An automatic overdrive debugging method for panels based on luminance sampling data

Abstract

This invention discloses an automatic overdrive adjustment method for panels based on brightness sampling data. It automatically measures and evaluates brightness waveforms with and without OD compensation, and searches for optimal compensation values ​​based on the evaluation results until all different voltage combinations achieve satisfactory compensation results. The method pre-configures a looping test scene in the driver chip's registers, consisting of several low-brightness frames and several high-brightness frames. After measurement, the entire measurement data is first smoothed, and a continuous combination of low-voltage and high-brightness frames is separated from the processed results. Then, the original data is analyzed to determine if an accurate result can be obtained. If so, the accurate result is calculated; otherwise, it is determined whether the current state is over-compensated or under-compensated. The above steps are performed sequentially for each voltage combination until a satisfactory OD compensation value is obtained for all combinations.

Description

Technical Field

[0001] This invention belongs to the field of image processing and relates to an automatic adjustment method for panel overdrive based on brightness sampling data. Background Technology

[0002] In traditional LCD displays, liquid crystal molecules require time to respond to electrical signals and change their alignment, resulting in slow response times and motion blur. Overdrive (OD) uses additional voltage pulses to accelerate the switching of liquid crystal molecules. When a rapid pixel switching is needed, the OD circuit applies a voltage pulse, forcing the liquid crystal molecules to respond more quickly. Generally, because OLED displays have extremely fast response times, typically in the millisecond or even microsecond range, they do not require OD to further improve response time. However, in cases where voltage switching is significant, the first two frames may still exhibit motion blur due to insufficient brightness and a large difference between subsequent frames.

[0003] To address these issues, measurements need to be taken of the OLED display during voltage switching to determine the brightness difference between the first two frames and subsequent frames. Odescent compensation (OD) needs to be added based on this, followed by remeasurement and evaluation of the compensation effect. The OD compensation intensity is then adjusted based on the evaluation until a suitable value is found. Because different combinations of high and low voltages require different OD compensation configurations, this is a complex and multifaceted process, typically requiring significant manpower and time, and the results are unpredictable.

[0004] Based on the above-mentioned technical problems, this invention proposes an automated method for measuring and analyzing waveforms after OD compensation, which can quickly complete this tedious process, and the compensation results are more stable and accurate than those of traditional methods. Summary of the Invention

[0005] This invention provides an automatic overdrive debugging method for panels based on brightness sampling data, comprising the following steps:

[0006] Step 1: Configure the test scenario and set the number of low-voltage frames and high-voltage frames;

[0007] Step 2: Input the low voltage value, high voltage value, and OD compensation value, and measure the test scenario;

[0008] Step 3: Smooth the measurement results;

[0009] Step 4: Analyze the smoothing results to obtain the interval;

[0010] Step 5: Fuzzy analysis of the original data within the interval;

[0011] Step 6: Attempt precise analysis. If successful, obtain the RT value directly; if unsuccessful, calibrate the fuzzy analysis results to obtain the RT value.

[0012] Step 7: Use binary search to find possible OD compensation values. If they exist, update the OD compensation values ​​and return to Step 2; otherwise, proceed to the next step.

[0013] Step 8: Record the optimal OD compensation value under the current voltage combination based on the RT value;

[0014] Step 9: Determine if there are any unmeasured voltage combinations. If so, update the voltage combination and return to Step 2; otherwise, end the measurement.

[0015] In step one, based on the evaluation of effect and time, a real test scene is formed by alternating between 6 low-brightness frames and 11 high-brightness frames. In each test scene, only a single-color sub-pixel is lit, that is, only one of the R, G, and B sub-pixels is lit at a time.

[0016] In step two, the OD compensation value is applied to the voltage and only takes effect in the first two frames when the brightness changes from dark to bright due to a large voltage change. The measurement instrument is used to collect the brightness information of the test scene at the highest frequency. If the combination of high and low voltage parameters is the first measurement, the OD compensation value is reset to the initial value of 0.

