A method and system for reducing luminance non-uniformity of a screen at different OPRs

Abstract

The application discloses a method and system for reducing luminance unevenness of a screen under different OPR, and the basic image data of a frame image is counted according to the data of an input picture, and the data is sent to an image format judgment module; the image format is judged to be a gray scale image or a monochrome image or a double-channel image or a mixed color image according to an image format judgment strategy and the basic image data of the frame image; the mapping table LUT of the pixel gray scale value of the image is obtained by acquiring image test data; when the image is a gray scale image or a monochrome image, or the image is a mixed color image, the G channel is selected, and the corresponding pixel value compensation value of the image is calculated; the method for reducing luminance unevenness of the screen under different OPR guarantees that the luminance of the gray scale image, the monochrome image and the double-channel mixed color image under different OPR is the same as the luminance displayed under 100% OPR, and the luminance of the R, G and B three-color images is consistent with the luminance of the gray scale image under the same gray scale after being added together.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of image display technology, and in particular to a method and system for reducing luminance unevenness of a screen at different OPR. BACKGROUND

[0002] Comparison of picture patterns at different open pixel ratios, that is, the sizes of white regions displayed on each picture are different. The white region represents pixels being lit up by current, and because the open pixel ratios of each picture are different, the total current amount is different. Even if the middle regions of each picture receive the same white grayscale data, the luminance of the middle positions of each picture is still different. This luminance inconsistency phenomenon leads to a decrease in the visual effect of the image.

[0003] When measuring the luminance of an image displaying a pure color image, the sum of the luminance of R, G, and B color images is greater than the luminance of a grayscale image at the same grayscale. SUMMARY

[0004] The technical problem solved by the present application is to provide a method for reducing luminance unevenness of a screen at different OPR. The method ensures that the luminance of a grayscale image, a single color image, and a double-channel mixed color image at different OPR is the same as the luminance displayed at 100% OPR, and the sum of the luminance of R, G, and B color images is consistent with the luminance of a grayscale image at the same grayscale.

[0005] To solve the above technical problem, the present application provides a method for reducing luminance unevenness of a screen at different OPR, comprising the following steps:

[0006] An image data statistics module statistically obtains basic image data of a frame of image according to the data of an input picture, and sends the data to an image format judgment module;

[0007] The image format judgment module judges the image format to be a grayscale image or a single color image or a double-channel image or a mixed color image according to an image format judgment strategy and the basic image data of a frame of image;

[0008] An image test statistics calculation module obtains image test data to obtain a mapping table LUT of image pixel grayscale values;

[0009] When the image is a gray scale image or a single color image, or the image is a two-channel image, the G channel is selected, or the image is a mixed color image, the image pixel compensation calculation module calculates the image corresponding pixel value compensation value: according to the value range obtained from the relationship between the frame minimum value and the frame average value of the image, the first correction value XZ1 is selected from the mapping table LUT, according to the value range of the relationship between the frame maximum value and the frame average value of the image, the second correction value XZ2 is selected from the mapping table LUT, and according to the value range of the frame maximum value of the image, the image two-side brightness compensation coefficient K is selected from the mapping table LUT; according to the first correction value XZ1, the second correction value XZ2, the compensation value C of the frame average value, and the image compensation strategy under the condition that the pixel value is compared with the frame average value, the image corresponding pixel value compensation value is obtained.

[0010] When the image is a mixed color image or a two-channel image, the pixel value of the other channel after compensation is mapped according to the original pixel ratio of the selected channel to the other channel.

[0011] Preferably, the step of "counting the basic image data of a frame of image" specifically includes counting the frame average values avgr, avgg, and avgb of the R, G, and B channels respectively, the frame maximum values maxr, maxg, and maxb of the R, G, and B channels respectively, and the frame minimum values minr, ming, and minb of the R, G, and B channels respectively.

[0012] Preferably, the image format judgment strategy is: when the frame maximum values maxr, maxg, and maxb of the R, G, and B channels are all greater than zero, and the difference between the maximum value maxavg of the frame average values of the R, G, and B channels and the minimum value minavg of the frame average values of the three channels is less than or equal to 8, it is determined that the image is a gray scale image; when the frame maximum values maxr, maxg, and maxb of the three channels are all greater than zero, and the difference between the maximum value maxavg of the frame average values of the R, G, and B channels and the minimum value minavg of the frame average values of the three channels is greater than 8, it is determined that the image is a gray scale image; when the frame maximum values of the R, G, and B channels only one is greater than 0, and the difference between the frame maximum value and the frame minimum value of any channel of the R, G, and B channels is greater than 5, it is determined that the image is a single color image; when the frame maximum value of any channel of the R, G, and B channels is only one less than zero, and the difference between the frame maximum value and the frame minimum value of any channel of the other two channels is greater than 5, it is determined that the image is a two-channel image.

