Coding method and related device for demura compensation data

Abstract

The application provides a coding and decoding method of Demura compensation data and related equipment, and after Demura compensation data of different color channels is generated, the Demura compensation data is reordered and pretreated to obtain a plurality of subblocks; then, the compensation data in each subblock is encoded, the obtained encoding code stream of each subblock is combined, and compensation data encoding corresponding to each color channel in a target AMOLED display panel is obtained; in the decoding process, the read compensation data encoding is decoded and reconstructed to obtain the reconstructed Demura compensation data for gray scale compensation of each pixel position of the target AMOLED display panel, and the effect of eliminating Mura defects and display brightness uniformity of the AMOLED display panel at different display brightness values and input image gray scales is improved.

Description

Technical Field

[0001] This invention relates to the field of display technology, and in particular to a method and related equipment for encoding and decoding Demura compensation data. Background Technology

[0002] Active-matrix organic light-emitting diode (AMOLED) is a novel active-matrix organic light-emitting diode display technology with advantages such as fast response speed, wide color gamut, high contrast, and low dynamic power consumption. The brightness of AMOLED is controlled by the current of the thin-film transistors (TFTs) driving the pixel circuit. Due to material and process limitations, the parasitic capacitance, threshold voltage Vth, and mobility of TFTs exhibit non-uniformity and migration phenomena. Furthermore, the luminous efficiency of OLEDs slowly degrades. These factors all contribute to brightness non-uniformity in AMOLED panel displays and may even cause color shift defects, collectively known as the Mura phenomenon / effect. Therefore, compensation is needed for the AMOLED pixel circuit, known as Demura. Depending on the principle, pixel circuit compensation methods are divided into internal compensation and external compensation. Internal compensation refers to constructing a compensation sub-circuit within the pixel circuit using TFTs to compensate for the threshold voltage Vth. th Uneven brightness caused by TFTs in pixel circuits. Considering power consumption and cost, the number of TFTs in the pixel circuit is limited, resulting in limited compensation effectiveness. External compensation refers to using external circuits or devices to sense the physical quantities of the electrical or optical characteristics of the pixel circuit and then performing corresponding compensation. It can simultaneously compensate for brightness unevenness caused by TFT and OLED characteristic drift, with good compensation effect and versatility and flexibility. According to different principles, external compensation is divided into two types: optical extraction and electrical extraction. Electrical extraction refers to using external sensing circuits to extract electrical signals from the TFT and OLED and then performing corresponding compensation. Optical extraction refers to providing the AMOLED panel with the same input, using high-resolution and high-precision optical cameras to collect brightness signals, generating corresponding compensation data, so that the compensated display brightness tends to be uniform. Overall, optical extraction compensation has the characteristics of intuitive basic principles, flexible compensation methods, and easy integration with Field-Programmable Gate Arrays (FPGAs), making it the mainstream Demura method at present.

[0003] External optical extraction demura must consider the actual brightness uniformity and color cast of each pixel circuit under different gray levels and color channels, and even the overall display brightness value (DBV) of the display panel. Furthermore, since the generated compensation data needs to be burned into the non-volatile memory (ROM) of the display driver IC (DDIC), the amount of compensation data generated must also be considered to save ROM space and reduce DDIC cost. Taking a 2560×1600 resolution panel as an example, if it is necessary to store compensation values ​​for three gray levels, and each compensation value is 6 bits, then the total compensation data for the three RGB color channels requires 2560×1600×3×3×6=221M bits of ROM space. AMOLED panel demura processing must efficiently compress the external compensation data before burning the compressed binary bitstream into ROM. Therefore, a suitable encoding and decoding method for external compensation data in demura is needed to strike a balance between compensation effect, compensation data volume, and real-time performance.

[0004] Some existing encoding and decoding methods have insufficient compression ratios (i.e., the amount of compensation data after compression is still large, requiring a lot of ROM space). Combining them with downsampling techniques directly affects the compensation effect. Encoding and decoding methods that combine Mura region classification (divided into trend type and random type) introduce additional computational load and storage of region locations. From the perspective of compression technology, they usually adopt the traditional approach of prediction + residual coding, or the three-channel interleaved coding technology JPEG LS for lossless image compression. They all have their own shortcomings in terms of compensation effect and / or compression ratio.

[0005] There are also some Demura data compression and decompression methods, which mainly rely on the constructed Demura compensation data table training dataset. The Mura characteristics of display panels of different models and sizes vary, and the compensation data are very different. In addition, deep network models are not convenient to deploy on lightweight DDIC, so they are not very practical.

[0006] Some Demura-compensated data compression methods combine sparse representation and end-to-end deep learning. Although they have excellent compression performance, they involve vectorization, sparse dictionaries, and the construction of compression objective functions, which are computationally intensive and complex, making them unsuitable for the implementation and deployment of decoders in DDIC. Summary of the Invention

[0007] This invention provides a method and related equipment for encoding and decoding Demura compensation data, the purpose of which is to eliminate the Mura defect at different display brightness values ​​and different image gray levels while saving storage space in the display driver chip.

[0008] To achieve the above objectives, the present invention provides a method for encoding and decoding Demura compensation data for AMOLED display panels, comprising:

[0009] Step 1: Generate Demura compensation data for different color channels in the target AMOLED display panel sequentially by selecting the typical grayscale of the target AMOLED display panel. The number of Demura compensation data for each color channel is equal to the number of pixels in the target AMOLED display panel.