[0017] In step three, mean filtering or Gaussian filtering is used to process the one-dimensional brightness information.

[0018] In step four, after obtaining the filtering results, the brightness values ​​of the filtered results are sorted from smallest to largest. The values ​​at the 5% and 95% positions are taken as the brightness references for low-brightness frames and high-brightness frames, respectively, resulting in a total of N brightness values. These N values ​​are then sorted to obtain an ascending sequence {brightness 1, brightness 2, brightness 3…brightness N}, which is then used to calculate the brightness value using the formula… After calculating the reference numbers for low-brightness and high-brightness frames, the brightness... With brightness The value is the reference brightness value between low-brightness frames and high-brightness frames; through and The linear interpolation of the value is used as the threshold T1 to distinguish the brightness of high and low brightness frames. Iterate through all the filtered brightness values ​​and determine whether two consecutive values ​​are on either side of a threshold T: If the preceding value is less than the threshold T and the following value is greater than the threshold T, it means that the line connecting the two consecutive values ​​intersects the horizontal line where the threshold T is located, and this intersection point is the left starting position of a peak; If the preceding value is greater than the threshold T and the following value is less than the threshold T, it also means that the line connecting the two values ​​intersects the horizontal line where the threshold is located, but this intersection point is the right ending position of a peak; If both consecutive values ​​are greater than or less than the threshold T, it means that the value is on or outside the peak; This method is used to determine the start and end positions of each peak, and the end of adjacent peaks. 前 Peak start, peak end 后 The three sequence numbers represent a transition from a low-brightness frame to a high-brightness frame, i.e., the interval [end of peak]. 前 End of peak 后 [ ] represents a range in which a low-brightness frame sequence transitions to a high-brightness frame sequence.

[0019] In step five, the interval is divided into 17 equal parts. The first 6 parts are designated as low-brightness frame blur intervals, and the last 11 parts are designated as high-brightness frame blur intervals. The maximum value in each interval is taken as the brightness reference for each frame, denoted as the sequence {low 1, low 2…low 6} and the sequence {high 1, high 2…high 6}. 11}; Remove the first and last frames from the low-brightness frame sequence, and calculate the average value of {low 2, low 3, low 4, low 5} as the brightness reference for the low-brightness frames, denoted as Y. 低 Remove the first and last 4 frames from the high-brightness frames, and take {high 3, high 4...high 9} to calculate the average value as the brightness reference for the high-brightness frames, denoted as Y. 高 Similarly, linear interpolation is used to calculate the threshold T2 that distinguishes between high and low brightness frames: Iterate through the original data within the interval, determining whether two values ​​are on opposite sides of T2. Before recording, find the first peak start point. Record the peak start and peak end points in matching pairs: {(peak start 1, peak end 1), (peak start 2, peak end 2) ... (peak start 1) ... (peak end 2) ... n End of peak n )} .

[0020] In step six, the width of each pair of paired peaks is first calculated by subtracting the start of the peak from the end of the peak, resulting in the sequence {peak width 1, peak width 2, ... peak width 3}. n First, we determine whether the width of each waveform remains consistent to evaluate whether these waveforms are regular. If the waveforms are regular, accurate solutions are supported; otherwise, they are not. We use the standard deviation and mean of the peak widths to determine the regularity of the waveforms. If the value obtained by dividing the standard deviation by one-quarter of the mean is less than 1, the waveform is considered regular; otherwise, it is considered irregular. The evaluation function is: When f (peak width) < 1, it is considered a regularity and requires precise processing. The maximum value of each peak interval is calculated separately as the brightness value of the current peak. Additionally, the number of peaks needs to be counted, because a frame may contain more than one peak in some cases. The number of peaks in a frame is estimated by dividing the number of peaks by the number of high-brightness frames. After obtaining the number of peaks C in each frame, the maximum value among the first C peaks is taken as the brightness of the first high-brightness frame, denoted as V. 1st Subsequent peaks are also counted every C peaks, and the average of these subsequent maximum values ​​is calculated and denoted as V. stable Using Y from the fuzzy analysis results in step five 低 As an estimate of low-brightness frames, it is denoted as V. start The final evaluation result of the OD compensation effect is denoted as RT. When RT is less than 1, the current OD compensation effect is considered to be under-compensated. When RT is greater than 1, the current OD compensation effect is considered to be over-compensated. After completing the accurate processing, proceed directly to step seven.