[0013] Preferably, the image compensation strategy under the condition that the pixel value is compared with the frame average value is:

[0014] The image pixel value Pix is compared with the average value avg of a row of pixel values:

[0015] When the image pixel value Pix is greater than or equal to the frame average value avg, the pixel value of the image after compensation is:

[0016] Pend = Pix + C * XZ1 + (P - avgl) / 255 * K

[0017] When the image pixel value is less than the frame average avg, the compensated pixel value of the image is:

[0018] Pend = Pix + C * XZ2 + (P - avgl) / 255 * K.

[0019] Preferably, the step "the image compensation calculation module obtains a mapping table LUT of image pixel gray value" is specifically: selecting an image with an intermediate window as a test picture, adjusting the picture with different OPRs of the frame average of the intermediate window pixel value being 16, 32,..., 256, setting LUT for the intermediate window gray scale pixel value being 16, 32,..., 256, marking the pixel value corresponding to the initial window pixel value, adjusting the size of the intermediate pixel value, ensuring that the marked gray scale brightness and the brightness when it is full screen are obtained by using interpolation to obtain the gray scale pixel value under the corresponding frame average, and gradually counting the respective LUT compensation values of the R, G and B channels of the image.

[0020] Preferably, when the image is a gray scale image, the "image pixel compensation calculation module calculates the pixel value compensation value corresponding to the image" is specifically: selecting the value of the first correction value XZ1 according to the range of the value obtained from the relationship min / avg;

[0021] selecting the value of the second correction value XZ2 according to the range of the value obtained from the relationship (256-max+avg) / 256;

[0022] selecting the image two-side brightness compensation coefficient K according to the value range of the frame maximum value of the image;

[0023] According to the processing of the image pixel value, the average avgl of a row of pixel values is counted;

[0024] According to the image frame average avg and the pixel value, the compensation value C is obtained by interpolation;

[0025] Comparing the image pixel value Pix with the average avg of a row of pixel values:

[0026] When the image pixel value Pix is greater than or equal to the frame average avg, the compensated pixel value of the image is:

[0027] Pend = Pix + C * XZ1 + (P - avgl) / 255 * K

[0028] When the image pixel value is less than the frame average avg, the compensated pixel value of the image is:

[0029] Pend = Pix + C * XZ2 + (P - avgl) / 255 * K.

[0030] Preferably, when the image is a monochrome image, the "image pixel compensation calculation module calculates the image corresponding pixel value compensation value" is specifically: according to the relationship min / avg the value of the range in the mapping table LUT selects the first correction value XZ1 value;

[0031] According to the relationship (256-max+avg) / 256 the value of the range in the mapping table LUT selects the second correction value XZ2 value;

[0032] According to the value range of the frame maximum value of the image in the mapping table LUT selects the image two side brightness compensation coefficient K;

[0033] According to the processing image pixel value in a line statistics a row of pixel value average avgl;

[0034] According to the image frame average avg and pixel value interpolation to get compensation value C;

[0035] The image pixel value Pix and a row of pixel value average avg comparison:

[0036] When the image pixel value Pix is greater than or equal to the frame average avg, the image after compensation pixel value is:

[0037] Pend = Pix + C * XZ1 + (P - avgl) / 255 * K

[0038] When the image pixel value is less than the frame average avg, the image after compensation pixel value is:

[0039] Pend = Pix + C * XZ2 + (P - avgl) / 255 * K.

[0040] Preferably, when the image is a mixed color image, the "image pixel compensation calculation module calculates the image corresponding pixel value compensation value" is specifically: first process R, G, B three channel G channel image pixel data:

[0041] According to the relationship min / avg the value of the range in the mapping table LUT selects the first correction value XZ1 value;

[0042] According to the relationship (256-max+avg) / 256 the value of the range in the mapping table LUT selects the second correction value XZ2 value;

[0043] According to the value range of the frame maximum value of the image in the mapping table LUT selects the image two side brightness compensation coefficient K;

[0044] Calculate the average value (avgl) of a row of pixel values ​​based on the row containing the pixel values ​​of the processed image.

[0045] The compensation value C is obtained by interpolating the image frame mean (avg) and pixel values.

[0046] Compare the image pixel value Pix with the average value avg of a row of pixel values:

[0047] When the image pixel value Pix is ​​greater than or equal to the frame mean value avg, the compensated pixel value of the image is:

[0048] Pend=Pix+C*XZ1+(P-avgl) / 255*K

[0049] When the image pixel value is less than the frame average (avg), the compensated pixel value is:

[0050] Pend=Pix+C*XZ2+(P-avgl) / 255*K;

[0051] Then, the pixel values ​​of the other two channels are mapped based on the original pixel ratios of the R, G, and B channels.

