrive voltage value.

[0106] By obtaining and performing mapping calculations on the current temperature data, the present invention can accurately obtain the liquid crystal temperature compensation coefficient, thereby ensuring that the influence of temperature fluctuations on liquid crystal display performance is effectively compensated, and improving the consistency and stability of the display. By calculating the difference between the current gray scale value and the target gray scale value for each region in the continuous rectangular target region group, the accurate grasp of the gray scale difference between different regions is ensured, providing a reliable data basis for the subsequent adjustment of the overdrive voltage value. By performing index queries on the gray scale conversion lookup table based on the gray scale difference data and temperature compensation parameters, the accurate basic overdrive voltage value can be obtained for the specific requirements of each region, ensuring the accurate matching of the overdrive voltage. By adjusting the dynamic response characteristics and optimizing the mode of the basic overdrive voltage value, the temporary overdrive voltage value can better adapt to the display requirements of different regions, thereby optimizing the display effect and reducing the blurring or ghosting phenomena in dynamic images.

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

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

[0109] Step S52: Calculate the pulse width of the response optimization target region data based on the safe voltage value to obtain the pulse width modulation parameter of the target region;

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

[0111] Step S54: Calculate the standard voltage value for the non-target region data to obtain the standard region voltage value;

[0112] Step S55: Perform standard pulse width modulation based on the standard region voltage value to obtain the pulse width modulation parameter of the standard region;

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

[0114] In an embodiment of the present invention, the display control unit performs voltage range limiting processing on the temporary overdrive voltage value. First, it determines that the voltage output range of the liquid crystal driving chip is from Vmin = 0V to Vmax = 5V. Then, it performs truncation limiting on the temporary overdrive voltage value V_temp. When V_temp < Vmin, V_temp is set to Vmin; when V_temp > Vmax, V_temp is set to Vmax. Next, it performs voltage slope limiting. It calculates the voltage change rate dV / dt of pixels at the same position in adjacent two frames. When the change rate exceeds the threshold of 2V / frame, it applies a voltage gradient smoothing algorithm for limiting to ensure a smooth transition of voltage changes and avoid image artifacts caused by voltage jumps. Finally, it applies voltage stability checking, analyzes the voltage change trend within 5 consecutive frames, and eliminates the oscillation phenomenon to obtain a safe voltage value. The display control unit calculates the pulse width for the data in the response optimization target area based on the safe voltage value. First, it establishes a voltage-pulse width mapping table PWM_Table, which describes the pulse width modulation parameters corresponding to different voltage values. Then, it performs a look-up table conversion on the safe voltage value V_safe to obtain the initial pulse width value PWM_init = PWM_Table[V_safe]. Next, it performs local adjustment according to the pixel position and surrounding pixel values. When the pixel is at a high-contrast edge, it applies an edge enhancement algorithm to appropriately increase the pulse width and enhance the edge sharpness; when the pixel is in a smooth gradient area, it applies a smoothing algorithm to reduce the pulse width change and keep the color transition natural. Finally, it quantizes the pulse width, converts the continuous value into an 8-bit quantization value (0 - 255) to obtain the pulse width modulation parameters for the target area. The display control unit converts the pulse width modulation parameters for the target area into a driving waveform. First, according to the driving mode of the liquid crystal display screen, it generates a basic driving waveform template. Then, it modifies the waveform duty cycle based on the pulse width modulation parameters to generate positive and negative polarity driving waveforms. Next, it adjusts the waveform timing to ensure that the rising edge and falling edge of the driving signal are respectively at the optimal moments to reduce signal cross-interference. Finally, it applies overshoot compensation technology to add a short high-voltage pulse at the starting stage of the waveform to accelerate the initial response of the liquid crystal molecules to obtain an optimized driving signal for the target area. The display control unit calculates the standard voltage value for the non-target area data. First, it reads the RGB data of the non-target area pixels from the frame buffer and performs grayscale conversion. Then, it queries the standard grayscale-voltage mapping table Standard_LUT to obtain the standard voltage value V_std = Standard_LUT[Gray]. Next, it applies gamma correction to non-linearly adjust the voltage value according to the gamma characteristic curve of the display screen to ensure a linear change in visual brightness. Finally, it applies panel uniformity compensation to finely adjust the voltage values of different areas according to the position characteristic map of the liquid crystal panel to compensate for the brightness non-uniformity caused by panel manufacturing errors to obtain the standard area voltage value;The display control unit performs standard pulse width modulation based on the standard region voltage value. Using the same voltage-pulse width mapping table PWM_Table as in step S52, it looks up and converts the standard region voltage value V_std to obtain the standard pulse width value PWM_std = PWM_Table[V_std]. Then, it adjusts the pulse width using the display color mode parameters to achieve different color performance styles. Finally, it quantizes the pulse width to 8 bits to obtain the standard region pulse width modulation parameters. The display control unit performs drive waveform conversion on the standard region pulse width modulation parameters. First, based on the standard drive method of the liquid crystal display screen, it generates a standard waveform template. Then, it modifies the waveform duty cycle according to the pulse width modulation parameters to generate positive and negative polarity drive waveforms. Next, it sets the AC drive polarity inversion to ensure that each pixel point undergoes polarity inversion between consecutive frames, avoiding image retention caused by DC bias. Finally, it sorts the waveform data according to the scanning timing of the display screen to obtain the standard drive signal for the standard region. This signal, together with the optimized drive signal for the target region, is sent to the liquid crystal panel through the display driver IC to complete the drive optimization of the entire display screen.;