[0021] In step six, the blurring result is calibrated, and the calibrated blurring result is used as the criterion for judging under-compensation or over-compensation. The main task of calibration is to determine the boundary between low-brightness frames and high-brightness frames. Specifically, the original blurring process is divided into intervals based on the number of frames. A total of 17 frames are used, including 6 low-brightness frames and 11 high-brightness frames as the test scene. The 6th and 7th intervals of the 17 intervals divided during blurring are taken and arranged in order to obtain the sequence {a1, a2…a... ... n}; Divide the sequence into n-1 combinations. Each combination sequentially divides the sequence into two groups, from combination {a1}{a2, a3…a… n}, to the combination {a1, a2…a n-1}{a n For each combination, calculate the standard deviation of the two groups, denoted as std1 and std2. When the sum of std1 and std2 for a combination is minimized, the boundary between the left and right groups of that combination is considered the accurate boundary between low-brightness frames and high-brightness frames. Take the brightness data of one interval length to the right of this boundary, and take the maximum value as the brightness of the first high-brightness frame, denoted as V. 1st Using Y from the fuzzy analysis results in step five 低 As an estimate of low-brightness frames, it is denoted as V. start Using Y from the fuzzy analysis results in step five 高 The estimate of the high-brightness frame is denoted as V. stable The final evaluation result of the OD compensation effect is denoted as RT. When RT is less than 1, the current OD compensation effect is considered to be under-compensated. When RT is greater than 1, the current OD compensation effect is considered to be over-compensated. After completing the fuzzing calibration, proceed to step seven. Attached Figure Description

[0022] Figure 1 The diagram shown is a flowchart of the present invention;

[0023] Figure 2 The figure shown is a brightness line graph obtained from an embodiment of the present invention;

[0024] Figure 3 The image shown is a smoothed line graph from an embodiment of the present invention.

[0025] Figure 4 The figure shows the threshold and peak range of an embodiment of the present invention;

[0026] Figure 5 The image shown is a high-brightness frame precisely measured according to an embodiment of the present invention. Detailed Implementation

[0027] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0028] Please see Figures 1-5 This invention provides an automatic overdrive debugging method for panels based on brightness sampling data, comprising the following steps:

[0029] Step 1: Configure the test scenario and set the number of low-voltage frames and high-voltage frames;

[0030] Step 2: Input the low voltage value, high voltage value, and OD compensation value, and measure the test scenario;

[0031] Step 3: Smooth the measurement results;

[0032] Step 4: Analyze the smoothing results to obtain the interval;

[0033] Step 5: Fuzzy analysis of the original data within the interval;

[0034] Step 6: Attempt precise analysis. If successful, obtain the RT value directly; if unsuccessful, calibrate the fuzzy analysis results to obtain the RT value.

[0035] Step 7: Use binary search to find possible OD compensation values. If they exist, update the OD compensation values ​​and return to Step 2; otherwise, proceed to the next step.

[0036] Step 8: Record the optimal OD compensation value under the current voltage combination based on the RT value;

[0037] Step 9: Determine if there are any unmeasured voltage combinations. If so, update the voltage combination and return to Step 2; otherwise, end the measurement.

[0038] In step one, based on the evaluation of effect and time, a real test scene is formed by alternating between 6 low-brightness frames and 11 high-brightness frames. In each test scene, only a single-color sub-pixel is lit, that is, only one of the R, G, and B sub-pixels is lit at a time.