[0010] Step 2: Reorder the Demura compensation data for each color channel to generate multiple sets of reordered Demura compensation data, and divide each set of reordered Demura compensation data into multiple sub-blocks.

[0011] Step 3: Using each sub-block as an encoding unit, predict the compensation value of each pixel in each sub-block to obtain the prediction mode corresponding to each sub-block and obtain the predicted pixel compensation value of each pixel position in each sub-block.

[0012] Step 4: For each sub-block, calculate the difference between the actual compensation value and the predicted pixel compensation value corresponding to each pixel position in the sub-block to obtain the prediction residual data of each sub-block. Then, transform and quantize the prediction residual data to obtain the frequency domain prediction residual transformation coefficients of each sub-block.

[0013] Step 5: Perform entropy coding on each sub-block based on the frequency domain prediction residual transform coefficients to obtain the coded bitstream of each sub-block, and combine the coded bitstreams of the sub-blocks to obtain the coded bitstream of each group of reordered Demura compensation data in the target AMOLED display panel.

[0014] Step 6: Read the encoded bitstream of each group of reordered Demura compensation data in the target AMOLED display panel and decode it in the reverse process of encoding to obtain the reconstructed Demura compensation data. The reconstructed Demura compensation data is used to perform grayscale data compensation on each pixel position of the target AMOLED display panel.

[0015] Furthermore, step 2 specifically includes:

[0016] Based on the distribution of each pixel position in the AMOLED display panel, the Demura compensation data of each color channel is reordered row by row from left to right and from top to bottom to obtain multiple sets of reordered Demura compensation data. Each set of reordered Demura compensation data has a width of 16 and a height of W×H / 16, where W and H are the width and height of the original Demura compensation data, respectively.

[0017] Each group of reordered Demura compensation data is divided into W×H / 256 sub-blocks.

[0018] Furthermore, the prediction models include 7 types, among which:

[0019] The first prediction model is

[0020] dst[1]=dst[2]=dst[3]=dst[4]=I;

[0021] dst[5]=dst[6]=dst[7]=dst[8]=J;

[0022] dst[9]=dst

[10] =dst

[11] =dst

[12] =K;

[0023] st

[13] =dst

[14] =dst

[15] =dst

[16] =L;

[0024] The second prediction model is:

[0025] dst[1]=dst[5]=dst[9]=dst

[13] =A;

[0026] dst[2]=dst[6]=dst

[10] =dst

[14] =B;

[0027] dst[3]=dst[7]=dst

[11] =dst

[15] =C;

[0028] dst[4]=dst[8]=dst

[12] =dst

[16] =D;

[0029] The third prediction model is: dst[1,16]=A;

[0030] The fourth prediction pattern is: dst[1,16]=B;

[0031] The fifth prediction pattern is: dst[1,16]=C;

[0032] The sixth prediction pattern is: dst[1,16]=I;

[0033] The seventh prediction pattern is: dst[1,16]=J;

[0034] Where dst[·] represents the predicted value of the current sub-block, and A, B, C, D, I, J, K, L all represent the reconstructed pixel values ​​of the upper and left sub-blocks adjacent to the current sub-block.

[0035] Furthermore, step 4 includes:

[0036] For each sub-block, the difference between the actual compensation value and the predicted pixel compensation value corresponding to each pixel position in the sub-block is calculated to obtain the prediction residual data for each sub-block;

[0037] The frequency domain transform coefficients of each sub-block are obtained by performing discrete cosine transform on the prediction residual data of each sub-block.

[0038] The frequency domain transform coefficients of each sub-block are quantized to obtain the frequency domain prediction residual transform coefficients of each sub-block.

[0039] Furthermore, by performing a discrete cosine transform on the prediction residual data of each sub-block, the frequency domain transform coefficients T[u,v] of each sub-block are obtained as follows:

[0040]

[0041] Where [u,v] represents the frequency components in the horizontal and vertical directions in the corresponding transform domain, X represents the prediction residual data of the sub-block, [x,y] represents the position of the prediction residual data, and s represents the number of sub-blocks.

[0042] Furthermore, by quantizing the frequency domain transform coefficients of each sub-block, the frequency domain prediction residual transform coefficients Q[u,v] of each sub-block are obtained as follows:

[0043]

[0044] Among them, Q step This represents the quantization step size, u = 1, 2, 3, 4, v = 1, 2, 3, 4.

[0045] Furthermore, step 6 includes:

[0046] Read the encoded bitstream of each group of reordered Demura compensation data in the target AMOLED display panel;

[0047] Entropy decoding is performed on the frequency domain prediction residual transformation coefficients of each sub-block to obtain the frequency domain prediction residual transformation coefficients;

[0048] The frequency domain transform coefficients of the prediction error are dequantized to obtain the frequency domain transform coefficients of each sub-block.

[0049] The frequency domain transform coefficients of each sub-block are subjected to inverse discrete cosine transform to obtain the prediction residual data of each sub-block;

[0050] The compensation data for each sub-block is reconstructed based on each predicted residual data and the corresponding prediction mode to obtain the reconstructed Demura compensation data.

[0051] The present invention also provides a Demura compensation data encoding and decoding device for use in AMOLED display panels, comprising:

[0052] The generation module is used to sequentially generate Demura compensation data for different color channels in the target AMOLED display panel by selecting the typical grayscale of the target AMOLED display panel. The number of Demura compensation data for each color channel is equal to the number of pixels in the target AMOLED display panel.