[0115] In the present invention, by performing voltage range limit processing on the temporary over-drive voltage value, it ensures that the voltage value is within a safe range, avoiding damage or abnormal display of the liquid crystal display screen caused by too high or too low voltage, and improving the stability and safety of the system. Based on the safe voltage value, it calculates the pulse width for the response optimization target region data, accurately obtaining the pulse width modulation parameters for the target region, thus providing a necessary basis for the generation of the optimized drive signal. By performing drive waveform conversion on the pulse width modulation parameters for the target region, it can generate an optimized drive signal suitable for the display requirements of the target region, improving the display effect of dynamic images and reducing ghosting and blurring phenomena. It calculates the standard voltage value for the non-target region data to ensure that the display signal for the non-target region meets the standard requirements, thus guaranteeing the display stability of the non-target region. By performing standard pulse width modulation based on the standard region voltage value, the obtained standard region pulse width modulation parameters effectively ensure that the display effect of the non-target region is not affected. By performing drive waveform conversion on the standard region pulse width modulation parameters, it can generate a standard drive signal adapted to the standard region, ensuring the normal display of all regions of the liquid crystal display screen and guaranteeing the balance and consistency of the overall display effect.

[0116] Preferably, the partitioned drive control of the liquid crystal display screen based on the optimized drive signal and the standard drive signal in step S6 includes:

[0117] Mapping and dividing the control region of the liquid crystal display screen based on the optimized drive signal and the standard drive signal to obtain region drive mapping data;

[0118] Perform temporal sorting on the region-driven mapping data to obtain partition-driven temporal data, where the minimum temporal interval in the temporal sorting is limited to be greater than or equal to 100 microseconds;

[0119] Based on the partition-driven temporal data, apply different voltage values to each sub-region of the liquid crystal display to obtain region-differentiated driving voltage values;

[0120] Perform temperature factor compensation calculation on the region-differentiated driving voltage values 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 range 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, adjust the voltage gradient of the boundary pixels in the region to obtain boundary smooth transition data;

[0123] Generate and output control of the driving signal for the boundary smooth transition data to obtain the final partition-driven control signal, where the signal update frequency of the final partition-driven control signal is synchronized with the frame rate, and the signal type is less than or equal to 4 standard waveform types;

[0124] Based on the final partition-driven control signal, monitor the liquid crystal response time in real-time to obtain the partition-driven control result.