[0052] Preferably, when the image is a dual-channel image, the "image pixel compensation calculation module calculates the corresponding pixel value compensation value" specifically means: if the image is a GB channel image or a GR channel image, then the pixel data of the G channel image in the dual-channel image is processed first:

[0053] Based on the range of values ​​obtained from the relation min / avg, the value of the first correction value XZ1 is selected in the mapping table LUT;

[0054] Based on the range of values ​​obtained from the relation (256-max+avg) / 256, the value of the second correction value XZ2 is selected in the mapping table LUT;

[0055] The brightness compensation coefficient K on both sides of the image is selected in the mapping table LUT based on the range of the maximum value of the image frame.

[0056] Calculate the average value (avgl) of a row of pixel values ​​based on the row containing the pixel values ​​of the processed image.

[0057] The compensation value C is obtained by interpolating the image frame mean (avg) and pixel values.

[0058] Compare the image pixel value Pix with the average value avg of a row of pixel values:

[0059] When the image pixel value Pix is ​​greater than or equal to the frame mean value avg, the compensated pixel value of the image is:

[0060] Pend=Pix+C*XZ1+(P-avgl) / 255*K

[0061] When the image pixel value is less than the frame average (avg), the compensated pixel value is:

[0062] Pend=Pix+C*XZ2+(P-avgl) / 255*K;

[0063] Then, the image value of the other channel is mapped based on the original pixel ratio of the two channels.

[0064] To solve the above-mentioned technical problems, the present invention also discloses an image processing system that adopts the above-mentioned method for reducing brightness unevenness under different OPR of the screen. The image processing system includes: an image data statistics module, an image format judgment module, and an image pixel compensation calculation module.

[0065] The image data statistics module calculates the basic image data of a frame based on the input image data and sends the data to the image format judgment module.

[0066] The image format determination module determines the image format as grayscale image, monochrome image, dual-channel image, or mixed color image based on the image format determination strategy and the basic image data of a frame.

[0067] The image test statistics calculation module obtains the image test data and generates a LUT (Layered Table) mapping table of image pixel grayscale values.

[0068] When the image is a grayscale image or a monochrome image, or when the image is a dual-channel image, the G channel is selected, or when the image is a mixed-color image, the image pixel compensation calculation module calculates the corresponding image value compensation value: based on the range of values ​​obtained from the relationship between the minimum frame value and the average frame value of the image, the first correction value XZ1 is selected in the mapping table LUT; based on the range of values ​​obtained from the relationship between the maximum frame value and the average frame value of the image, the second correction value XZ2 is selected in the mapping table LUT; based on the range of values ​​obtained from the maximum frame value of the image, the brightness compensation coefficient K on both sides of the image is selected in the mapping table LUT; based on the first correction value XZ1, the second correction value XZ2, the average value avgl, the compensation value C of the average frame value, and the image compensation strategy under the condition of comparing the pixel value with the average frame value, the corresponding image value compensation value is obtained.

[0069] After adopting the above method and system, the image data statistics module counts the basic image data of a frame based on the input image data and sends the data to the image format judgment module. The image format judgment module determines the image format as grayscale image, monochrome image, dual-channel image, or mixed color image based on the image format judgment strategy and the basic image data of a frame. The image test statistics calculation module obtains the image test data to get the image pixel grayscale value mapping table LUT. When the image is a grayscale image or monochrome image, or a dual-channel image, the G channel is selected, or the image is a mixed color image, the G channel is selected. The image pixel compensation calculation module calculates the corresponding pixel value compensation value: based on the relationship between the frame minimum value and the frame mean value of the image, the value of the first correction value XZ1 is selected from the mapping table LUT, and based on the frame maximum value of the image... The relationship between the value and the frame mean value is selected in the mapping table LUT, and the range of the second correction value XZ2 is selected in the mapping table LUT according to the range of the maximum value of the image frame. The brightness compensation coefficient K on both sides of the image is selected in the mapping table LUT according to the first correction value XZ1, the second correction value XZ2, the mean value avgl, the compensation value C of the frame mean value, and the image compensation strategy when comparing the pixel value with the frame mean value. When the image is a mixed color image or a dual-channel image, the image value of the other channel after compensation is mapped according to the ratio of the original pixels of the selected channel to the other channel. This method of reducing the brightness unevenness of the screen under different OPR ensures that the brightness of grayscale images, monochrome images, and dual-channel mixed color images under different OPR is the same as the brightness displayed under 100% OPR. The brightness of the R, G, B three-color images is added together and is consistent with the brightness of the grayscale image under the same grayscale. Attached Figure Description

