Data processing method, data processing circuit and data processing device

Abstract

The application discloses a data processing method, a data processing circuit and a data processing device, which are used for adjusting the display brightness of a display screen in a display device. The data processing method comprises the following steps: obtaining stored variable-length binary coding data corresponding to a single sub-pixel; dividing the variable-length binary coding data according to frequency channels, and storing the variable-length coding data in multiple frequency channels; decoding the variable-length coding data stored in at least one frequency channel to obtain intermediate data; and performing an inverse transformation operation on the intermediate data to obtain sub-pixel brightness compensation data. According to the data processing method, the stored variable-length coding brightness compensation data is stored and decoded according to frequency channels, so that the decoded brightness compensation data can be obtained according to the data stored in at least one frequency channel. The required frequency channel is selected according to compensation requirements, and the compensation accuracy, the data storage amount and the complexity of the decoding operation are considered.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a data processing method, a data processing circuit, and a data processing device. Background Technology

[0002] During the production of OLED displays, due to factors such as materials and processes, some products may exhibit uneven brightness in the displayed image (mura, a transliteration from Japanese).

[0003] Currently, external compensation systems for OLED manufacturing processes eliminate horizontal lines on displays exhibiting mura phenomena using advanced sub-pixel-level optical imaging technology and software algorithms. This requires not only hardware implementation of the corresponding algorithms but also storage of brightness compensation data in memory. However, brightness compensation data is typically large and must be compressed.

[0004] Current methods for compressing brightness compensation data generally employ two approaches: lossless and lossy encoding. Lossless compression requires decoding before burning the data to memory, and the adjustment factors are all floating-point numbers, leading to precision loss and excessively long code tables, resulting in limited data compression ratios. Lossy compression, on the other hand, often adjusts based on transformations in the communication domain, forcibly removes some information, and then performs further compression using Huffman coding and run-length encoding. This method results in significant data loss after decoding, making it ineffective for pixel compensation. Therefore, current compression methods cannot adaptively adjust the compression ratio during both compression and decoding processes, consuming excessive hardware resources and severely limiting the applicability of brightness compensation methods and OLED products. Furthermore, current decoding methods for compressed data also suffer from large data decoding losses, high computational load, and large overall power consumption and area requirements, resulting in poor brightness compensation performance. Summary of the Invention

[0005] In view of the above problems, the purpose of this invention is to provide a data processing method, a data processing circuit, and a data processing device to solve the problems in the prior art.

[0006] According to one aspect of the present invention, a data processing method is provided for adjusting the display brightness of a display screen in a display device. The data processing method includes: acquiring stored variable-length binary encoded data corresponding to a single sub-pixel; dividing and storing the variable-length binary encoded data into multiple frequency channel variable-length encoded data according to frequency channels; decoding at least one frequency channel variable-length encoded data in the multiple frequency channel variable-length encoded data to obtain intermediate data; and performing an inverse transformation operation on the intermediate data to obtain sub-pixel brightness compensation data.

[0007] Optionally, the frequency channel includes one low-frequency channel and three high-frequency channels, and the at least one frequency channel includes the low-frequency channel.

[0008] Optionally, the data processing method further includes: processing the acquired sub-pixel brightness compensation data of the three-color sub-pixels to obtain actual brightness compensation data, and providing it to the display screen.

[0009] Optionally, the step of decoding the variable-length coded data stored in at least one frequency channel to obtain intermediate data includes: for each frequency channel, decoding the multiple data groups included in the variable-length coded data into multiple quantization codes according to a preset rule to obtain a set of quantization code combination data; performing a dequantization operation on the quantization code combination data to obtain a quantization value; and performing a data prediction operation on the quantization value of the low-frequency channel separately to obtain the intermediate data.

[0010] Optionally, each data group includes a binary flag code and a quantization code, wherein the quantization code corresponds one-to-one with the quantization value, the flag code represents the grouping of the quantization value, and the number of bits of all the flag codes and the number of bits of all the quantization codes are not completely the same. The preset rule includes the correspondence between the number of bits of each flag code and each data group.

[0011] Optionally, the step of decoding the multiple data groups included in the variable-length encoded data into multiple quantization codes according to a preset rule for each frequency channel to obtain a set of quantization code combination data includes: obtaining the stored preset rule; reading the flag code for each data group according to the preset rule; and obtaining the quantization code of the corresponding data group according to the flag code and the number of bits of the data group.

[0012] Optionally, the step of performing data prediction operation on the quantized value includes: updating the current quantized value according to the previous quantized value located in the same row as the current quantized value, and / or updating the current quantized value according to the previous quantized value located in the same column as the current quantized value.

[0013] Optionally, the step of performing an inverse transformation operation on the intermediate data to obtain sub-pixel brightness compensation data includes: performing a first inverse transformation operation on the intermediate data to obtain first sub-pixel brightness compensation data, and performing brightness compensation on an odd-numbered row of the pixel unit of the display screen; and extracting the intermediate data stored in the row buffer and performing a second inverse transformation operation to obtain second sub-pixel brightness compensation data, and performing brightness compensation on an even-numbered row of the pixel unit of the display screen, wherein the odd-numbered row and the even-numbered row are adjacent.

[0014] Optionally, before obtaining the stored variable-length binary encoded data corresponding to a single sub-pixel, the method further includes: encoding the brightness compensation data into the variable-length binary encoded data, wherein the step of encoding the brightness compensation data into the variable-length binary encoded data includes: downsampling the brightness compensation data to obtain sub-pixel brightness compensation data corresponding to the three color sub-pixels respectively; performing discrete wavelet transform on the sub-pixel brightness compensation data corresponding to each sub-pixel to obtain multiple transformed data divided according to frequency; combining the transformed data belonging to the same frequency to form intermediate data for multiple frequency channels; performing data prediction and quantization operations on the intermediate data for each frequency channel to obtain a set of quantized encoded combination data; setting a flag code for each quantization code in each set of quantized encoded combination data to obtain a data group, and then arranging the multiple data groups according to the encoding factor to obtain a set of variable-length encoded data; and arranging and combining the variable-length encoded data of multiple frequency channels to obtain the variable-length binary encoded data corresponding to each sub-pixel, and storing it as a binary document.