[0125] In the embodiments of the present invention, for the zoned driving control of a liquid crystal display screen based on an optimized driving signal and a standard driving signal, first, a pixel mapping method is used to map and divide the control regions corresponding to the optimized driving signal and the standard driving signal. By establishing the association relationship between pixel coordinates and driving signals, regional driving mapping data is generated. The regional driving mapping data undergoes a timing sorting process by a data processing module. According to the requirement that the set minimum timing interval limit is greater than or equal to 100 microseconds, the driving signals of each sub-region are re-allocated on the time axis to generate zoned driving timing data, ensuring that the loading timings of the driving signals of each sub-region meet the hardware control requirements. Based on the zoned driving timing data, the driving control unit applies different voltage values to each sub-region of the liquid crystal display screen. An independent voltage control circuit is used to apply an accurately matched driving voltage to each sub-region, thereby forming regionally differentiated driving voltage values. Subsequently, the regionally differentiated driving voltage values enter a temperature compensation calculation module, where they are corrected in real time according to the current temperature detection data. The temperature detection accuracy is set to ±1°C, the temperature compensation range is set to 5 - 45°C, and the driving voltage is dynamically adjusted according to the standard of updating the frequency once per second for the temperature compensation coefficient, ensuring the voltage compensation accuracy in different temperature environments. The corrected driving voltage values are transmitted to a boundary pixel voltage adjustment unit, where the pixel voltages of adjacent sub-regions are calculated for gradients, and a digital filtering algorithm is used to smooth the voltage gradients to generate boundary smooth transition data, ensuring that the gray-scale changes between different driving regions remain stable. Subsequently, the boundary smooth transition data is converted into a final zoned driving control signal by a signal processing module. The signal update frequency is synchronized with the frame rate of the liquid crystal display screen, and the driving signal type is set to no more than 4 standard waveform types to adapt to different gray-scale transition requirements. The final zoned driving control signal is transmitted to the liquid crystal display screen driving circuit through a high-speed data bus, the liquid crystal response time is monitored in real time, a zoned driving control result is generated, and the zoned driving signals for the next frame are adjusted based on the feedback data.

[0126] The present invention maps and divides the control area of the liquid crystal display screen based on the optimized driving signal and the standard driving signal, ensuring precise control of the display area and laying a foundation for the subsequent optimization of the driving signal. The timing sorting process is performed on the regional driving mapping data, effectively optimizing the driving timing of each region and ensuring the stable performance of the liquid crystal display screen at a high refresh rate. The minimum limit of the timing interval is 100 microseconds, which helps to avoid screen tearing and stuttering phenomena. Different voltage values are loaded on each sub-region of the liquid crystal display screen based on the partition driving timing data, and the generated regional differential driving voltage values enable each display region to provide an appropriate voltage according to actual needs, thereby improving the dynamic responsiveness of the display. By performing temperature factor compensation calculation on the regional differential driving voltage values, the corrected driving voltage values are obtained, effectively avoiding the negative impact of temperature changes on the display effect. The temperature compensation accuracy is limited within ±1°C, ensuring the stability and accuracy of the driving voltage. Based on the corrected driving voltage values, the voltage gradient of the boundary pixels of the region is adjusted, successfully achieving a smooth transition at the boundary and avoiding obvious unevenness or flickering at the display edge, improving the overall quality of the display effect. The driving signal is generated and output controlled based 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. By real-time monitoring 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 screen and the high-quality realization of the display effect.