[0039] In step two, input the voltage parameters for the low-brightness frame, the voltage parameters for the high-brightness frame, and the OD compensation value. This compensation value applies to the voltage and only takes effect in the first two frames when a significant voltage change causes the brightness to increase from dark to bright. Use a measuring instrument to collect brightness information of the test scene at the highest frequency. If the combination of high and low voltage parameters is the first measurement, the OD compensation value is reset to the initial value of 0. Depending on the specifications of the measuring instrument and the acquisition time, several brightness values ​​will be obtained. Based on the actual measurement, a brightness line graph obtained by connecting the first 2000 brightness values ​​is shown below. Figure 2 As shown.

[0040] In step three, the brightness data is smoothed. Mean filtering or Gaussian filtering can be used to process the one-dimensional brightness information, such as... Figure 3 As shown, mean filtering is used directly to process the image, replacing the mean of the surrounding K values, including the image itself, with the brightness value described above. The calculation result is shown in the figure. This is done to separate a group of high and low frame sequences.

[0041] In step four, after obtaining the filtering results, the brightness values ​​of the filtered results are sorted from smallest to largest. The values ​​at the 5% and 95% positions are taken as the brightness references for low-brightness frames and high-brightness frames, respectively, resulting in a total of N brightness values. These N values ​​are then sorted to obtain an ascending sequence {brightness 1, brightness 2, brightness 3…brightness N}, which is then used to calculate the brightness value using the formula… After calculating the reference numbers for low-brightness and high-brightness frames, the brightness... With brightness The value is the reference brightness value between low-brightness frames and high-brightness frames; through and The linear interpolation of the value is used as the threshold T1 to distinguish the brightness of high and low brightness frames. Iterate through all the filtered brightness values ​​and determine whether two consecutive values ​​are on either side of a threshold T: If the preceding value is less than the threshold T and the following value is greater than the threshold T, it means that the line connecting the two consecutive values ​​intersects the horizontal line where the threshold T is located, and this intersection point is the left starting position of a peak; If the preceding value is greater than the threshold T and the following value is less than the threshold T, it also means that the line connecting the two values ​​intersects the horizontal line where the threshold is located, but this intersection point is the right ending position of a peak; If both consecutive values ​​are greater than or less than the threshold T, it means that the value is on or outside the peak. What is needed now is to obtain the start and end positions of each peak to determine the start and end positions of each peak, and the end of adjacent peaks. 前 Peak start, peak end 后 The three sequence numbers represent a transition from a low-brightness frame to a high-brightness frame, i.e., the interval [end of peak]. 前 End of peak 后 [ ] represents a range where a low-brightness frame sequence transitions to a high-brightness frame sequence, such as Figure 4 As shown.

[0042] After determining the intervals where a continuous low-brightness frame sequence transitions to a high-brightness frame sequence from the above steps, the raw data of these intervals is analyzed and processed. First, blurring is performed to obtain an approximate result, and the interval is divided into several equal sub-intervals. Since the embodiment uses 6 low-voltage frames and 11 high-voltage frames, the interval is divided into 17 equal parts. The first 6 parts are designated as the low-brightness frame blurring intervals, and the last 11 parts as the high-brightness frame blurring intervals. The maximum value in each sub-interval is taken as the brightness reference for each frame, denoted as the sequence {low 1, low 2…low 6} and the sequence {high 1, high 2…high 6}. 11}; Remove the first and last frames from the low-brightness frame sequence, and calculate the average value of {low 2, low 3, low 4, low 5} as the brightness reference for the low-brightness frames, denoted as Y. 低 Remove the first and last 4 frames from the high-brightness frames, and take {high 3, high 4...high 9} to calculate the average value as the brightness reference for the high-brightness frames, denoted as Y. 高 Similarly, linear interpolation is used to calculate the threshold T2 that distinguishes between high and low brightness frames: Iterate through the original data within the interval, determining whether two values ​​are on opposite sides of T2. Before recording, find the first peak start point. Record the peak start and peak end points in matching pairs: {(peak start 1, peak end 1), (peak start 2, peak end 2) ... (peak start 1) ... (peak end 2) ... n End of peak n )} .