[0015] Optionally, the discrete wavelet transform includes a binary wavelet transform, and the variable-length binary encoded data is stored in the form of a lookup table.

[0016] Optionally, the step of setting a flag code for each quantization code in each group of quantization code combination data to obtain a data group, and then arranging multiple data groups according to the coding factor to obtain a set of variable-length coded data includes: dividing a group of quantization code combination data into multiple groups, each group containing a different number of quantization codes; setting a flag code for each group, the multiple flag codes having different bit lengths; combining each quantization code with the flag code of the corresponding group to form a data group; arranging multiple data groups according to the coding factor to obtain a set of variable-length coded data, wherein the coding factor includes a compression factor.

[0017] According to another aspect of the present invention, a data processing circuit is provided for decoding variable-length binary encoded data for adjusting the display brightness of a display screen in a display device. The data processing circuit includes at least one decoding unit, wherein each decoding unit includes: multiple data channels for dividing and storing the variable-length binary encoded data obtained from a memory into multiple frequency channels of variable-length encoded data, and decoding the variable-length encoded data to obtain intermediate data; and an inverse transformer connected to the multiple data channels for performing an inverse transformation operation on the intermediate data to obtain sub-pixel brightness compensation data for a single sub-pixel. The data channels and the frequency channels correspond one-to-one, each data channel includes a first-in-first-out (FIFO) memory and a decoder, the multiple FIFO memories respectively store the variable-length encoded data of multiple frequency channels, and the decoder performs the decoding operation on the variable-length encoded data.

[0018] Optionally, each data channel further includes: a register connected between the first-in-first-out memory and the decoder, which transmits the variable-length encoded data to the decoder and counts the number of effective bits of the variable-length encoded data stored therein, and when the number of effective bits is less than a unit value, reads a unit value of the variable-length encoded data from the first-in-first-out memory, wherein a unit value is 96 bits.

[0019] Optionally, the frequency channel includes one low-frequency channel and three high-frequency channels, and the inverter obtains the intermediate data from at least the data channel corresponding to the low-frequency channel.

[0020] Optionally, the data storage depth of the first-in-first-out memory of the data channel corresponding to the low-frequency channel is 12*96 bits, and the data storage depth of the first-in-first-out memory of the data channel corresponding to the three high-frequency channels is 8*96 bits.

[0021] Optionally, the decoder includes: an entropy decoding unit, which decodes multiple data groups included in the variable-length encoded data into multiple quantization codes according to a preset rule for each frequency channel, to obtain a set of quantization code combination data; and a quantization unit, connected to the entropy decoding unit, which performs a dequantization operation on the quantization code combination data to obtain a quantization value, thereby obtaining intermediate data.

[0022] Optionally, the decoder within the data channel containing the low-frequency channel further includes: a prediction unit connected to the quantization unit, which performs a data prediction operation on the quantization value of the low-frequency channel to obtain the intermediate data.

[0023] Optionally, each data group includes a binary flag code and a quantization code, wherein the quantization code corresponds one-to-one with the quantization value, the flag code represents the grouping of the quantization value, the number of bits of all flag codes and the number of bits of all quantization codes are not exactly the same, and the preset rule is stored in the memory, the preset rule including the correspondence between the number of bits of each flag code and each data group.

[0024] Optionally, the data processing circuit includes multiple decoding units, each decoding unit outputting a sub-pixel brightness compensation data, and the multiple sub-pixel brightness compensation data output by the multiple decoding units are different types of compensation data provided to the same area of ​​the pixel unit of the display screen.

[0025] Optionally, the data processing circuit further includes: a row buffer connected to the decoder and the inverse transformer, which stores the intermediate data and transmits the intermediate data to the inverse transformer. The intermediate data is directly subjected to a first inverse transformation operation by the inverse transformer to obtain first sub-pixel brightness compensation data, which is used to compensate the brightness of an odd-numbered row of the pixel unit of the display screen. The intermediate data extracted from the row buffer is subjected to a second inverse transformation operation by the inverse transformer to obtain second sub-pixel brightness compensation data, which is used to compensate the brightness of an even-numbered row of the pixel unit of the display screen. The odd-numbered row and the even-numbered row are adjacent to each other.

[0026] Optionally, the data processing circuit further includes: a compensation circuit, which acquires the brightness compensation data of the sub-pixels corresponding to the three color sub-pixels respectively, processes the brightness compensation data of the sub-pixels to obtain actual brightness compensation data, and provides it to the display screen.

[0027] According to another aspect of the present invention, a data processing apparatus is provided, comprising: the data processing circuit described above; a cache unit for storing the variable-length binary encoded data; and a controller connected between the cache unit and the data processing circuit for reading the variable-length binary encoded data from the cache unit and allocating it to each data channel.

[0028] Optionally, the variable-length binary encoded data is stored in the cache unit in the form of a lookup table, and the variable-length binary encoded data corresponding to each lookup table is transmitted by the controller to a corresponding decoding unit.

[0029] Optionally, the data processing device further includes a memory connected to the cache unit for storing all the variable-length binary encoded data and preset rules corresponding to the three-color sub-pixels, wherein the memory includes a flash memory.

[0030] Optionally, the data processing circuit is located inside the driver chip of the display screen, while the cache unit and the controller are located outside the driver chip.

[0031] The data processing method, circuit, and apparatus provided in this application first store variable-length binary encoded data obtained using VLC (Variable Length Coding). During the encoding process, different encoding lengths can be used based on the frequency of data occurrence, resulting in smaller data size, easier encoding, and reduced storage device area. During decoding, encoded data and decoding can be performed separately according to frequency channels. Decoding using encoded data from at least one frequency channel yields the actual brightness compensation data, simplifying the computational workload and operations. Decoding and using the encoded data from the frequency channel with the most stored information significantly reduces the size of the compensation data, decreases space requirements, improves response speed, and lowers power consumption. When higher compensation accuracy is needed, encoded data from multiple frequency channels can be decoded. By selecting appropriate frequency channels, both compensation accuracy and power consumption can be balanced, improving the product's applicability.

[0032] Furthermore, discrete wavelet transform is used to obtain data from multiple frequency channels. The low-frequency channel data is an approximation of the original data, preserving its most basic and intuitive features, while the three high-frequency channels retain the detailed information of the original data. Therefore, the final sub-pixel brightness compensation data can be obtained by decoding only the encoded data from the low-frequency channels, resulting in high compensation accuracy, low power consumption, and fast response. Moreover, the brightness compensation effect can be further improved by using the high-frequency channel data, achieving graded brightness compensation.