[0070] Figure 1 This is a flowchart of the method for reducing brightness unevenness of a screen under different OPRs according to the present invention;

[0071] Figure 2 This is a system block diagram of an image processing system for reducing brightness unevenness under different OPR values ​​of a screen, according to the present invention. Detailed Implementation

[0072] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0073] Example 1

[0074] Please see Figure 1 and Figure 2 , Figure 1 This is a flowchart of the method for reducing brightness unevenness of a screen under different OPRs according to the present invention. Figure 2This is a system block diagram of an image processing system for reducing brightness unevenness under different OPRs of the screen according to the present invention;

[0075] This embodiment discloses a method for reducing brightness unevenness under different OPR (Optical Performance Level) conditions of a screen, including the following steps:

[0076] Image data statistics module 11 counts the basic image data of a frame of an image based on the data of the input image and sends the data to the image format judgment module;

[0077] Image format determination module 12 determines the image format as: grayscale image, monochrome image, dual-channel image, or mixed color image based on the image format determination strategy and the basic image data of a frame;

[0078] Image test statistics calculation module 13 obtains the image test data and obtains the image pixel grayscale value mapping table LUT;

[0079] When the image is a grayscale image or a monochrome image, or when the image is a dual-channel image, the G channel is selected, or when the image is a mixed-color image, the image pixel compensation calculation module 14 calculates the corresponding image value compensation value: based on the range of values ​​obtained from the relationship between the minimum frame value and the average frame value of the image, the first correction value XZ1 is selected in the mapping table LUT; based on the range of values ​​obtained from the relationship between the maximum frame value and the average frame value of the image, the second correction value XZ2 is selected in the mapping table LUT; based on the range of values ​​obtained from the maximum frame value of the image, the brightness compensation coefficient K on both sides of the image is selected in the mapping table LUT; based on the first correction value XZ1, the second correction value XZ2, the average value avgl, the compensation value C of the average frame value, and the image compensation strategy under the condition of comparing the pixel value with the average frame value, the corresponding image value compensation value is obtained.

[0080] When the image is a mixed color image or a dual-channel image, the image value of the other channel is mapped according to the ratio of the original pixels of the selected channel to the original pixels of the other channel.

[0081] Example 2

[0082] This embodiment is based on Embodiment 1. In this embodiment, the step of "statistically calculating the basic image data of a frame" specifically means: calculating the frame mean values ​​avgr, avgg, and avgb of the R, G, and B channels of the image, the frame maximum values ​​maxr, maxg, and maxb of the R, G, and B channels, and the frame minimum values ​​minr, minming, and minb of the R, G, and B channels.

[0083] Example 3

[0084] This embodiment is based on Embodiment 1. In this embodiment, the image format determination strategy is as follows: when the maximum frame values ​​maxr, maxg, and maxb of the R, G, and B channels are all greater than zero, and the difference between the maximum frame average value maxavg and the minimum frame average value minavg of the R, G, and B channels is less than or equal to 8, the image is determined to be a grayscale image; when the maximum frame values ​​maxr, maxg, and maxb of the three channels are all greater than zero, and the difference between the maximum frame average value maxavg and the minimum frame average value minavg of the R, G, and B channels is greater than 8, the image is determined to be a grayscale image; when only one of the maximum frame values ​​of the R, G, and B channels is greater than 0, and the difference between the maximum and minimum frame values ​​of any one of the R, G, and B channels is greater than 5, the image is determined to be a monochrome image; when only one of the maximum frame values ​​of any one of the R, G, and B channels is less than zero, and the difference between the maximum and minimum frame values ​​of any one of the other two channels is greater than 5, the image is determined to be a dual-channel image.

[0085] Example 4

[0086] This embodiment is based on Embodiment 3. In this embodiment, the image compensation strategy for comparing pixel values ​​with frame average values ​​is as follows:

[0087] Compare the image pixel value Pix with the average value avg of a row of pixel values:

[0088] When the image pixel value Pix is ​​greater than or equal to the frame mean value avg, the compensated pixel value of the image is:

[0089] Pend=Pix+C*XZ1+(P-avgl) / 255*K

[0090] When the image pixel value is less than the frame average (avg), the compensated pixel value is:

[0091] Pend=Pix+C*XZ2+(P-avgl) / 255*K.