[0043] After obtaining the sequence of peak and trough pairs, we attempt to perform precise processing. First, we calculate the width of each pair of peaks by subtracting the peak start from the peak end, resulting in the sequence {peak width 1, peak width 2, ... peak width 3}.n First, we determine whether the width of each waveform remains consistent to evaluate whether these waveforms are regular. If the waveforms are regular, accurate solutions are supported; otherwise, they are not. We use the standard deviation and mean of the peak widths to determine the regularity of the waveforms. If the value obtained by dividing the standard deviation by one-quarter of the mean is less than 1, the waveform is considered regular; otherwise, it is considered irregular. The evaluation function is: When f (peak width) < 1, it is considered a regularity and requires precise processing. The maximum value of each peak interval is calculated separately as the brightness value of the current peak. Additionally, the number of peaks needs to be counted, because a frame may contain more than one peak in some cases. The number of peaks in a frame is estimated by dividing the number of peaks by the number of high-brightness frames. After obtaining the number of peaks C in each frame, the maximum value among the first C peaks is taken as the brightness of the first high-brightness frame, denoted as V. 1st Subsequent peaks are also counted every C peaks, and the average of these subsequent maximum values ​​is calculated and denoted as V. stable Using Y from the fuzzy analysis results in step five 低 As an estimate of low-brightness frames, it is denoted as V. start The final evaluation result of the OD compensation effect is denoted as RT. When RT is less than 1, the current OD compensation effect is considered to be under-compensated. When RT is greater than 1, the current OD compensation effect is considered to be over-compensated. After completing the accurate processing, proceed directly to step seven.

[0044] In step six, if the precise processing fails, it is considered that the current waveform is irregular and the compensation effect cannot be accurately estimated. Only an approximate RT value can be obtained by calibrating the blurring result. The calibrated blurring result is used as the criterion for judging under-compensation or over-compensation. The main task of calibration is to determine the boundary between low-brightness frames and high-brightness frames. Specifically, the original blurring process is divided into intervals based on the number of frames. In this example, a total of 17 frames are used: 6 low-brightness frames and 11 high-brightness frames as the test scene. The 6th and 7th intervals from the 17 intervals divided during blurring are taken and arranged sequentially to obtain the sequence {a1, a2…a ... n}; Divide the sequence into n-1 combinations. Each combination sequentially divides the sequence into two groups, from combination {a1}{a2, a3…a… n}, to the combination {a1, a2…a n-1}{a nFor each combination, calculate the standard deviation of the two groups, denoted as std1 and std2. When the sum of std1 and std2 for a combination is minimized, the boundary between the left and right groups of that combination is considered the accurate boundary between low-brightness frames and high-brightness frames. Take the brightness data of one interval length to the right of this boundary, and take the maximum value as the brightness of the first high-brightness frame, denoted as V. 1st Using Y from the fuzzy analysis results in step five 低 As an estimate of low-brightness frames, it is denoted as V. start Using Y from the fuzzy analysis results in step five 高 The estimate of the high-brightness frame is denoted as V. stable The final evaluation result of the OD compensation effect is denoted as RT. When RT is less than 1, the current OD compensation effect is considered to be under-compensated. When RT is greater than 1, the current OD compensation effect is considered to be over-compensated. After completing the fuzzing calibration, proceed to step seven.

[0045] After obtaining the precise result or the calibrated fuzzy result, a binary search is performed within the compensation value range based on the relationship between the RT value and 1 from the evaluation function result. If it is still possible to find a better OD compensation value, the search continues, a new OD compensation value is updated, and the process returns to step two. If there are no better OD compensation value candidates, the process proceeds to the next step.

[0046] If there are still unmeasured voltage combinations, switch to the next voltage group and return to step two to perform the measurement.

[0047] The measurement ends once all voltage combinations have been measured.

[0048] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is limited by the appended claims and their equivalents.