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

[0128] Performing real-time optical response acquisition on the display area after partition driving of the liquid crystal display screen based on the partition driving control result to obtain regional response curve data;

[0129] Measuring the rise time and fall time of different gray-scale conversions based on the regional response curve data to obtain a regional response time matrix;

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

[0131] Performing a visual persistence effect model calculation on the regional response time matrix to obtain pixel blur width data, where the visual persistence time in the visual persistence effect model calculation is limited to 8-16 milliseconds;

[0132] Performing sharpness analysis on the edge of the target region based on the pixel blur width data to obtain an edge sharpness score;

[0133] Track the change trajectory of the target area location based on the partition drive control result to obtain the motion trajectory clarity data;

[0134] Calculate the uniformity of the brightness transition of adjacent areas based on the partition drive control result to obtain the brightness transition smoothness score;

[0135] Evaluate and calculate the color restoration accuracy based on the partition drive control result to obtain the color fidelity data, where the number of reference color points is less than or equal to 8 standard color points;

[0136] Calculate the contrast difference based on the partition drive control result to obtain the dynamic contrast score;

[0137] Perform weighted fusion calculation on the edge sharpness score, motion trajectory clarity data, brightness transition smoothness score, color fidelity data and dynamic contrast score to obtain the comprehensive quality prediction value;

[0138] Divide the global display effect level based on the comprehensive quality prediction value to obtain the display effect evaluation data.

[0139] In the embodiments of the present invention, in the process of dynamically evaluating the clarity of the partition driving control result, first, a high-precision optical sensor is used to collect real-time optical responses of the display area after the partition driving of the liquid crystal display screen, and a high-speed sampling circuit is used to record the change in light intensity to generate regional response curve data. The regional response curve data is input into the signal processing module, and the rise time and fall time of different gray-scale conversions are calculated through a digital differential algorithm to form a regional response time matrix. The gray-scale conversion type is set to 16 typical conversion types, the measurement range of the response time is limited to the 10%-90% standardized brightness range, and the measurement error is controlled within ±0.5 milliseconds. The regional response time matrix generates pixel blur width data by calculating the visual persistence effect model. The visual persistence time is limited within the range of 8-16 milliseconds, and the influence of visual residue on the clarity of the dynamic picture is analyzed by combining the time integration method. Based on the pixel blur width data, the sharpness of the target area edge is analyzed, the brightness change rate of the edge pixels is extracted by using the gradient calculation method, and the edge sharpness score is calculated. The partition driving control result is further input into the trajectory analysis module, and the motion vector is calculated by analyzing the position change of the target area in consecutive frames to obtain the motion trajectory clarity data. The calculation of the brightness transition between adjacent areas adopts a spatial filtering method, and the brightness transition smoothness score is generated by analyzing the uniformity of the brightness gradient. The color reproduction accuracy evaluation is based on the standard color matching algorithm, and the color fidelity data is obtained by calculating the color difference between the driving display result and 8 standard color points. The dynamic contrast score is calculated by using the local contrast analysis method, and the final dynamic contrast score is obtained through the distribution statistics of the ratio of the maximum and minimum brightness in the area. The edge sharpness score, the motion trajectory clarity data, the brightness transition smoothness score, the color fidelity data, and the dynamic contrast score are input into the quality evaluation unit, and the comprehensive quality prediction value is calculated by using the weighted fusion calculation method. The global display effect level threshold is set in combination with the display screen specification parameters, and finally the display effect evaluation data is divided.

[0140] The present invention can acquire regional response curve data by collecting real-time optical responses of the display area after partition driving the liquid crystal display screen based on the partition driving control results, so as to accurately understand the dynamic response characteristics of the display area. By measuring the rise time and fall time of different gray-scale conversions based on the regional response curve data, a regional response time matrix is obtained, which effectively helps to identify the delay problems in gray-scale changes and ensures that the response speed is within a predetermined time range. The limitation of the gray-scale conversion type is within 16 typical conversion types, and the rise / fall time is measured within the range of 10%-90% of the normalized brightness, ensuring the accuracy of the measurement, and the error is limited within ±0.5 milliseconds, providing high-precision response time data. By calculating the persistence of vision effect model on the regional response time matrix, the pixel blur width data can be accurately obtained, providing a basis for further display optimization. By performing sharpness analysis on the edges of the target area based on the pixel blur width data, an edge sharpness score is obtained, thereby optimizing the edge clarity in the display effect. By tracking the change trajectory of the target area position, the motion trajectory clarity data can be obtained, effectively improving the clarity of dynamic images. The calculation of the luminance transition uniformity between adjacent areas further optimizes the transition effect between display areas, obtaining a luminance transition smoothness score and reducing the visual incoherence. By evaluating the color reproduction accuracy, the color reproduction accuracy and authenticity are ensured, where the number of reference color points is limited within 8 standard color points, ensuring 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, obtaining a dynamic contrast score. Finally, by performing weighted fusion calculation on the edge sharpness score, the motion trajectory clarity data, the luminance transition smoothness score, the color fidelity data and the dynamic contrast score, a comprehensive quality prediction value is obtained, further performing a global level division on the display effect, thereby obtaining detailed display effect evaluation data, providing an effective basis for subsequent optimization and adjustment.