[0033] Furthermore, during the encoding process, a quantization code is generated for each quantization value. These quantization codes are then grouped, and a flag code is assigned to each group. The flag code and the quantization code are combined into a data group. During decoding, the relationship between the flag code and the data group length can be determined according to preset rules, thus obtaining the quantization code. Finally, the data is processed back to its quantized value, restoring the data before encoding. The entire encoding and decoding process is simple. The flag code allows for easy parsing of the quantized value, improving data processing speed and ensuring high data fidelity.

[0034] Furthermore, the encoding, quantization, and transformation operations used in the encoding process can correspond one-to-one with the entropy decoding, dequantization, and inverse transformation operations in the decoding process, realizing completely reversible changes in data, effectively improving data accuracy, greatly increasing the data compression ratio, and enhancing the reliability of compensation operations.

[0035] Furthermore, different compensation methods can be used for different areas of the screen. Specifically, the intermediate data of odd-numbered rows can be buffered by using a row buffer, and the brightness compensation data of even-numbered rows can be obtained by direct inverse transformation based on the intermediate data. This reduces the computational load of decoding even-numbered row data without affecting the compensation accuracy, and reduces power consumption and cost. Attached Figure Description

[0036] The above and other objects, features and advantages of the present invention will become more apparent from the following description of embodiments of the invention with reference to the accompanying drawings, in which:

[0037] Figure 1 A flowchart illustrating the encoding of brightness compensation data into variable-length binary encoded data in a data processing method according to an embodiment of the present invention is shown.

[0038] Figure 2 It shows Figure 1 A schematic diagram illustrating the process of data transformation and arrangement in China;

[0039] Figure 3 A schematic diagram illustrating the matching of flag encoding and quantization encoding during the data encoding and decoding process in the data processing method according to an embodiment of the present invention is shown.

[0040] Figure 4 A flowchart of a data processing method according to an embodiment of the present invention is shown;

[0041] Figure 5 It shows Figure 4 The detailed flowchart of step S203;

[0042] Figure 6 A schematic diagram of the data prediction process in the data processing method according to an embodiment of the present invention is shown;

[0043] Figure 7 A schematic diagram of the data inverse transformation process in the data processing method according to an embodiment of the present invention is shown;

[0044] Figure 8 A schematic block diagram of a data processing apparatus and a data processing circuit according to a first embodiment of the present invention is shown;

[0045] Figure 9 A schematic block diagram of a data processing circuit according to a second embodiment of the present invention is shown. Detailed Implementation

[0046] The invention will now be described in more detail with reference to the accompanying drawings. In the various drawings, the same elements are indicated by similar reference numerals. For clarity, the various parts in the drawings are not drawn to scale. Furthermore, some well-known parts may not be shown.

[0047] The present invention is described below based on embodiments, but the invention is not limited to these embodiments. In the detailed description of the invention below, certain specific details are described in detail. Those skilled in the art will fully understand the invention even without these details. To avoid obscuring the essence of the invention, well-known methods, processes, flows, elements, and circuits are not described in detail.

[0048] Unless the context explicitly requires it, the terms "comprising," "including," and similar terms throughout the specification and claims should be interpreted as encompassing rather than exclusive or exhaustive; that is, meaning "including but not limited to." In the description of this invention, it should be understood that terms such as "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance. Furthermore, in the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0049] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples.

[0050] This invention proposes a data processing method, primarily involving the compression, storage, and decoding of brightness compensation data for removing the mura phenomenon in OLED screens. During the encoding of the brightness compensation data, VLC encoding is used to perform discrete wavelet transform on the brightness compensation data of the three-color sub-pixels, reorganizing and transforming it to obtain data for four frequency channels (LL / LH / HL / HH). Then, a binary document is generated based on the compression factor and channel address data. In the decoding process of the OLED screen's driver chip, the stored encoded binary document is first retrieved, then the data for the four frequency channels is retrieved through a first-in-first-out memory, and finally, the actual brightness compensation data for the three-color sub-pixels is obtained through a decoder. The VLC encoding and decoding method effectively reduces the size of the compensation data, decreases the storage space and memory area required, improves the accuracy of the compensation data, reduces data transmission processes and computational load, and significantly reduces power consumption. The following is combined with the appendix... Figure 1-7 A detailed introduction will be provided.

[0051] Figure 1 A flowchart illustrating the encoding of brightness compensation data into variable-length binary encoded data in a data processing method according to an embodiment of the present invention is shown. Figure 1 As shown, the data processing method in this embodiment includes: encoding brightness compensation data into variable-length binary encoded data, specifically including steps S101-S106.

[0052] In step S101, the brightness compensation data is downsampled to obtain the brightness compensation data for each of the three color sub-pixels. In this step, a common data downsampling method is used to obtain the brightness compensation data for each of the R, G, and B color sub-pixels. Subsequent steps process the brightness compensation data for each of the three color sub-pixels.

[0053] In step S102, discrete wavelet transform is performed on the sub-pixel brightness compensation data corresponding to each sub-pixel to obtain multiple transformed data divided according to frequency. In this step, discrete wavelet transform is used to process the sub-pixel brightness compensation data, and the scale and translation of the basic wavelet are discretized. In image processing, binary wavelets are often used as the discrete wavelet transform function. After this transformation, transformed data of four frequency channels (LL, LH, HH, and HL) divided according to frequency (high frequency H and low frequency L) are obtained.

[0054] In step S103, conversion data belonging to the same frequency are combined together to form intermediate data with multiple frequency channels. For each color sub-pixel, multiple sets of four-frequency channel data can be obtained. Then, the conversion data of the four frequency channels are combined according to the frequency channels to obtain intermediate data.