[0053] The reordering module is used to reorder the Demura compensation data of each color channel separately, generate multiple sets of reordered Demura compensation data, and divide each set of reordered Demura compensation data into multiple sub-blocks.

[0054] The prediction module is used to predict the compensation value of each pixel in each sub-block as the encoding unit, so as to obtain the prediction mode corresponding to each sub-block and obtain the predicted pixel compensation value of each pixel position in each sub-block.

[0055] The processing module is used to calculate the difference between the actual compensation value and the predicted pixel compensation value corresponding to each pixel position in each sub-block for each sub-block, to obtain the prediction residual data of each sub-block, and to transform and quantize the prediction residual data to obtain the frequency domain prediction residual transformation coefficients of each sub-block.

[0056] The combination module is used to entropy encode each sub-block based on the frequency domain prediction residual transform coefficients to obtain the coded bitstream of each sub-block, and to combine the coded bitstreams of the sub-blocks to obtain the coded bitstream of each group of reordered Demura compensation data in the target AMOLED display panel.

[0057] The decoding module is used to read the encoded bitstream of each group of reordered Demura compensation data in the target AMOLED display panel and decode it in the reverse process of encoding to obtain the reconstructed Demura compensation data. The reconstructed Demura compensation data is used to perform grayscale data compensation on each pixel position of the target AMOLED display panel.

[0058] The present invention also provides a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement a method for encoding and decoding Demura compensation data.

[0059] The present invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements a method for encoding and decoding Demura compensation data.

[0060] The above-described solution of the present invention has the following beneficial effects:

[0061] Compared with existing technologies, this invention first acquires and reorders Demura compensation data for different color channels to generate multiple sets of reordered Demura compensation data. Each set of reordered Demura compensation data is then divided into multiple sub-blocks, significantly reducing the display driver chip area overhead required for caching and saving storage space in the display driver chip. Next, the compensation data within each sub-block is encoded using mode prediction, transformation, quantization, and entropy coding to achieve compression. The encoded bitstreams of each sub-block are then combined to obtain the compensation data encoding corresponding to each color channel in the target AMOLED display panel. Then, the encoded bitstreams of each set of reordered Demura compensation data in the target AMOLED display panel are read and decoded in the reverse process to obtain the reconstructed Demura compensation data. The reconstructed Demura compensation data is used to perform grayscale data compensation on each pixel position of the target AMOLED display panel, eliminating Mura defects at different display brightness values ​​and different image grayscales while saving storage space in the display driver chip.

[0062] Other beneficial effects of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0063] Figure 1 This is a flowchart illustrating an embodiment of the present invention;

[0064] Figure 2 This is a schematic diagram of a macroblock in an embodiment of the present invention;

[0065] Figure 3 This is a schematic diagram illustrating the predicted pixel compensation value in an embodiment of the present invention;

[0066] Figure 4 This is a schematic diagram of the encoding / decoding device in an embodiment of the present invention;

[0067] Figure 5 This is a schematic diagram of the structure of the terminal device in an embodiment of the present invention. Detailed Implementation

[0068] To make the technical problems, solutions, and advantages of this invention clearer, a detailed description will be provided below with reference to the accompanying drawings and specific embodiments. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0069] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0070] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a locking connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0071] Furthermore, the technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0072] This invention addresses existing problems by providing a method and related equipment for encoding and decoding Demura compensation data.

[0073] like Figure 1 As shown, an embodiment of the present invention provides a method for encoding and decoding Demura compensation data for an AMOLED display panel, comprising:

[0074] Step 1: Generate Demura compensation data for different color channels in the target AMOLED display panel sequentially by selecting the typical grayscale of the target AMOLED display panel. The number of Demura compensation data for each color channel is equal to the number of pixels in the target AMOLED display panel.

[0075] Step 2: Reorder the Demura compensation data for each color channel to generate multiple sets of reordered Demura compensation data, and divide each set of reordered Demura compensation data into multiple sub-blocks.

[0076] Step 3: Using each sub-block as an encoding unit, predict the compensation value of each pixel in each sub-block to obtain the prediction mode corresponding to each sub-block and obtain the predicted pixel compensation value of each pixel position in each sub-block.

[0077] Step 4: For each sub-block, calculate the difference between the actual compensation value and the predicted pixel compensation value corresponding to each pixel position in the sub-block to obtain the prediction residual data of each sub-block. Then, transform and quantize the prediction residual data to obtain the frequency domain prediction residual transformation coefficients of each sub-block.

[0078] Step 5: Perform entropy coding on each sub-block based on the frequency domain prediction residual transform coefficients to obtain the coded bitstream of each sub-block, and combine the coded bitstreams of the sub-blocks to obtain the coded bitstream of each group of reordered Demura compensation data in the target AMOLED display panel.

[0079] Step 6: Read the encoded bitstream of each group of reordered Demura compensation data in the target AMOLED display panel and decode it in the reverse process of encoding to obtain the reconstructed Demura compensation data. The reconstructed Demura compensation data is used to perform grayscale data compensation on each pixel position of the target AMOLED display panel.