[0092] Example 5

[0093] This embodiment is based on Embodiment 1. In this embodiment, the step "the image compensation calculation module obtains the image pixel grayscale value mapping table LUT" specifically involves: selecting an image with a central window as the test image, adjusting the frame mean of the central window pixel value to 16, 32, ..., 256 for different OPR images, setting a LUT for the central window grayscale pixel value of 16, 32, ..., 256, marking the pixel value corresponding to the initial window pixel value, and adjusting the size of the central pixel value to ensure that the marked grayscale brightness and its brightness when displayed in full screen are interpolated to obtain the grayscale pixel value under the corresponding frame mean, and gradually calculating the LUT compensation values ​​for the R, G, and B channels of the image.

[0094] Example 6

[0095] This embodiment is based on embodiment three. In this embodiment, when the image is a grayscale image, the "image pixel compensation calculation module calculates the corresponding image value compensation value" specifically means: select the value of the first correction value XZ1 in the mapping table LUT according to the range of the value obtained by the relation min / avg.

[0096] Based on the range of values ​​obtained from the relation (256-max+avg) / 256, the value of the second correction value XZ2 is selected in the mapping table LUT;

[0097] The brightness compensation coefficient K on both sides of the image is selected in the mapping table LUT based on the range of the maximum value of the image frame.

[0098] Calculate the average value (avgl) of a row of pixel values ​​based on the row containing the pixel values ​​of the processed image.

[0099] The compensation value C is obtained by interpolating the image frame mean (avg) and pixel values.

[0100] Compare the image pixel value Pix with the average value avg of a row of pixel values:

[0101] When the image pixel value Pix is ​​greater than or equal to the frame mean value avg, the compensated pixel value of the image is:

[0102] Pend=Pix+C*XZ1+(P-avgl) / 255*K

[0103] When the image pixel value is less than the frame average (avg), the compensated pixel value is:

[0104] Pend=Pix+C*XZ2+(P-avgl) / 255*K.

[0105] Example 7

[0106] This embodiment is based on embodiment three. In this embodiment, when the image is a monochrome image, the "image pixel compensation calculation module calculates the corresponding image value compensation value" specifically means: select the value of the first correction value XZ1 in the mapping table LUT according to the range of the value obtained by the relation min / avg.

[0107] Based on the range of values ​​obtained from the relation (256-max+avg) / 256, the value of the second correction value XZ2 is selected in the mapping table LUT;

[0108] The brightness compensation coefficient K on both sides of the image is selected in the mapping table LUT based on the range of the maximum value of the image frame.

[0109] Calculate the average value (avgl) of a row of pixel values ​​based on the row containing the pixel values ​​of the processed image.

[0110] The compensation value C is obtained by interpolating the image frame mean (avg) and pixel values.

[0111] Compare the image pixel value Pix with the average value avg of a row of pixel values:

[0112] When the image pixel value Pix is ​​greater than or equal to the frame mean value avg, the compensated pixel value of the image is:

[0113] Pend=Pix+C*XZ1+(P-avgl) / 255*K

[0114] When the image pixel value is less than the frame average (avg), the compensated pixel value is:

[0115] Pend=Pix+C*XZ2+(P-avgl) / 255*K.

[0116] Example 8

[0117] This embodiment is based on Embodiment 3. In this embodiment, when the image is a mixed-color image, the "image pixel compensation calculation module calculates the corresponding pixel value compensation value" specifically involves: first, processing the pixel data of the G channel image in the R, G, and B channels:

[0118] Based on the range of values ​​obtained from the relation min / avg, the value of the first correction value XZ1 is selected in the mapping table LUT;

[0119] Based on the range of values ​​obtained from the relation (256-max+avg) / 256, the value of the second correction value XZ2 is selected in the mapping table LUT;

[0120] The brightness compensation coefficient K on both sides of the image is selected in the mapping table LUT based on the range of the maximum value of the image frame.

[0121] Calculate the average value (avgl) of a row of pixel values ​​based on the row containing the pixel values ​​of the processed image.

[0122] The compensation value C is obtained by interpolating the image frame mean (avg) and pixel values.

[0123] Compare the image pixel value Pix with the average value avg of a row of pixel values:

[0124] When the image pixel value Pix is ​​greater than or equal to the frame mean value avg, the compensated pixel value of the image is:

[0125] Pend=Pix+C*XZ1+(P-avgl) / 255*K

[0126] When the image pixel value is less than the frame average (avg), the compensated pixel value is:

[0127] Pend=Pix+C*XZ2+(P-avgl) / 255*K;

[0128] Then, the pixel values ​​of the other two channels are mapped based on the original pixel ratios of the R, G, and B channels.

[0129] Example 9

[0130] This embodiment is based on Embodiment 3. In this embodiment, when the image is a dual-channel image, the "image pixel compensation calculation module calculates the corresponding pixel value compensation value" specifically means: if the image is a GB channel image or a GR channel image, then the pixel data of the G channel image in the dual-channel image is processed first:

[0131] Based on the range of values ​​obtained from the relation min / avg, the value of the first correction value XZ1 is selected in the mapping table LUT;

[0132] Based on the range of values ​​obtained from the relation (256-max+avg) / 256, the value of the second correction value XZ2 is selected in the mapping table LUT;

[0133] The brightness compensation coefficient K on both sides of the image is selected in the mapping table LUT based on the range of the maximum value of the image frame.