[0055] Figure 2 It shows Figure 1 A schematic diagram illustrating the process of data transformation and arrangement. (Example) Figure 2 As shown, wavelet transform is first used to decompose the input data R into sub-data blocks of different frequencies (LL, LH, HH, and HL), converting them into spatial distribution information. The low-frequency sub-data block LL is an approximation of the original data, being the closest to it and retaining the basic information and most of the important data. The high-frequency sub-data blocks in the three directions reflect the detailed information of the original data. Therefore, in step S102, the sub-pixel brightness compensation data of each sub-pixel is converted into transformed data for four frequency channels: LL / LH / HL / HH. The LL channel stores the most compensation information. Then, the multiple transformed data are arranged and combined according to their respective frequency channels to obtain intermediate data for the four frequency channels.

[0056] See next Figure 1In step S104, data prediction and quantization operations are performed on the intermediate data of each frequency channel to obtain a set of quantized code combination data. In this step, both data prediction and quantization process the intermediate data of sub-pixels of the same color. Both prediction and quantization perform various calculations on the data according to corresponding formulas. For example, prediction changes the numerical value of the data, while quantization converts the positive or negative value of the data. After this step, each data is processed into a quantized code, which is, for example, binary data. Therefore, each frequency channel contains multiple quantized codes, that is, each frequency channel obtains a set of quantized value combination data.

[0057] In step S105, a flag code is set for each quantization code in each group of quantized code combination data to obtain a data group. Then, multiple data groups are arranged according to the coding factor to obtain a set of variable-length coded data. In this step, encoding is performed using VLC encoding. A flag code is set for each quantization code to obtain a data group, and then multiple data groups are arranged in a certain order.

[0058] This step specifically includes: dividing a set of quantized coded data into multiple groups, each group containing a different number of quantized codes; assigning a flag code to each group, with the number of bits in the flag codes varying; combining each quantized code with the flag code of its corresponding group to form a data group; arranging the multiple data groups according to the coding factor to obtain a set of variable-length coded data, where the coding factor includes a compression factor. See details... Figure 3 .

[0059] Figure 3 A schematic diagram illustrating the matching of flag encoding and quantization encoding during the data encoding and decoding process in the data processing method according to an embodiment of the present invention is shown.

[0060] like Figure 3 As shown, there is a one-to-one correspondence between quantization values ​​and quantization codes. A quantization value is, for example, any value between -128 and 127. A quantization code is binary data obtained after conversion; for example, a negative sign is represented by 0, and a positive sign by 1. Then, all quantization codes (or quantization values) for a frequency channel are grouped according to their numerical values. The number of quantization codes contained in each group is not entirely the same. For example, using... Figure 3The example divides the data into 5 groups, each containing a different amount of data. The same flag code is assigned to the quantization code within the same group, but each group has a different flag code, and the length of the flag code can also vary. Then, each quantization code and its corresponding flag code are combined one by one to form a data group. Afterwards, multiple data groups are arranged in a certain order to form variable-length encoded data. When combining data groups, the flag code can come first, followed by the quantization code, and the total length or number of bits in each data group can not be exactly the same, achieving the effect of variable-length encoding.

[0061] Furthermore, the frequency and position of different quantization codes can vary. By setting certain quantization codes to appear frequently and others infrequently, shorter flag codes can be used for frequently occurring quantization codes, while longer flag codes can be used for infrequently occurring quantization codes. This allows for adjusting the overall length of the encoded data as needed. For example, different positions and frequencies of quantization codes can be set based on encoding factors, such as compression factors and scaling factors, to arrange and compress multiple data groups. Shorter flag codes can also be set for groups containing a large number of quantization codes, allowing for adjustment of the overall encoded data length based on actual requirements. When users require faster response times, less storage space, and lower power consumption, the frequency of data with smaller quantization values ​​can be set higher, resulting in shorter data group lengths, shorter overall encoded data length, and less storage space usage. Conversely, when users require high compensation accuracy and good display effects, the frequency of data with larger quantization values ​​can be set higher, ensuring that each row of pixel units on the display receives high-precision compensation data.

[0062] After the above encoding process, data storage is simple and decoding is easy. During decoding, the initial data is checked to see if a flag code has been acquired and to analyze which group the acquired flag code belongs to. Then, according to preset rules, the total length of the data group corresponding to that flag code is found, and the corresponding quantization code is read and parsed. For example, if data 10 is acquired, corresponding to the second group (number 1), based on the total number of bits in the data group (3 bits), one more bit of data is taken to obtain the quantization code for decoding. If 1110 is acquired, then 3 more bits of data are taken for decoding. The encoding and decoding processes are completely reversible, improving the reliability of data transmission and increasing data decoding accuracy.

[0063] As can be seen, the data from all four frequency channels can be encoded using the method described above to obtain variable-length encoded data for all four channels.

[0064] See also Figure 1In step S106, the variable-length encoded data of multiple frequency channels are arranged and combined to obtain variable-length binary encoded data corresponding to each sub-pixel, which is then stored as a binary document. In this step, the data of the four frequency channels are combined according to storage address or other rules, such as HL, HH, LL, LH or LL, LH, HL, HH, or other orders. The variable-length binary encoded data corresponding to each sub-pixel is obtained and stored as a binary document. The encoded data is stored in the form of a LUT (Look-Up Table). The binary document can also store QT (compression factor) or scaling factor, data storage address, and checksum values ​​such as chksum.

[0065] Of course, the brightness compensation data for other sub-pixels is compressed and stored in the same way, also generating a binary document. During decoding, the data from the binary document is read separately for each sub-pixel and then decoded.

[0066] Figure 4 A flowchart of a data processing method according to an embodiment of the present invention is shown.

[0067] After Figure 1 Following the data encoding process of the embodiment, the data processing method of this embodiment further includes a data decoding process, specifically including steps S201-S205. For example... Figure 4 As shown:

[0068] In step S201, the variable-length binary encoded data corresponding to each stored sub-pixel is obtained. For example, the variable-length binary encoded data corresponding to each sub-pixel is obtained sequentially in the order of R, G, B, and then decoded accordingly.

[0069] In step S202, the variable-length binary encoded data is divided and stored as variable-length encoded data for multiple frequency channels according to the frequency channels. In this step, the acquired variable-length binary encoded data of the monochrome sub-pixels is divided and stored according to the frequency channels, resulting in four channels of variable-length encoded data. The frequency channels include one low-frequency channel and three high-frequency channels.