[0080] Specifically, step 1 includes:

[0081] Select a typical grayscale value for the AMOLED display panel, such as [3264192], and generate compensation data for the R, G, and B color channels of the display panel as [R32 G32 B32 R64 G64 B64 R192 G192B192]. Considering the random distribution and uncertainty of the AMOLED display panel's morphology, the compensation data for each color channel and grayscale value corresponds one-to-one with the actual pixel points of each color channel of the display panel. The size of the pixel circuits in each channel may differ for pixels with different RGB arrangements. Here, we take a uniform RGB size as an example. That is, we assume that the size of the display panel is 1792×828; the corresponding Demura compensation data for each typical grayscale value under the R, G, and B color channels is also 1792×828.

[0082] It should be noted that grayscale refers to the brightness level relationship between the darkest black and the brightest white of the display panel. Typical grayscale refers to the most typical brightness level of the display panel, such as level 32, level 64, level 192, level 256, etc. In this embodiment of the invention, level 32, level 64, and level 192 are taken as typical grayscale.

[0083] The preferred option is that step 2 specifically includes:

[0084] Based on the distribution of each pixel position in the AMOLED display panel, the Demura compensation data of each color channel is reordered row by row from left to right and from top to bottom to obtain multiple sets of reordered Demura compensation data. Each set of reordered Demura compensation data has a width of 16 and a height of W×H / 16, where W and H are the width and height of the original Demura compensation data, respectively.

[0085] Each group of reordered Demura compensation data is divided into W×H / 256 sub-blocks.

[0086] In embodiments of the present invention, such as Figure 2 As shown, the 256 reordered compensation data points in each row of the 1792×828 reordered Demura compensation data are divided into W×H / 256 4×4 sub-blocks. All sub-blocks in each macroblock are then reordered in a "z" shape from left to right and from top to bottom. This ensures that when the compensation data is read in row-by-row order, each macroblock only needs to buffer 256 pixels instead of 16 rows of data, i.e., 16×828 compensation data points. During decoding output, it is only necessary to decode the encoding within the sub-blocks sequentially and restore them to the 256 pixels of that row for sequential output.

[0087] Specifically, in step 3, each sub-block is used as an encoding unit to predict the compensation value of each pixel in each sub-block. According to the corresponding prediction mode, the prediction error between the actual compensation value and the prediction mode compensation value is calculated, and the prediction mode with the smallest prediction error is selected as the encoding prediction mode of the sub-block.

[0088] The preferred option is that the prediction mode includes 7 selectable prediction modes for independently predicting each 4×4 sub-block, suitable for image coding prediction modes with a large amount of detail, such as... Figure 3As shown, pixels A to D at the top and I to L at the left of the 4×4 sub-block are encoded and reconstructed pixels, used as prediction reference pixels in the encoding and decoding process. Pixels 1 to 16 are pixels to be predicted, implemented using the values ​​of A to D, I to L, and 7 prediction modes. The first prediction mode is the horizontal prediction mode, which derives the corresponding pixel values ​​horizontally from I, J, K, and L. The second prediction mode is the vertical prediction mode, which derives the corresponding pixel values ​​vertically from A, B, C, and D. The third to seventh prediction modes are the reference prediction modes, which derive all the corresponding pixel values ​​at each position within the sub-block sequentially from A, B, C, I, and J.

[0089] Specifically, the first prediction model is

[0090] dst[1]=dst[2]=dst[3]=dst[4]=I;

[0091] dst[5]=dst[6]=dst[7]=dst[8]=J;

[0092] dst[9]=dst

[10] =dst

[11] =dst

[12] =K;

[0093] st

[13] =dst

[14] =dst

[15] =dst

[16] =L;

[0094] The second prediction model is:

[0095] dst[1]=dst[5]=dst[9]=dst

[13] =A;

[0096] dst[2]=dst[6]=dst

[10] =dst

[14] =B;

[0097] dst[3]=dst[7]=dst

[11] =dst

[15] =C;

[0098] dst[4]=dst[8]=dst

[12] =dst

[16] =D;

[0099] The third prediction model is: dst[1,16]=A;

[0100] The fourth prediction pattern is: dst[1,16]=B;

[0101] The fifth prediction pattern is: dst[1,16]=C;

[0102] The sixth prediction pattern is: dst[1,16]=I;

[0103] The seventh prediction pattern is: dst[1,16]=J;

[0104] Where dst[·] represents the predicted value of the current sub-block, and A, B, C, D, I, J, K, L all represent the reconstructed pixel values ​​of the upper and left sub-blocks adjacent to the current sub-block.

[0105] In this embodiment of the invention, for each sub-block, the reconstruction loss of various prediction modes is calculated and compared in sequence, and the prediction mode with the smallest reconstruction loss is selected as the optimal prediction mode for the current 4×4 sub-block. The prediction modes of 16 sub-blocks are determined in sequence, and the prediction mode encoded bitstream of each sub-block can be obtained.

[0106] The preferred option is that step 4 includes:

[0107] Considering the inevitable error between the predicted value and the actual data of the sub-block, in order to reduce the coding distortion caused by the prediction error, for each sub-block, the difference between the actual compensation value and the predicted pixel compensation value corresponding to each pixel position in the sub-block is calculated to obtain the prediction residual data of each sub-block.

[0108] The frequency domain transform coefficients of each sub-block are obtained by performing discrete cosine transform on the prediction residual data of each sub-block.