Claims

1. A panel overdrive automatic debugging method based on brightness sampling data, characterized in that: Includes the following steps: Step 1: Configure the test scenario and set the number of low-voltage frames and high-voltage frames; Step 2: Input the low voltage value, high voltage value, and OD compensation value, and measure the test scenario; Step 3: Smooth the measurement results; Step 4: Analyze the smoothing results to obtain the interval; Step 5: Fuzzy analysis of the original data within the interval; Step 6: Attempt precise analysis. If successful, directly obtain the RT value. If it fails, the fuzzy analysis results are calibrated to obtain the RT value; Step 7: Use binary search to find possible OD compensation values. If they exist, update the OD compensation values ​​and return to step 2. If it does not exist, proceed to the next step; Step 8: Record the optimal OD compensation value under the current voltage combination based on the RT value; Step 9: Determine if there are any unmeasured voltage combinations. If so, update the voltage combinations and return to Step 2. If not, then end the measurement; In step four, after obtaining the filtering results, the brightness values ​​of the filtered results are sorted from smallest to largest. The values ​​at the 5% and 95% positions are taken as the brightness references for low-brightness frames and high-brightness frames, respectively, resulting in a total of N brightness values. These N values ​​are then sorted to obtain an ascending sequence {brightness 1, brightness 2, brightness 3…brightness N}, which is then used to calculate the brightness value using the formula… After calculating the reference numbers for low-brightness and high-brightness frames, the brightness... With brightness The value is the reference brightness value between low-brightness frames and high-brightness frames; through and The linear interpolation of the value is used as the threshold T1 to distinguish the brightness of high and low brightness frames. Iterate through all the filtered brightness values ​​and determine whether two consecutive values ​​are on either side of a threshold T: If the preceding value is less than the threshold T and the following value is greater than the threshold T, it means that the line connecting the two consecutive values ​​intersects the horizontal line where the threshold T is located, and this intersection point is the left starting position of a peak; If the preceding value is greater than the threshold T and the following value is less than the threshold T, it also means that the line connecting the two values ​​intersects the horizontal line where the threshold is located, but this intersection point is the right ending position of a peak; If both consecutive values ​​are greater than or less than the threshold T, it means that the value is on or outside the peak; This method is used to determine the start and end positions of each peak, and the end of adjacent peaks. 前 Peak start, peak end 后 The three sequence numbers represent a transition from a low-brightness frame to a high-brightness frame, i.e., the interval [end of peak]. 前 End of peak 后 [This refers to a range where a low-brightness frame sequence transitions into a high-brightness frame sequence;] In step five, the interval is divided into 17 equal parts. The first 6 parts are designated as low-brightness frame blur intervals, and the last 11 parts are designated as high-brightness frame blur intervals. The maximum value in each interval is taken as the brightness reference for each frame, denoted as the sequence {low 1, low 2…low 6} and the sequence {high 1, high 2…high 6}. 11 }; Remove the first and last frames from the low-brightness frame sequence, and calculate the average value of {low 2, low 3, low 4, low 5} as the brightness reference for the low-brightness frames, denoted as Y. 低 Remove the first and last 4 frames from the high-brightness frames, and take {high 3, high 4...high 9} to calculate the average value as the brightness reference for the high-brightness frames, denoted as Y. 高 Similarly, linear interpolation is used to calculate the threshold T2 that distinguishes between high and low brightness frames: Iterate through the original data within the interval, determining whether two values ​​are on opposite sides of T2. Before recording, find the first peak start point. Record the peak start and peak end points in matching pairs: {(peak start 1, peak end 1), (peak start 2, peak end 2) ... (peak start 1) ... (peak end 2) ... n End of peak n )} .

2. The automatic overdrive debugging method for a panel based on luminance sampling data according to claim 1, characterized in that: In step one, based on the evaluation of effect and time, a real test scene is formed by alternating between 6 low-brightness frames and 11 high-brightness frames. In each test scene, only a single-color sub-pixel is lit, that is, only one of the R, G, and B sub-pixels is lit at a time.