[0070] In step S203, intermediate data is obtained by decoding at least one variable-length coded data of multiple frequency channels. In this step, intermediate data is obtained by decoding the variable-length coded data of at least one frequency channel. This at least one frequency channel includes a low-frequency channel; except for the LL frequency channel, the other three frequency channels LH / HL / HH can be turned off. That is, intermediate data can be obtained by decoding only the data of the low-frequency channel LL, or by decoding the data of the low-frequency channel LL and any one to three other channels.

[0071] Figure 5 It shows Figure 4 The detailed flowchart of step S203 is shown below. Figure 5 As shown, this step specifically includes steps S2031-S2033.

[0072] In step S2031, for each frequency channel, the variable-length coded data, comprising multiple data groups, is decoded into multiple quantization codes according to a preset rule, resulting in a set of quantized code combination data. In this step, each data group includes a binary flag code and a quantization code. The quantization code corresponds one-to-one with the quantization value, and the flag code represents the grouping of quantization values. Furthermore, the bit length of all flag codes and all quantization codes is not identical. The preset rule includes the correspondence between the bit length of each flag code and each data group. According to... Figure 3 The decoding method described herein obtains the quantization encoding value of each data group, resulting in a set of quantized encoding combination data. Specific steps include: acquiring the stored preset rules; for each data group, reading the flag encoding according to the preset rules; and obtaining the quantization encoding of the corresponding data group based on the flag encoding and the number of bits in the data group.

[0073] In this embodiment, during the encoding process, a quantization code is generated based on each quantization value. These quantization codes are then grouped, and a flag code is assigned to each group. The flag code and the quantization code are combined into a data group. During decoding, the relationship between the flag code and the data group length can be obtained according to preset rules, thus yielding the quantization code. Finally, the data is processed back to its quantization value, restoring the data before encoding. The entire encoding and decoding process is simple. The flag code allows for easy parsing of the quantization value, improving data processing speed and ensuring high data fidelity.

[0074] In step S2032, the quantized encoded combined data is dequantized to obtain quantized values. In this step, for example, the Round function and QT coefficients are used to process the data of the selected frequency channel, converting the quantized code into the corresponding quantized values.

[0075] In step S2033, a data prediction operation is performed solely on the quantized values ​​of the low-frequency channel to obtain intermediate data. In this step, the data prediction operation can be performed only on the quantized values ​​of the low-frequency channel because the low-frequency channel stores the most compensation information. Through prediction, further compensation calculations can be performed on the data of the LL frequency channel, effectively improving data accuracy.

[0076] According to the data processing method of this embodiment, the series of operations such as encoding, quantization and transformation used in the encoding process can correspond one-to-one with the entropy decoding, dequantization and inverse transformation operations in the decoding process, so as to realize the complete reversible change of data, effectively improve data accuracy, greatly improve the data compression ratio, and improve the reliability of compensation operations.

[0077] See next Figure 4 In step S204, an inverse transform operation is performed on the intermediate data to obtain sub-pixel brightness compensation data. In this step, sub-pixel brightness compensation data can be obtained by inverse transforming only the data from the low-frequency channel, or by performing an inverse transform on data from multiple frequency channels, including the low-frequency channel. This inverse transform process is reversible with the discrete wavelet transform process.

[0078] In step S205, the acquired sub-pixel brightness compensation data of the three-color sub-pixels is processed to obtain actual brightness compensation data, which is then provided to the display screen. Sub-pixel brightness compensation data of other sub-pixels is acquired in the same manner, and the sub-pixel brightness compensation data of the three-color sub-pixels is processed through certain permutations and combinations to obtain actual brightness compensation data, which is then provided to the corresponding pixel unit of the display screen.

[0079] In this embodiment, the data processing method employs discrete wavelet transform to obtain data across multiple frequency channels. The low-frequency channel data approximates the original data, preserving its most basic and intuitive features, while the three high-frequency channels retain the detailed information of the original data. Therefore, the final sub-pixel brightness compensation data can be obtained by decoding only the encoded data from the low-frequency channels, resulting in high compensation accuracy, low power consumption, and fast response. Furthermore, the brightness compensation effect can be further improved by using the high-frequency channel data, achieving graded brightness compensation.

[0080] Figure 6 A schematic diagram of the data prediction process in the data processing method according to an embodiment of the present invention is shown.

[0081] In this embodiment, it can be based on Figure 5Step S2033 performs a prediction operation on the data. During the prediction operation, the current quantized value can be updated based on the previous quantized value located in the same row as the current quantized value, and / or based on the previous quantized value located in the same column as the current quantized value. For example... Figure 6 As shown, Mode A updates the current quantization value based on the previous quantization value in the same row as the current quantization value. For example, it might sum the current quantization value and the previous quantization value and take the average, or it might replace the current quantization value with the previous quantization value after some processing. Mode B updates the current quantization value based on the previous quantization value in the same column as the current quantization value. It can be done in a similar way to Mode A. Mode C is a combination of Modes A and B, updating the current quantization value based on both the previous and preceding quantization values. For example, it could be updating the current quantization value by summing the previous and preceding quantization values ​​and taking the average, or by combining the previous and preceding quantization values ​​in a certain proportion.

[0082] Figure 7 A schematic diagram of the data inverse transformation process in the data processing method according to an embodiment of the present invention is shown.

[0083] like Figure 7 As shown, the data from the four frequency channels are first processed mathematically. For example, after the first step, L0 = LL + LH, L1 = LL – LH, H0 = HL + HH, H1 = HL – HH, resulting in the data for L0, L1, H0, and H1. Then, the second step is executed: R0 = L0 + H0, R1 = L0 – H0, R2 = L1 + H1, R3 = L1 – H1, resulting in the data for R0, R1, R2, and R3. Finally, the third step determines whether the obtained data falls within a certain numerical range, for example, -128 to 127. R0 = max(-128, min(127, R0)), R1 = max(-128, min(127, R1)), R2 = max(-128, min(127, R2)), R3 = max(-128, min(127, R3)).

[0084] The inverse transformation described above is used to obtain the sub-pixel brightness compensation data of pixel R. The data processing methods for pixels G and B are the same. Through a series of operations, the actual brightness compensation data corresponding to each sub-pixel is obtained.