[0134] Calculate the average value (avgl) of a row of pixel values ​​based on the row containing the pixel values ​​of the processed image.

[0135] The compensation value C is obtained by interpolating the image frame mean (avg) and pixel values.

[0136] Compare the image pixel value Pix with the average value avg of a row of pixel values:

[0137] When the image pixel value Pix is ​​greater than or equal to the frame mean value avg, the compensated pixel value of the image is:

[0138] Pend=Pix+C*XZ1+(P-avgl) / 255*K

[0139] When the image pixel value is less than the frame average (avg), the compensated pixel value is:

[0140] Pend=Pix+C*XZ2+(P-avgl) / 255*K;

[0141] Then, the image value of the other channel is mapped based on the original pixel ratio of the two channels.

[0142] Example 10

[0143] Please see Figure 2 , Figure 2 This is a system block diagram of an image processing system for reducing brightness unevenness under different OPRs of the screen according to the present invention;

[0144] This embodiment discloses an image processing system that employs the method described in Embodiment 1 for reducing brightness unevenness under different screen OPRs. The image processing system includes: an image data statistics module 11, an image format judgment module 12, and an image pixel compensation calculation module 13.

[0145] Image data statistics module 11 counts the basic image data of a frame of an image based on the data of the input image and sends the data to the image format judgment module;

[0146] Image format determination module 12 determines the image format as: grayscale image, monochrome image, dual-channel image, or mixed color image based on the image format determination strategy and the basic image data of a frame;

[0147] Image test statistics calculation module 13 obtains the image test data and obtains the image pixel grayscale value mapping table LUT;

[0148] When the image is a grayscale image or a monochrome image, or when the image is a dual-channel image, the G channel is selected, or when the image is a mixed-color image, the image pixel compensation calculation module 14 calculates the corresponding image value compensation value: based on the range of values ​​obtained from the relationship between the minimum frame value and the average frame value of the image, the first correction value XZ1 is selected in the mapping table LUT; based on the range of values ​​obtained from the relationship between the maximum frame value and the average frame value of the image, the second correction value XZ2 is selected in the mapping table LUT; based on the range of values ​​obtained from the maximum frame value of the image, the brightness compensation coefficient K on both sides of the image is selected in the mapping table LUT; based on the first correction value XZ1, the second correction value XZ2, the average value avgl, the compensation value C of the average frame value, and the image compensation strategy under the condition of comparing the pixel value with the average frame value, the corresponding image value compensation value is obtained.

[0149] This method for reducing brightness unevenness under different OPRs ensures that the brightness of grayscale images, monochrome images, and dual-channel mixed images under different OPRs is the same as the brightness displayed under 100% OPR. The sum of the brightness of the R, G, and B three-color images is consistent with the brightness of the grayscale image under the same grayscale.

[0150] It should be understood that the above are merely preferred embodiments of the present invention and should not be construed as limiting the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A method for reducing brightness unevenness of a screen under different OPRs, characterized in that, Includes the following steps: The image data statistics module calculates the basic image data of a frame based on the input image data and sends the data to the image format judgment module. The image format determination module determines the image format as grayscale image, monochrome image, dual-channel image, or mixed color image based on the image format determination strategy and the basic image data of a frame. The image test statistics calculation module obtains the image pixel grayscale value mapping table LUT of the image test data; When the image is a grayscale image or a monochrome image, or when the image is a dual-channel image, the G channel is selected, or when the image is a mixed-color image, the image pixel compensation calculation module calculates the corresponding image value compensation value: based on the range of values ​​obtained from the relationship between the minimum frame value and the average frame value of the image, the first correction value XZ1 is selected in the mapping table LUT; based on the range of values ​​obtained from the relationship between the maximum frame value and the average frame value of the image, the second correction value XZ2 is selected in the mapping table LUT; based on the range of values ​​of the maximum frame value of the image, the brightness compensation coefficient K on both sides of the image is selected in the mapping table LUT; based on the first correction value XZ1, the second correction value XZ2, the compensation coefficient K, the average value avgl of the row of pixels in the row where the pixel value is located, the compensation value C of the average frame value, and the image compensation strategy when comparing the pixel value with the average frame value, the corresponding image value compensation value is obtained. When the image is a mixed color image or a dual-channel image, the image value of the other channel is mapped according to the ratio of the original pixels of the selected channel to the original pixels of the other channel.