[0141] Preferably, the present invention further provides a display optimization system for a liquid crystal display screen, which is used to execute the above-mentioned display optimization method for a liquid crystal display screen. The display optimization system for a liquid crystal display screen includes:

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

[0143] A gray-scale change calculation module, configured to calculate the gray-scale change rate according to the motion area data; perform threshold truncation on the gray-scale change rate data to obtain response optimization target area data and non-target area data;

[0144] A target area merging module, which is used to evaluate the continuity of the response-optimized target area data, and perform merging processing based on the continuity evaluation result to obtain a group of continuous rectangular target areas;

[0145] A temperature adaptive calculation module, which is used to obtain the current temperature data; calculate the grayscale value difference of the group of continuous rectangular target areas according to the current temperature data to obtain a temporary overdrive voltage value;

[0146] A partition modulation driving module, which is used to perform pulse width modulation on the temporary overdrive voltage value, where high-frequency pulse width modulation is performed on the response-optimized target area data to generate an optimized driving signal, and standard pulse width modulation is performed on the non-target area data to generate a standard driving signal;

[0147] A clarity evaluation module, which is used to perform partition compensation driving control on the liquid crystal display based on the optimized driving signal and the standard driving signal, and perform dynamic clarity evaluation on the partition driving control result to obtain display effect evaluation data.

[0148] Therefore, from any perspective, the embodiments should be regarded as exemplary and non-restrictive. The scope of the present invention is not limited by the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the application documents are intended to be included in the present invention.

[0149] The above are only specific embodiments of the present invention, enabling those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be obvious to those skilled in the art. The general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. A display optimization method for a liquid crystal display screen, characterized in that: The following steps are involved: Step S1: obtaining current image frame data and previous image frame data, and calculating the inter-frame difference based on a preset pixel difference threshold; Perform threshold judgment based on inter-frame difference data to obtain motion area data; Step S2: Calculate the grayscale change rate according to the motion area data; Threshold interception is performed on the grayscale change rate data to obtain response optimization target area data and non-target area data; Step S3: performing continuity evaluation on the response optimization target area data, and performing merging processing based on the continuity evaluation result to obtain a continuous rectangular target area group; Step S4: obtaining current temperature data; calculating grayscale value differences of the continuous rectangular target area group according to the current temperature data to obtain a temporary overdrive voltage value; Step S5: performing pulse width modulation on the temporary over-driving voltage value, wherein high-frequency pulse width modulation is performed on the response optimization target area data to generate an optimized driving signal, and standard pulse width modulation is performed on the non-target area data to generate a standard driving signal; Step S6: performing partition compensation drive control on the liquid crystal display screen based on the optimized drive signal and the standard drive signal, and performing dynamic definition evaluation on the partition drive control result 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: obtaining the current image frame data and the previous image frame data, and performing noise filtering processing to obtain a standardized image frame data set; 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; Step S13: clustering adjacent pixels on the pixel difference matrix data to obtain regional difference data; Step S14: binarizing the region difference data based on a preset motion determination threshold to obtain preliminary motion region marking data; Step S15: performing morphological expansion and erosion operations on the preliminary motion region mark data to obtain optimized motion region data; Step S16: extracting motion region edge data from the optimized motion region data; Step S17: Expand the pixels of the motion region edge data 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: traverse the motion area data at pixel level to obtain a motion area pixel coordinate set; Step S22: extracting a current grayscale value matrix from the current image frame data based on the motion region pixel coordinate set; Step S23: extracting a previous grayscale value matrix from the previous image frame data based on the motion region pixel coordinate set; Step S24: performing a difference operation on the current grayscale value matrix and the previous grayscale value matrix to obtain a grayscale difference matrix; Step S25: performing ratio calculation based on the grayscale difference matrix and the current grayscale value matrix, and performing long-term effect evaluation to obtain grayscale change trend data; Step S26: Smoothing the grayscale change trend data to obtain grayscale change rate data; Step S27: performing threshold comparison and classification on the grayscale change rate data to obtain preliminary target area marking data and non-target area data; Step S28: performing boundary refinement processing on the preliminary target region marking data to obtain optimized target region data; Step S29: performing response time gradient analysis on the optimized target area data to obtain response optimized target area data.