[0085] The data processing method provided by this invention first stores variable-length binary encoded data obtained using VLC (Variable Length Coding). During the encoding process, different encoding lengths can be used based on the frequency of data occurrence, resulting in smaller data size, easier encoding, and reduced storage device area. During decoding, encoded data and decoding can be performed separately according to frequency channels. Decoding using encoded data from at least one frequency channel yields the actual brightness compensation data, simplifying the computational workload and operations. Decoding and using the encoded data from the frequency channel with the most stored information significantly reduces the size of the compensation data, decreases space occupation, improves response speed, and lowers power consumption. When higher compensation accuracy is required, encoded data from multiple frequency channels can be decoded. By selecting appropriate frequency channels, both compensation accuracy and power consumption can be balanced, improving product applicability.

[0086] Furthermore, the data processing method also includes: performing a first inverse transformation operation on the intermediate data to obtain the first sub-pixel brightness compensation data, and performing brightness compensation on an odd-numbered row of the pixel unit of the display screen; and extracting the intermediate data stored in the row buffer to perform a second inverse transformation operation to obtain the second sub-pixel brightness compensation data, and performing brightness compensation on an even-numbered row of the pixel unit of the display screen, with the odd-numbered rows and even-numbered rows being adjacent.

[0087] When performing brightness compensation on the screen, different compensation methods can be used for different areas of the screen. For example, a set of sub-pixel brightness compensation data can be provided to only one row of the pixel unit, or a set of sub-pixel brightness compensation data can be provided to two rows. In this case, a row buffer can be used to buffer the intermediate data of the odd-numbered rows, and the brightness compensation data of the even-numbered rows can be obtained directly by inverse transformation based on the intermediate data. This reduces the computational load of decoding the even-numbered rows of data, does not affect the compensation accuracy, and reduces power consumption and cost.

[0088] Furthermore, the present invention also provides a corresponding data processing apparatus for executing the above-described data processing method, see details below. Figure 8 .

[0089] Figure 8 A schematic block diagram of a data processing apparatus and a data processing circuit according to a first embodiment of the present invention is shown.

[0090] like Figure 8As shown, a data processing apparatus 100 is provided for providing brightness compensation data to a display screen 200, such as an OLED display screen. The data processing apparatus 100 includes a memory 110, a cache unit 120, a controller 130, and a data processing circuit 140 connected in sequence. The cache unit 120 is, for example, an SRAM, which reads variable-length binary encoded data from the memory 110 and stores it in the form of a lookup table. The controller 130, also known as a read controller, is connected between the cache unit 120 and the data processing circuit 140, and reads variable-length binary encoded data from the cache unit 120 and allocates it to each data channel of the data processing circuit 140. The memory 110 is connected to the cache unit 120 and is used to store all variable-length binary encoded data corresponding to the three-color sub-pixels and preset rules; the memory 110 includes flash memory. The data processing circuit 140 is located, for example, inside the display screen's driver chip, while the cache unit 120 and the controller 130 are located outside the driver chip.

[0091] The data processing circuit 140 in this embodiment is mainly used to decode variable-length binary encoded data for adjusting the display brightness of the screen in the display device. The data processing circuit 140 includes at least one decoding unit 150 and a compensation circuit 180. Each decoding unit 150 includes multiple data channels 160 and an inverse converter 170. The data processing circuit 140 divides the variable-length binary encoded data obtained from the memory 110 according to frequency channels and stores it in multiple data channels 160, storing it as variable-length encoded data for multiple frequency channels. It then decodes the variable-length encoded data in each of its respective data channels 160 to obtain intermediate data. The inverse converter 170 is connected to the multiple data channels 160 and performs an inverse transformation operation on the intermediate data to obtain sub-pixel brightness compensation data for a single sub-pixel.

[0092] In this embodiment, data channel 160 and frequency channel correspond one-to-one, such as... Figure 8 Each decoding unit 150 shows four data channels, corresponding to the storage of data for the HH, HL, LH, and LL frequency channels, respectively. Each data channel 160 includes a first-in-first-out (FIFO) memory 161 and a decoder 163. Multiple FIFO memories 161 store variable-length encoded data for multiple frequency channels, while the decoder 163 performs decoding operations on the variable-length encoded data. The FIFO 161 is a FIFO (First Input First Output) memory. FIFO4 can be used to store data for the LL frequency channel. The data storage depth of the FIFO for the low-frequency channels is set to 12*96 bits, and the data storage depth of the FIFOs for the other three high-frequency channels is 8*96 bits. The FIFO continuously reads data stored in the corresponding SRAM 120 each time.

[0093] Each data channel 160 also includes a register 162, which is connected between the FIFO 161 and the decoder 163. Register 162 is used to transfer variable-length encoded data from the FIFO 161 to the decoder 163. Register 162 is also primarily used to count the number of valid bits of the stored variable-length encoded data. When the number of valid bits is less than a unit value, a unit value of variable-length encoded data is read from the FIFO 161, for example, 96 bits. In implementation, a 192-bit register can be used to buffer the data output from the FIFO and record the current number of valid data bits. When the number of valid data bits consumed by the decoder 163 is less than 96, the next data is read from the FIFO and added to the end of register 162.

[0094] In this embodiment, the frequency channels include one low-frequency channel and three high-frequency channels. The inverter 170 obtains intermediate data from at least the data channel 160 corresponding to the low-frequency channel. That is, except for the data channel corresponding to the LL frequency channel, the other data channels can be turned off to reduce the amount of data processing.

[0095] Furthermore, the decoder 163 may include an entropy decoding unit and a quantization unit. For each frequency channel, the entropy decoding unit decodes multiple data groups of variable-length encoded data into multiple quantization codes according to a preset rule, obtaining a set of quantized code combination data. The quantization unit, connected to the entropy decoding unit, performs dequantization on the quantized code combination data to obtain quantized values, thus obtaining intermediate data. Each data group includes a binary flag code and a quantization code. The quantization code corresponds one-to-one with the quantization value. The flag code represents the grouping of quantization values. The number of bits for all flag codes and all quantization codes are not completely identical, and the preset rules are stored in the memory 110, including the correspondence between the number of bits for each flag code and each data group. Of course, the decoder 163 within the data channel 160 containing the low-frequency channel also includes a prediction unit. The prediction unit, connected to the quantization unit, performs data prediction on the quantized values ​​of the low-frequency channel to obtain intermediate data.