[0109] The frequency domain transform coefficients of each sub-block are quantized to obtain the frequency domain prediction residual transform coefficients of each sub-block.

[0110] In this embodiment of the invention, the discrete cosine transform converts the image from the spatial domain to the frequency domain and separates the high-frequency and low-frequency information of the image. The high-frequency coefficients are more numerous, but the amplitude is relatively small. Therefore, the high-frequency information is easily quantized to 0 during the quantization process, thereby achieving the purpose of compression.

[0111] The preferred method is to perform a discrete cosine transform on the prediction residual data of each sub-block to obtain the frequency domain transform coefficients T[u,v] of each sub-block as follows:

[0112]

[0113] Where [u,v] represents the frequency components in the horizontal and vertical directions in the corresponding transform domain, X represents the prediction residual data of the sub-block, [x,y] represents the position of the prediction residual data, and s represents the number of sub-blocks.

[0114] The preferred method is to quantize the frequency domain transform coefficients of each sub-block separately, so as to obtain the frequency domain prediction residual transform coefficients Q[u,v] of each sub-block:

[0115]

[0116] Among them, Q step This represents the quantization step size, u = 1, 2, 3, 4, v = 1, 2, 3, 4.

[0117] Specifically, step 5 includes:

[0118] Entropy coding is performed on each sub-block based on the frequency domain prediction residual transform coefficients to obtain the entropy coded bitstream of each sub-block. The frequency domain prediction residual transform coefficients are used to reconstruct the prediction residual of the sub-block. The coded bitstream of the sub-block consists of prediction mode coding, prediction residual coding (frequency domain prediction residual transform coefficients, quantization coefficients), etc. The coded bitstream represents the bitstream during coding. The coded bitstream of the sub-block includes the frequency domain prediction residual transform coefficients.

[0119] The encoded bitstreams of the sub-blocks are spliced ​​and combined in the order of the sub-blocks to obtain the compensation data encoding corresponding to each color channel in the target AMOLED display panel.

[0120] It should be noted that entropy coding is an existing lossless compression coding method. In this embodiment of the invention, considering that the prediction residual data of each sub-block exhibits the following characteristics after transformation and quantization: non-zero coefficients are mainly concentrated in the low-frequency part, while most of the high-frequency coefficients are zero; after zig-zag scanning, the non-zero coefficient values ​​near the DC coefficient are relatively large, while the non-zero coefficient values ​​at high-frequency positions are mostly +1 and -1; the number of non-zero coefficients in adjacent sub-blocks is correlated; entropy coding utilizes the correlation provided by adjacent encoded symbols to select a suitable context model for the symbol to be encoded, including the selection of the table required for non-zero coefficient encoding and the update of the suffix length of the trailing coefficient, to achieve efficient compression.

[0121] Preferably, step 6 includes:

[0122] Read the encoded bitstream of each group of reordered Demura compensation data in the target AMOLED display panel;

[0123] Entropy decoding is performed on the frequency domain prediction residual transformation coefficients of each sub-block to obtain the frequency domain prediction residual transformation coefficients;

[0124] The frequency domain transform coefficients of the prediction error are dequantized to obtain the frequency domain transform coefficients of each sub-block.

[0125] The frequency domain transform coefficients of each sub-block are subjected to inverse discrete cosine transform to obtain the prediction residual data of each sub-block;

[0126] The compensation data for each sub-block is reconstructed based on each predicted residual data and the corresponding prediction mode to obtain the reconstructed Demura compensation data.

[0127] The decoding process in this embodiment of the invention is the reverse of the encoding process. Therefore, the decoding process involves sequentially reading the compensation data encoded bitstream according to the encoding order, and performing entropy decoding, inverse quantization, and inverse DCT (i.e., IDCT) processing. First, the prediction residual of each 4x4 sub-block is obtained. Then, based on each prediction residual data, the compensation data of each sub-block is reconstructed to obtain the reconstructed Demura compensation data. Finally, the sub-blocks are further processed according to the attached... Figure 1 The pixel rearrangement rules are used to obtain compensation data for 256 pixel positions in a row, which is used to perform grayscale compensation for each pixel position of the target AMOLED display panel.

[0128] In this embodiment of the invention, for Demura compensation of typical gray levels, compensation can be performed by directly reading the corresponding position compensation data after decoding and reconstructing the typical gray level Demura data; for Demura compensation of atypical gray levels, compensation can be performed by referring to the Demura compensation reconstruction data of neighboring typical gray levels, and the compensation of the corresponding pixel position of the final atypical gray level can be obtained together; the compensation data is then superimposed and displayed, thus completing the final Demura compensation; the statistics of peak signal-to-noise ratio after compression at different compression ratios before and after typical gray level reconstruction with Demura compensation are shown in Table 1 below:

[0129] Table 1

[0130] R_032 52.3091 52.052 51.8105 51.5691 51.263 51.1645 51.102 G_032 52.2103 51.7218 51.191 50.8178 50.3948 50.2082 50.0835 B_032 52.3253 52.1141 51.9152 51.7135 51.4318 51.3442 51.2895 grayscale 16:1 compression 18:1 compression 20:1 compression 24:1 compression 27:1 compression 30:1 compression 32:1 compression R_064 49.4003 49.1567 48.9648 48.6771 48.5485 48.451 48.3769 G_064 48.3991 48.1612 47.9779 47.6324 47.4634 47.3386 47.2703 B_064 49.6509 49.4008 49.2147 48.9218 48.7941 48.6955 48.6242 grayscale 18:1 compression 20:1 compression 24:1 compression 28:1 compression 30:1 compression 32:1 compression 36:1 compression R_192 47.4817 47.2553 46.4373 45.7917 45.6261 45.4753 40.3264 G_192 45.8948 45.5049 44.7491 44.2269 44.0294 43.8624 41.8871 B_192 47.535 47.3136 46.4683 45.8848 45.7409 45.5774 40.5031