4. The display optimization method for a liquid crystal display screen according to claim 1, characterized in that: The continuity evaluation of the response optimization target area data in step S3 includes: Perform pixel connectivity analysis on the response optimization target area data to obtain initial connected area label data; Perform clustering on the initial connected region label data to obtain the target region clustering data, where the minimum region area limit for clustering is less than or equal to 16 pixels; Extracting regional shape feature data from the target region clustering data; Performing rectangular fitting calculation on the regional 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 of 0°, 45°, 90°, and 135°; The initial rectangular area data is overlapped and calculated to obtain rectangular overlap data, wherein the overlap ratio threshold in the overlap calculation is limited to be 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 result in step S3 includes: The rectangular overlap data is screened based on the overlap threshold, and when the rectangular overlap data is greater than the overlap threshold, the rectangular area data corresponding to the rectangular overlap data is merged to obtain merged rectangular area data; The overlap threshold is limited to between 30% and 50%. If the rectangular overlap data is less than 30%, irrelevant areas will be merged incorrectly. If the rectangular overlap data is greater than 50%, obviously related areas cannot be merged. Expanding the pixel boundaries of the merged rectangular area data to obtain expanded boundary rectangular area data; Perform pixel alignment processing on the extended boundary rectangular area data to obtain aligned rectangular area data; The aligned rectangular area data is subjected to spatial position analysis and grouping processing to obtain a continuous rectangular target area group.

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: obtaining current temperature data; performing mapping calculation on the current temperature data to obtain a liquid crystal temperature compensation coefficient; Step S42: performing difference calculation on the current grayscale value and the target grayscale value of each area in the continuous rectangular target area group to obtain grayscale difference data; Step S43: performing an index query on the grayscale conversion lookup table based on the grayscale difference data and the temperature compensation parameter to obtain a basic over-driving voltage value; Step S44: dynamically adjusting the response characteristics and optimizing the mode of the basic over-driving voltage value to obtain a temporary over-driving 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: performing voltage range limiting processing on the temporary over-driving voltage value to obtain a safe voltage value; Step S52: Calculate the pulse width of the response optimization target area data based on the safety voltage value to obtain the target area pulse width modulation parameters; Step S53: converting the pulse width modulation parameters of the target area into a driving waveform to obtain an optimized driving signal for the target area; Step S54: Calculate the standard voltage value for the non-target area data to obtain the standard area voltage value; Step S55: performing standard pulse width modulation based on the standard region voltage value to obtain standard region pulse width modulation parameters; Step S56: converting the pulse width modulation parameters of the standard area into a driving waveform to obtain a standard driving signal of the standard area.