[0096] The compensation circuit 180 is used to acquire the sub-pixel brightness compensation data corresponding to the three color sub-pixels respectively, and to process the sub-pixel brightness compensation data of the three color sub-pixels to obtain the actual brightness compensation data, which is then provided to the display screen 200.

[0097] Figure 9 A schematic block diagram of a data processing circuit according to a second embodiment of the present invention is shown.

[0098] like Figure 9As shown, the data processing circuit 240 may include multiple decoding units 250. For example, two decoding units 250 may be configured. The SRAM 220 can read data from multiple LUTs from the memory, for example, it also reads data from two LUTs. The variable-length binary encoded data corresponding to each lookup table is transmitted by the controller to the corresponding decoding unit, that is, each decoding unit 250 processes the data of one LUT. Each of the multiple decoding units 250 can output one sub-pixel brightness compensation data, and the multiple sub-pixel brightness compensation data output by the multiple decoding units 250 at the same time are different types of compensation data provided to the same area of ​​the pixel unit of the display screen. For example, offset0 and offset1 output by decoding units 250 and 350 are different types or different information of brightness compensation data provided to the same area of ​​the pixel unit. The compensation circuit 280 connects multiple decoding units, integrates and processes the data, and then provides it to the display screen.

[0099] For each decoding unit, such as decoding unit 250, its inverter 270 obtains intermediate data from at least the data channel corresponding to the low-frequency channel LL. Similarly, in decoding unit 350, all data channels except the data channel corresponding to LL can be turned off, and the inverter 370 obtains intermediate data from at least this open data channel. Turning off a data channel can be achieved by disconnecting data transmission between register 262 and decoder 263, or by disconnecting data transmission between FIFO 261 and register 262.

[0100] Furthermore, the data processing circuit 240 also includes a row buffer 290, which is connected to the decoder 263 (or 363) and the inverse transformer 270 (or 370). The row buffer 290 is used to store intermediate data and transmit the intermediate data to the inverse transformer 270 (or 370). Since VLC encoded data supports both 2*1 and 2*2 display screen partitioning modes, in the 2*2 mode, the row buffer 290 can be used to buffer compensation data for odd-numbered rows, while data for even-numbered rows is read and used, and the corresponding decoder is turned off. That is, the intermediate data directly undergoes a first inverse transformation operation through the inverse transformer 270 to obtain the first sub-pixel brightness compensation data, which is used to compensate the brightness of an odd-numbered row of the pixel unit of the display screen; while the intermediate data extracted from the row buffer 290 undergoes a second inverse transformation operation through the inverse transformer 270 to obtain the second sub-pixel brightness compensation data, which is used to compensate the brightness of an even-numbered row of the pixel unit of the display screen, with odd-numbered rows adjacent to even-numbered rows.

[0101] In summary, the data processing method, data processing circuit, and data processing device provided in this application first store variable-length binary encoded data obtained using VLC (Variable Length Coding). During the encoding process, different encoding lengths can be used based on the frequency of data occurrence, resulting in smaller data size, easier encoding, and reduced storage device area. During the decoding process, encoded data and decoding can be performed separately according to frequency channels. Decoding using encoded data from at least one frequency channel yields the actual brightness compensation data, simplifying the computational workload and operations. Decoding and using the encoded data from the frequency channel with the most stored information significantly reduces the size of the compensation data, decreases space occupation, improves response speed, and lowers power consumption. When higher compensation accuracy is required, encoded data from multiple frequency channels can be decoded. By selecting appropriate frequency channels, both compensation accuracy and power consumption can be balanced, improving the product's applicability.

[0102] Furthermore, discrete wavelet transform is used to obtain data from multiple frequency channels. The low-frequency channel data is an approximation of the original data, preserving its most basic and intuitive features, while the three high-frequency channels retain the detailed information of the original data. Therefore, the final sub-pixel brightness compensation data can be obtained by decoding only the encoded data from the low-frequency channels, resulting in high compensation accuracy, low power consumption, and fast response. Moreover, the brightness compensation effect can be further improved by using the high-frequency channel data, achieving graded brightness compensation.

[0103] Furthermore, during the encoding process, a quantization code is generated for each quantization value. These quantization codes are then grouped, and a flag code is assigned to each group. The flag code and the quantization code are combined into a data group. During decoding, the relationship between the flag code and the data group length can be determined according to preset rules, thus obtaining the quantization code. Finally, the data is processed back to its quantized value, restoring the data before encoding. The entire encoding and decoding process is simple. The flag code allows for easy parsing of the quantized value, improving data processing speed and ensuring high data fidelity.

[0104] Furthermore, the encoding, quantization, and transformation operations used in the encoding process can correspond one-to-one with the entropy decoding, dequantization, and inverse transformation operations in the decoding process, realizing completely reversible changes in data, effectively improving data accuracy, greatly increasing the data compression ratio, and enhancing the reliability of compensation operations.

[0105] Furthermore, different compensation methods can be used for different areas of the screen. Specifically, the intermediate data of odd-numbered rows can be buffered by using a row buffer, and the brightness compensation data of even-numbered rows can be obtained by direct inverse transformation based on the intermediate data. This reduces the computational load of decoding even-numbered row data without affecting the compensation accuracy, and reduces power consumption and cost.

[0106] As described above, these embodiments of the present invention do not exhaustively cover all details, nor do they limit the invention to the specific embodiments described. Clearly, many modifications and variations can be made based on the above description. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to effectively utilize the invention and its modifications. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A data processing method for adjusting the display brightness of a screen in a display device, the data processing method comprising: Retrieve the variable-length binary encoded data corresponding to a single stored sub-pixel; The variable-length binary encoded data is divided and stored into multiple frequency channels according to the frequency channels. The frequency channels include one low-frequency channel and three high-frequency channels. The low-frequency channel retains the basic information of the original data, and the three high-frequency channels reflect the detailed information of the original data. Intermediate data is obtained by decoding at least the variable-length coded data of the low-frequency channels from the variable-length coded data of the multiple frequency channels. as well as The intermediate data is subjected to an inverse transformation operation to obtain sub-pixel brightness compensation data.

2. The data processing method according to claim 1 further includes: The acquired three-color sub-pixel brightness compensation data is processed to obtain actual brightness compensation data, which is then provided to the display screen.