[0131] As shown in Table 1, the encoding / decoding method provided by this invention reconstructs typical grayscale compensation data using different compression ratios. The peak signal-to-noise ratio (PSNR) gradually decreases with increasing compression ratio, but remains at a relatively high level. Furthermore, the lower the grayscale, the higher the PSNR. This is because the Demura compensation value for low grayscales has a relatively small range, resulting in a smaller compensation error. Conversely, the range of Demura compensation data for high grayscales is larger, leading to increased reconstruction error and a corresponding decrease in PSNR. The Demura compensation data encoding / decoding method provided by this invention can achieve different compression ratios. It allows for flexible setting of compression ratios for different grayscales and color channels based on actual Demura effect requirements, thereby ensuring that the final encoded bitstream meets the storage limitations of high compression ratios in display driver chips, demonstrating significant practical value.

[0132] In this embodiment of the invention, PSNR statistics are obtained by comparing the compensation data reconstructed through decoding with the actual uncompressed encoded compensation data;

[0133] The different compression ratios are designed as follows: the bitstream process of this application is clear, the distribution of each bitstream is basically clear, and different prediction modes, transformation coefficients, and quantization coefficients can be combined to obtain bitstreams with different coding lengths. Conversely, by fixing the compression ratio, the coding process can be optimized among various combinations to achieve the fixed compression ratio test requirements.

[0134] Compared with the prior art, the embodiments of the present invention first acquire and reorder Demura compensation data of different color channels to generate multiple sets of reordered Demura compensation data, and divide each set of reordered Demura compensation data into multiple sub-blocks, which significantly reduces the display driver chip area overhead required for caching and saves storage space in the display driver chip. Then, the compensation data in each sub-block is encoded through mode prediction, transformation, quantization and entropy coding to achieve compression. The encoded bitstreams of each sub-block are combined to obtain the compensation data encoding corresponding to each color channel in the target AMOLED display panel. Next, the encoded bitstream of each set of reordered Demura compensation data in the target AMOLED display panel is read and decoded in the reverse process of encoding to obtain the reconstructed Demura compensation data. The reconstructed Demura compensation data is used to perform grayscale data compensation for each pixel position of the target AMOLED display panel, eliminating the Mura defect at different display brightness values ​​and different image grayscales while saving storage space in the display driver chip.

[0135] This invention also provides a Demura compensation data encoding and decoding device, applied to AMOLED display panels, such as... Figure 4 As shown, the encoding / decoding device 100 includes:

[0136] The generation module 101 is used to sequentially generate Demura compensation data for different color channels in the target AMOLED display panel by selecting the typical grayscale of the target AMOLED display panel. The number of Demura compensation data for each color channel is equal to the number of pixels in the target AMOLED display panel.

[0137] The reordering module 102 is used to reorder the Demura compensation data of each color channel to generate multiple sets of reordered Demura compensation data, and to divide each set of reordered Demura compensation data into multiple sub-blocks.

[0138] The prediction module 103 is used to predict the compensation value of each pixel in each sub-block using each sub-block as the encoding unit, so as to obtain the prediction mode corresponding to each sub-block and obtain the predicted pixel compensation value of each pixel position in each sub-block.

[0139] The processing module 104 is used to calculate the difference between the actual compensation value and the predicted pixel compensation value corresponding to each pixel position in each sub-block for each sub-block, to obtain the prediction residual data of each sub-block, and to transform and quantize the prediction residual data to obtain the frequency domain prediction residual transformation coefficients of each sub-block.

[0140] The combination module 105 is used to entropy encode each sub-block based on the frequency domain prediction residual transform coefficients to obtain the coded bitstream of each sub-block, and to combine the coded bitstreams of the sub-blocks to obtain the coded bitstream of each group of reordered Demura compensation data in the target AMOLED display panel.

[0141] The decoding module 106 is used to read the encoded bitstream of each group of reordered Demura compensation data in the target AMOLED display panel and decode it in the reverse process of encoding to obtain the reconstructed Demura compensation data. The reconstructed Demura compensation data is used to perform grayscale data compensation on each pixel position of the target AMOLED display panel.

[0142] Specifically, the processing module 104 is used to calculate the difference between the actual compensation value and the predicted pixel compensation value corresponding to each pixel position in each sub-block, so as to obtain the prediction residual data of each sub-block; to perform discrete cosine transform on the prediction residual data of each sub-block to obtain the frequency domain transform coefficients of each sub-block; and to quantize the frequency domain transform coefficients of each sub-block to obtain the frequency domain prediction residual transform coefficients of each sub-block.

[0143] The aforementioned processing module 104 includes:

[0144] The solution submodule is used to calculate the difference between the actual compensation value and the predicted pixel compensation value for each pixel position in each subblock, so as to obtain the prediction residual data for each subblock.

[0145] The transformation submodule is used to perform discrete cosine transform on the prediction residual data of each sub-block to obtain the frequency domain transform coefficients of each sub-block.