2. The method for reducing brightness unevenness of a screen under different OPRs according to claim 1, characterized in that, The step "statistically calculate the basic image data of a frame" specifically involves: calculating the frame mean values ​​avgr, avgg, and avgb for each of the R, G, and B channels, the frame maximum values ​​maxr, maxg, and maxb for each of the R, G, and B channels, and the frame minimum values ​​minr, minming, and minb for each of the R, G, and B channels.

3. The method for reducing brightness unevenness of a screen under different OPRs according to claim 1, characterized in that, The image format determination strategy is as follows: If the maximum frame values ​​(maxr, maxg, and maxb) of the R, G, and B channels are all greater than zero, and the difference between the maximum frame average (maxavg) and the minimum frame average (minavg) of the R, G, and B channels is less than or equal to 8, the image is determined to be a grayscale image. If the maximum values ​​(maxr, maxg, and maxb) of the three channels are all greater than zero, and the difference between the maximum frame average (maxavg) and the minimum frame average (minavg) of the R, G, and B channels is greater than 8, the image is determined to be a mixed color image. If only one of the maximum frame values ​​of the R, G, and B channels is greater than 0, and the difference between the maximum and minimum frame values ​​of any one of the R, G, and B channels is greater than 5, the image is determined to be a monochrome image. If only one of the maximum frame values ​​of any one of the R, G, and B channels is less than zero, and the difference between the maximum and minimum frame values ​​of any of the other two channels is greater than 5, the image is determined to be a dual-channel image.

4. The method for reducing brightness unevenness of a screen under different OPRs according to claim 3, characterized in that, The image compensation strategy for comparing pixel values ​​with frame average is as follows: Compare the image pixel value Pix with the mean of a row of pixel values, avgl: When the image pixel value Pix is ​​greater than or equal to the frame mean value avg, the compensated pixel value of the image is: Pend=Pix+C*XZ1+(Pix-avgl) / 255*K When the image pixel value is less than the frame average (avg), the compensated pixel value is: Pend=Pix+C*XZ2+(Pix-avgl) / 255*K.

5. The method for reducing brightness unevenness of a screen under different OPRs according to claim 1, characterized in that, The step "Image Test Statistical Calculation Module Obtains Image Pixel Grayscale Value Mapping Table (LUT) for Image Test Data" specifically involves: selecting an image with a central window as the test image; adjusting the frame mean of the central window pixel value to 16, 32, ..., 256 for different OPR images; setting a LUT for the central window grayscale pixel value of 16, 32, ..., 256; marking the pixel value corresponding to the initial window pixel value; and adjusting the size of the central pixel value to ensure that the marked grayscale brightness and its brightness when displayed in full screen are interpolated to obtain the corresponding grayscale pixel value under the frame mean; and gradually calculating the LUT compensation values ​​for the R, G, and B channels of the image.

6. The method for reducing brightness unevenness of a screen under different OPRs according to claim 3, characterized in that, When the image is a grayscale image, the "image pixel compensation calculation module calculates the corresponding image value compensation value" specifically means: select the value of the first correction value XZ1 in the mapping table LUT according to the range of the value obtained by the relation min / avg; Based on the range of values ​​obtained from the relation (256-max+avg) / 256, the value of the second correction value XZ2 is selected in the mapping table LUT; The brightness compensation coefficient K on both sides of the image is selected in the mapping table LUT based on the range of the maximum value of the image frame. Calculate the average value (avgl) of a row of pixel values ​​based on the row containing the pixel values ​​of the processed image. The compensation value C is obtained by interpolating the image frame mean (avg) and pixel values. Compare the image pixel value Pix with the mean of a row of pixel values, avgl: When the image pixel value Pix is ​​greater than or equal to the frame mean value avg, the compensated pixel value of the image is: Pend=Pix+C*XZ1+(Pix-avgl) / 255*K When the image pixel value is less than the frame average (avg), the compensated pixel value is: Pend=Pix+C*XZ2+(Pix-avgl) / 255*K.

7. The method for reducing brightness unevenness of a screen under different OPRs according to claim 3, characterized in that, When the image is a monochrome image, the "image pixel compensation calculation module calculates the corresponding pixel value compensation value" specifically means: select the value of the first correction value XZ1 in the mapping table LUT according to the range of values ​​obtained by the relation min / avg; Based on the range of values ​​obtained from the relation (256-max+avg) / 256, the value of the second correction value XZ2 is selected in the mapping table LUT; The brightness compensation coefficient K on both sides of the image is selected in the mapping table LUT based on the range of the maximum value of the image frame. Calculate the average value (avgl) of a row of pixel values ​​based on the row containing the pixel values ​​of the processed image. The compensation value C is obtained by interpolating the image frame mean (avg) and pixel values. Compare the image pixel value Pix with the mean of a row of pixel values, avgl: When the image pixel value Pix is ​​greater than or equal to the frame mean value avg, the compensated pixel value of the image is: Pend=Pix+C*XZ1+(Pix-avgl) / 255*K When the image pixel value is less than the frame average (avg), the compensated pixel value is: Pend=Pix+C*XZ2+(Pix-avgl) / 255*K.