8. The display optimization method for a liquid crystal display screen according to claim 1, characterized in that: The step S6 of controlling the partition driving of the liquid crystal display screen based on the optimized driving signal and the standard driving signal includes: Mapping and dividing the control area of ​​the liquid crystal display screen based on the optimized driving signal and the standard driving signal to obtain regional driving mapping data; Performing time sequence sorting processing on the regional drive mapping data to obtain partition drive time sequence data, wherein the minimum time sequence interval in the time sequence sorting processing is limited to be greater than or equal to 100 microseconds; Based on the partition driving timing data, different voltage values ​​are loaded on each sub-area of ​​the liquid crystal display screen to obtain a regional differentiated driving voltage value; Perform temperature factor compensation calculation on the regional differentiated driving voltage value to obtain a corrected driving voltage value; 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; Adjusting the pixel voltage gradient at the region boundary based on the corrected driving voltage value to obtain boundary smooth transition data; Performing drive signal generation and output control on the boundary smooth transition data to obtain a final partition drive control signal, wherein the signal update frequency of the final partition drive control signal is synchronized with the frame rate, and the signal type is less than or equal to 4 standard waveform types; Based on the final partition driving control signal, the liquid crystal response time is monitored in real time to obtain the partition driving control result.

9. The display optimization method for a liquid crystal display screen according to claim 8, characterized in that: The step S6 of evaluating the dynamic clarity of the partition drive control result includes: Based on the partition driving control result, real-time optical response acquisition is performed on the display area of ​​the liquid crystal display screen after partition driving to obtain regional response curve data; Based on the regional response curve data, the rise time and fall time of different grayscale conversions are measured to obtain the regional response time matrix; The grayscale conversion type is limited to 16 typical conversion types, the rise / fall time definition is limited to 10%-90% standardized brightness range, and the measurement error is limited to ±0.5 milliseconds; The visual persistence effect model is calculated for the regional response time matrix to obtain pixel blur width data, wherein the visual persistence time limit in the visual persistence effect model calculation is 8-16 milliseconds; Perform sharpness analysis on the edge of the target area based on pixel blur width data to obtain edge sharpness score; Based on the partition drive control results, the target area position change trajectory is tracked to obtain the motion trajectory clarity data; Based on the partition drive control results, the uniformity of brightness transition of adjacent areas is calculated to obtain the brightness transition smoothness score; The color reproduction accuracy is evaluated and calculated based on the partition drive control results to obtain color fidelity data, where 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; Perform weighted fusion calculation on edge sharpness score, motion trajectory clarity data, brightness transition smoothness score, color fidelity data and dynamic contrast score to obtain a comprehensive quality prediction value; The global display effect level is divided based on the comprehensive quality prediction value to obtain display effect evaluation data.

10. A display optimization system for a liquid crystal display screen, characterized in that: Used to execute the display optimization method for a liquid crystal display screen according to claim 1, the display optimization system for a liquid crystal display screen comprises: The frame difference detection module is used to obtain the current image frame data and the previous image frame data, calculate the inter-frame difference based on the preset pixel difference threshold, and perform threshold judgment based on the inter-frame difference data to obtain the motion area data; A grayscale change calculation module is used to calculate the grayscale change rate according to the motion area data; threshold interception is performed on the grayscale change rate data to obtain the response optimization target area data and non-target area data; A target area merging module is used to perform continuity evaluation on the response optimization target area data and perform merging processing based on the continuity evaluation results to obtain a continuous rectangular target area group; The temperature adaptive calculation module is used to obtain current temperature data; calculate the grayscale value difference of the continuous rectangular target area group according to the current temperature data to obtain a temporary overdrive voltage value; A partition modulation driving module is used to perform pulse width modulation on the temporary over-driving voltage value, wherein high-frequency pulse width modulation is performed on the response optimization target area data to generate an optimized driving signal, and standard pulse width modulation is performed on the non-target area data to generate a standard driving signal; The clarity evaluation module is used to perform partition compensation drive control on the liquid crystal display screen based on the optimized drive signal and the standard drive signal, and to perform dynamic clarity evaluation on the partition drive control result to obtain display effect evaluation data.

Images