[0146] The quantization submodule is used to quantize the frequency domain transform coefficients of each sub-block to obtain the frequency domain prediction residual transform coefficients of each sub-block.

[0147] Specifically, the decoding module 106 is used to read the encoded bitstream of each group of reordered Demura compensation data in the target AMOLED display panel; perform entropy decoding on the frequency domain prediction residual change coefficients of each sub-block to obtain the frequency domain prediction residual transformation coefficients; perform inverse quantization on the prediction error frequency domain transformation coefficients to obtain the frequency domain transformation coefficients of each sub-block; perform inverse discrete cosine transform on the frequency domain transformation coefficients of each sub-block to obtain the prediction residual data of each sub-block; and reconstruct the compensation data of each sub-block based on each prediction residual data and the corresponding prediction mode to obtain the reconstructed Demura compensation data.

[0148] The decoding module 106 includes:

[0149] The reading submodule is used to read the encoded bitstream of each group of reordered Demura compensation data in the target AMOLED display panel;

[0150] The entropy decoding submodule is used to perform entropy decoding on the frequency domain prediction residual transformation coefficients of each sub-block to obtain the frequency domain prediction residual transformation coefficients.

[0151] The dequantization submodule is used to dequantize the frequency domain transform coefficients of the prediction error to obtain the frequency domain transform coefficients of each sub-block.

[0152] The inverse transform submodule is used to perform discrete cosine inverse transform on the frequency domain transform coefficients of each sub-block to obtain the prediction residual data of each sub-block.

[0153] The reconstruction submodule is used to reconstruct the compensation data of each sub-block based on each prediction residual data and the corresponding prediction mode, so as to obtain the reconstructed Demura compensation data.

[0154] This invention also provides a terminal device, such as... Figure 5 As shown, the terminal device D10 of this embodiment includes: at least one processor D100 ( Figure 5 The diagram shows only one processor, a memory D101, and a computer program D102 stored in the memory D101 and executable on the at least one processor D100. When the processor D100 executes the computer program D102, it implements a method for encoding and decoding Demura compensation data. Alternatively, when the processor D100 executes the computer program D102, it implements the functions of each module / unit in the above-described device embodiments.

[0155] The terminal device D10 can be a desktop computer, laptop, handheld computer, server, server cluster, or cloud server, etc. This terminal device may include, but is not limited to, a processor D100 and a memory D101. Those skilled in the art will understand that... Figure 5 This is merely an example of terminal device D10 and does not constitute a limitation on terminal device D10. It may include more or fewer components than shown in the figure, or combine certain components, or different components, such as input / output devices, network access devices, etc.

[0156] The processor D100 can be a central processing unit (CPU), but it can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0157] In some embodiments, the memory D101 may be an internal storage unit of the terminal device D10, such as a hard disk or memory of the terminal device D10. In other embodiments, the memory D101 may be an external storage device of the terminal device D10, such as a plug-in hard disk, smart media card (SMC), secure digital card (SD), flash card, etc., equipped on the terminal device D10. Furthermore, the memory D101 may include both internal and external storage units of the terminal device D10. The memory D101 is used to store the operating system, applications, bootloader, data, and other programs, such as the program code of the computer program. The memory D101 can also be used to temporarily store data that has been output or will be output.

[0158] It should be noted that the information interaction and execution process between the above-mentioned devices / units are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.

[0159] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0160] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements a method for encoding and decoding Demura compensation data.

[0161] This application provides a computer program product that, when run on a mobile terminal, enables the mobile terminal to implement the steps described in the above-described method embodiments.

[0162] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying the computer program code to a building device / terminal device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electrical carrier signals or telecommunication signals.

[0163] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for encoding and decoding Demura compensation data, characterized in that, For use in AMOLED display panels, including: Step 1: By selecting the typical grayscale of the target AMOLED display panel, generate Demura compensation data for different color channels in the target AMOLED display panel in sequence. The number of Demura compensation data for each color channel is equal to the number of pixels in the target AMOLED display panel. Step 2: Reorder the Demura compensation data for each color channel to generate multiple sets of reordered Demura compensation data, and divide each set of reordered Demura compensation data into multiple sub-blocks. Step 3: Using each sub-block as an encoding unit, predict the compensation value of each pixel in each sub-block to obtain the prediction mode corresponding to each sub-block and obtain the predicted pixel compensation value of each pixel position in each sub-block. Step 4: For each sub-block, calculate the difference between the actual compensation value and the predicted pixel compensation value corresponding to each pixel position in the sub-block to obtain the prediction residual data of each sub-block. Then, transform and quantize the prediction residual data to obtain the frequency domain prediction residual transformation coefficients of each sub-block. Step 5: Based on the frequency domain prediction residual transform coefficients, entropy coding is performed on each sub-block to obtain the coded bitstream of each sub-block, and the coded bitstreams of the sub-blocks are combined to obtain the coded bitstream of each group of reordered Demura compensation data in the target AMOLED display panel. Step 6: Read the encoded bitstream of each group of reordered Demura compensation data in the target AMOLED display panel and decode it in the reverse process of encoding to obtain the reconstructed Demura compensation data. The reconstructed Demura compensation data is used to perform grayscale data compensation on each pixel position of the target AMOLED display panel.