8. The method for reducing brightness unevenness of a screen under different OPRs according to claim 3, characterized in that, When the image is a mixed-color image, the "image pixel compensation calculation module calculates the corresponding pixel value compensation value" specifically involves: first, processing the pixel data of the G channel of the R, G, and B images: Based on the range of values ​​obtained from the relation min / avg, the value of the first correction value XZ1 is selected in the mapping table LUT; Based on the range of values ​​obtained from the relation (256-max+avg) / 256, the value of the second correction value XZ2 is selected in the mapping table LUT; The brightness compensation coefficient K on both sides of the image is selected in the mapping table LUT based on the range of the maximum value of the image frame. Calculate the average value (avgl) of a row of pixel values ​​based on the row containing the pixel values ​​of the processed image. The compensation value C is obtained by interpolating the image frame mean (avg) and pixel values. Compare the image pixel value Pix with the mean of a row of pixel values, avgl: When the image pixel value Pix is ​​greater than or equal to the frame mean value avg, the compensated pixel value of the image is: Pend=Pix+C*XZ1+(Pix-avgl) / 255*K When the image pixel value is less than the frame average (avg), the compensated pixel value is: Pend=Pix+C*XZ2+(Pix-avgl) / 255*K; Then, the pixel values ​​of the other two channels are mapped based on the original pixel ratios of the R, G, and B channels.

9. The method for reducing brightness unevenness of a screen under different OPRs according to claim 3, characterized in that, When the image is a dual-channel image, the "image pixel compensation calculation module calculates the corresponding pixel value compensation value" specifically means: if the image is a GB channel image or a GR channel image, then the pixel data of the G channel image in the dual-channel image is processed first: Based on the range of values ​​obtained from the relation min / avg, the value of the first correction value XZ1 is selected in the mapping table LUT; Based on the range of values ​​obtained from the relation (256-max+avg) / 256, the value of the second correction value XZ2 is selected in the mapping table LUT; The brightness compensation coefficient K on both sides of the image is selected in the mapping table LUT based on the range of the maximum value of the image frame. Calculate the average value (avgl) of a row of pixel values ​​based on the row containing the pixel values ​​of the processed image. The compensation value C is obtained by interpolating the image frame mean (avg) and pixel values. Compare the image pixel value Pix with the mean of a row of pixel values, avgl: When the image pixel value Pix is ​​greater than or equal to the frame mean value avg, the compensated pixel value of the image is: Pend=Pix+C*XZ1+(Pix-avgl) / 255*K When the image pixel value is less than the frame average (avg), the compensated pixel value is: Pend=Pix+C*XZ2+(Pix-avgl) / 255*K; Then, the image value of the other channel is mapped based on the original pixel ratio of the two channels.

10. An image processing system employing the method for reducing brightness unevenness under different OPRs of a screen as described in claim 1, characterized in that, The image processing system includes: an image data statistics module, an image format judgment module, and an image pixel compensation calculation module; The image data statistics module calculates the basic image data of a frame based on the input image data and sends the data to the image format judgment module. The image format determination module determines the image format as grayscale image, monochrome image, dual-channel image, or mixed color image based on the image format determination strategy and the basic image data of a frame. The image test statistics calculation module obtains the image test data and generates a LUT (Layered Table) mapping table of image pixel grayscale values. When the image is a grayscale image or a monochrome image, or when the image is a dual-channel image, the G channel is selected, or when the image is a mixed-color image, the image pixel compensation calculation module calculates the corresponding image value compensation value: based on the range of values ​​obtained from the relationship between the minimum frame value and the average frame value of the image, the first correction value XZ1 is selected in the mapping table LUT; based on the range of values ​​obtained from the relationship between the maximum frame value and the average frame value of the image, the second correction value XZ2 is selected in the mapping table LUT; based on the range of values ​​of the maximum frame value of the image, the brightness compensation coefficient K on both sides of the image is selected in the mapping table LUT; based on the first correction value XZ1, the second correction value XZ2, the compensation coefficient K, the average value avgl of the row of pixels in the row where the pixel value is located, the compensation value C of the average frame value, and the image compensation strategy under the comparison of the pixel value and the average frame value, the corresponding image value compensation value is obtained.

Images