3. The automatic overdrive debugging method for a panel based on luminance sampling data according to claim 1, characterized in that: In step two, the OD compensation value is applied to the voltage and only takes effect in the first two frames when the brightness changes from dark to bright due to a large voltage change. The measurement instrument is used to collect the brightness information of the test scene at the highest frequency. If the combination of high and low voltage parameters is the first measurement, the OD compensation value is reset to the initial value of 0.

4. The automatic overdrive debugging method for a panel based on luminance sampling data according to claim 1, characterized in that: In step three, mean filtering or Gaussian filtering is used to process the one-dimensional brightness information.

5. The automatic overdrive debugging method for a panel based on luminance sampling data according to claim 1, characterized in that: In step six, the width of each pair of paired peaks is first calculated by subtracting the start of the peak from the end of the peak, resulting in the sequence {peak width 1, peak width 2, ... peak width 3}. n First, we determine whether the width of each waveform remains consistent to evaluate whether these waveforms are regular. If the waveforms are regular, accurate solutions are supported; otherwise, they are not. We use the standard deviation and mean of the peak widths to determine the regularity of the waveforms. If the value obtained by dividing the standard deviation by one-quarter of the mean is less than 1, the waveform is considered regular; otherwise, it is considered irregular. The evaluation function is: When f (peak width) < 1, it is considered a regularity and requires precise processing. The maximum value of each peak interval is calculated separately as the brightness value of the current peak. Additionally, the number of peaks needs to be counted, because a frame may contain more than one peak in some cases. The number of peaks in a frame is estimated by dividing the number of peaks by the number of high-brightness frames. After obtaining the number of peaks C in each frame, the maximum value among the first C peaks is taken as the brightness of the first high-brightness frame, denoted as V. 1st Subsequent peaks are also counted every C peaks, and the average of these subsequent maximum values ​​is calculated and denoted as V. stable Using Y from the fuzzy analysis results in step five 低 As an estimate of low-brightness frames, it is denoted as V. start The final evaluation result of the OD compensation effect is denoted as RT. When RT is less than 1, the current OD compensation effect is considered to be under-compensated. When RT is greater than 1, the current OD compensation effect is considered to be over-compensated. After completing the accurate processing, proceed directly to step seven.

6. The automatic overdrive debugging method for a panel based on luminance sampling data according to claim 5, characterized in that: In step six, the blurring result is calibrated, and the calibrated blurring result is used as the criterion for judging under-compensation or over-compensation. The main task of calibration is to determine the boundary between low-brightness frames and high-brightness frames. Specifically, the original blurring process is divided into intervals based on the number of frames. A total of 17 frames are used, including 6 low-brightness frames and 11 high-brightness frames as the test scene. The 6th and 7th intervals of the 17 intervals divided during blurring are taken and arranged in order to obtain the sequence {a1, a2…a... ... n }; Divide the sequence into n-1 combinations. Each combination sequentially divides the sequence into two groups, from combination {a1}{a2, a3…a… n }, to the combination {a1, a2…a n-1 }{a n For each combination, calculate the standard deviation of the two groups, denoted as std1 and std2. When the sum of std1 and std2 for a combination is minimized, the boundary between the left and right groups of that combination is considered the accurate boundary between low-brightness frames and high-brightness frames. Take the brightness data of one interval length to the right of this boundary, and take the maximum value as the brightness of the first high-brightness frame, denoted as V. 1st Using Y from the fuzzy analysis results in step five 低 As an estimate of low-brightness frames, it is denoted as V. start Using Y from the fuzzy analysis results in step five 高 The estimate of the high-brightness frame is denoted as V. stable The final evaluation result of the OD compensation effect is denoted as RT. When RT is less than 1, the current OD compensation effect is considered to be under-compensated. When RT is greater than 1, the current OD compensation effect is considered to be over-compensated. After completing the fuzzing calibration, proceed to step seven.

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