2. The encoding and decoding method for Demura compensation data according to claim 1, characterized in that, Step 2 specifically includes: Based on the distribution of each pixel position in the AMOLED display panel, the Demura compensation data of each color channel is reordered row by row from left to right and from top to bottom to obtain multiple sets of reordered Demura compensation data. Each set of reordered Demura compensation data has a width of 16 and a height of W×H / 16, where W and H are the width and height of the original Demura compensation data, respectively. Each group of reordered Demura compensation data is divided into W×H / 256 sub-blocks.

3. The encoding and decoding method for Demura compensation data according to claim 2, characterized in that, The prediction models include 7 types, among which: The first prediction model is dst[1]=dst[2]=dst[3]=dst[4]=I; dst[5]=dst[6]=dst[7]=dst[8]=J; dst[9]=dst[10]=dst[11]=dst[12]=K; st[13]=dst[14]=dst[15]=dst[16]=L; The second prediction model is: dst[1]=dst[5]=dst[9]=dst[13]=A; dst[2]=dst[6]=dst[10]=dst[14]=B; dst[3]=dst[7]=dst[11]=dst[15]=C; dst[4]=dst[8]=dst[12]=dst[16]=D; The third prediction model is: dst[1,16]=A; The fourth prediction pattern is: dst[1,16]=B; The fifth prediction model is: dst[1,16]=C; The sixth prediction pattern is: dst[1,16]=I; The seventh prediction pattern is: dst[1,16]=J; Where dst[·] represents the predicted value of the current sub-block, and A, B, C, D, I, J, K, L all represent the reconstructed pixel values ​​of the upper and left sub-blocks adjacent to the current sub-block.

4. The encoding and decoding method for Demura compensation data according to claim 3, characterized in that, Step 4 includes: For each sub-block, the difference between the actual compensation value and the predicted pixel compensation value corresponding to each pixel position in the sub-block is calculated to obtain the prediction residual data for each sub-block; The frequency domain transform coefficients of each sub-block are obtained by performing discrete cosine transform on the prediction residual data of each sub-block. The frequency domain transform coefficients of each sub-block are quantized to obtain the frequency domain prediction residual transform coefficients of each sub-block.

5. The encoding and decoding method for Demura compensation data according to claim 4, characterized in that, The frequency domain transform coefficients T[u,v] of each sub-block are obtained by performing discrete cosine transform on the prediction residual data of each sub-block: Where [u,v] represents the frequency components in the horizontal and vertical directions in the corresponding transform domain, X represents the prediction residual data of the sub-block, [x,y] represents the position of the prediction residual data, and s represents the number of sub-blocks.

6. The encoding and decoding method for Demura compensation data according to claim 5, characterized in that, The frequency domain transform coefficients of each sub-block are quantized to obtain the frequency domain prediction residual transform coefficients Q[u,v] of each sub-block: Among them, Q step This represents the quantization step size, u = 1, 2, 3, 4, v = 1, 2, 3, 4.

7. The encoding and decoding method for Demura compensation data according to claim 6, characterized in that, Step 6 includes: Read the encoded bitstream of each group of reordered Demura compensation data in the target AMOLED display panel; Entropy decoding is performed on the frequency domain prediction residual transformation coefficients of each sub-block to obtain the frequency domain prediction residual transformation coefficients; The frequency domain prediction residual transform coefficients are dequantized to obtain the frequency domain transform coefficients of each sub-block. The frequency domain transform coefficients of each sub-block are subjected to inverse discrete cosine transform to obtain the prediction residual data of each sub-block; The compensation data for each sub-block is reconstructed based on each predicted residual data and the corresponding prediction mode to obtain the reconstructed Demura compensation data.

8. A Demura compensation data encoding and decoding apparatus, characterized in that, Applications in AMOLED display panels include: The generation module is used to sequentially generate Demura compensation data for different color channels in the target AMOLED display panel by selecting typical gray levels of the target AMOLED display panel. The number of Demura compensation data for each color channel is equal to the number of pixels in the target AMOLED display panel. The reordering module is used to reorder the Demura compensation data of each color channel separately, generate multiple sets of reordered Demura compensation data, and divide each set of reordered Demura compensation data into multiple sub-blocks. The prediction module is used to predict the compensation value of each pixel in each sub-block as the encoding unit, so as to obtain the prediction mode corresponding to each sub-block and obtain the predicted pixel compensation value of each pixel position in each sub-block. The processing module is used to calculate the difference between the actual compensation value and the predicted pixel compensation value corresponding to each pixel position in each sub-block for each sub-block, to obtain the prediction residual data of each sub-block, and to transform and quantize the prediction residual data to obtain the frequency domain prediction residual transformation coefficients of each sub-block. The combination module is used to entropy encode each sub-block based on the frequency domain prediction residual transform coefficients to obtain the coded bitstream of each sub-block, and to combine the coded bitstreams of the sub-blocks to obtain the coded bitstream of each group of reordered Demura compensation data in the target AMOLED display panel. The decoding module is used to read the encoded bitstream of each group of reordered Demura compensation data in the target AMOLED display panel and decode it in the reverse process of encoding to obtain the reconstructed Demura compensation data. The reconstructed Demura compensation data is used to perform grayscale data compensation on each pixel position of the target AMOLED display panel.

9. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the encoding and decoding method for Demura compensation data as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the encoding and decoding method for Demura compensation data as described in any one of claims 1 to 7.

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