3. The data processing method according to claim 1, wherein, The step of decoding at least the variable-length coded data of the lower frequency channels from the variable-length coded data of the plurality of frequency channels to obtain intermediate data includes: For each frequency channel, the multiple data groups included in the variable-length coded data are decoded into multiple quantization codes according to a preset rule to obtain a set of quantization code combination data; The quantized encoded combination data is dequantized to obtain the quantized value; and The intermediate data is obtained by performing a data prediction operation on the quantization value of the low-frequency channel separately.

4. The data processing method according to claim 3, wherein, Each data group includes a binary flag code and a quantization code. The quantization code corresponds one-to-one with the quantization value. The flag code represents the grouping of the quantization value. The number of bits in all flag codes and the number of bits in all quantization codes are not exactly the same. The preset rule includes the correspondence between the number of bits in each flag code and each data group.

5. The data processing method according to claim 4, wherein, The step of decoding the multiple data groups included in the variable-length coded data into multiple quantized codes according to a preset rule for each frequency channel to obtain a set of quantized code combination data includes: Retrieve the preset rules for storage; For each data group, the flag code is read according to the preset rules; The quantization code of the corresponding data group is obtained based on the flag code and the number of bits in the data group.

6. The data processing method according to claim 3, wherein, The steps for performing data prediction on the quantized value include: The current quantization value is updated based on the previous quantization value located in the same row as the current quantization value, and / or based on the previous quantization value located in the same column as the current quantization value.

7. The data processing method according to claim 1, wherein, The steps of performing an inverse transformation operation on the intermediate data to obtain sub-pixel brightness compensation data include: Perform a first inverse transformation on the intermediate data to obtain the first sub-pixel brightness compensation data, and perform brightness compensation on an odd-numbered row of pixel units on the display screen; and The intermediate data stored in the row buffer is extracted and subjected to a second inverse transformation operation to obtain the second sub-pixel brightness compensation data. Brightness compensation is then performed on an even-numbered row of the pixel unit of the display screen. The odd-numbered rows and the even-numbered rows are adjacent to each other.

8. The data processing method according to claim 1, wherein, Before the step of acquiring the stored variable-length binary encoded data corresponding to a single sub-pixel, the method further includes: encoding the brightness compensation data into the variable-length binary encoded data. The step of encoding the brightness compensation data into the variable-length binary encoded data includes: The brightness compensation data is downsampled to obtain the brightness compensation data of the sub-pixels corresponding to the three colors; Discrete wavelet transform is performed on the brightness compensation data of each sub-pixel to obtain multiple transformed data divided according to frequency; The converted data belonging to the same frequency are combined together to form intermediate data for multiple frequency channels; For each frequency channel, the intermediate data is subjected to data prediction and quantization operations to obtain a set of quantized coded combination data; A flag code is assigned to each quantized code in each group of quantized code combination data to obtain a data group. Multiple data groups are then arranged according to a coding factor to obtain a set of variable-length coded data. The variable-length encoded data of multiple frequency channels are arranged and combined to obtain the variable-length binary encoded data corresponding to each sub-pixel, and stored as a binary document.

9. The data processing method according to claim 8, wherein, The discrete wavelet transform includes a binary wavelet transform, and the variable-length binary encoded data is stored in the form of a lookup table.

10. The data processing method according to claim 8, wherein, The steps of assigning a flag code to each quantized code in each group of quantized code combination data to obtain a data group, and then arranging multiple data groups according to the coding factor to obtain a set of variable-length coded data include: A set of quantized code combination data is divided into multiple groups, and the number of quantized codes contained in each group is not exactly the same; Each group is assigned a flag code, and the number of bits in the multiple flag codes is not exactly the same; Each quantization code is combined with the corresponding flag code to form a data group; Arrange multiple data groups according to the coding factor to obtain a set of variable-length coded data, wherein the coding factor includes a compression factor.

11. A data processing circuit for decoding variable-length binary encoded data used to adjust the display brightness of a display screen in a display device, the data processing circuit comprising at least one decoding unit, wherein, Each of the decoding units includes: Multiple data channels divide and store the variable-length binary encoded data retrieved from the memory into multiple frequency-channel variable-length encoded data, and decode the variable-length encoded data to obtain intermediate data; and An inverse transformer, connected to the multiple data channels, performs an inverse transformation operation on the intermediate data to obtain sub-pixel brightness compensation data for individual sub-pixels. The data channels and frequency channels correspond one-to-one. Each data channel includes a first-in-first-out (FIFO) memory and a decoder. The multiple FIFO memories store variable-length coded data for multiple frequency channels respectively. The decoder performs decoding operations on the variable-length coded data. The frequency channels include one low-frequency channel and three high-frequency channels. The low-frequency channel retains the basic information of the original data, while the three high-frequency channels reflect the detailed information of the original data. The inverter obtains the intermediate data from at least the data channel corresponding to the low-frequency channel.

12. The data processing circuit according to claim 11, wherein, Each data channel also includes: A register, connected between the first-in-first-out memory and the decoder, transmits the variable-length encoded data to the decoder and counts the number of valid bits of the variable-length encoded data stored therein. When the number of valid bits is less than one unit value, it reads one unit value of the variable-length encoded data from the first-in-first-out memory, where one unit value is 96 bits.

13. The data processing circuit according to claim 11, wherein, The data storage depth of the FIFO memory for the data channel corresponding to the low-frequency channel is 12*96 bits, and the data storage depth of the FIFO memory for the data channel corresponding to the three high-frequency channels is 8*96 bits.

14. The data processing circuit according to claim 11, wherein, The decoder includes: The entropy decoding unit, for each frequency channel, decodes multiple data groups comprising the variable-length encoded data into multiple quantized codes according to a preset rule, obtaining a set of quantized code combination data; and The quantization unit, connected to the entropy decoding unit, performs a dequantization operation on the quantized encoded combined data to obtain quantized values ​​and intermediate data.

15. The data processing circuit according to claim 14, wherein, The decoder within the data channel containing the low-frequency channel further includes: The prediction unit, connected to the quantization unit, performs a data prediction operation on the quantization value of the low-frequency channel to obtain the intermediate data.

16. The data processing circuit according to claim 14, wherein, Each data group includes a binary flag code and a quantization code. The quantization code corresponds one-to-one with the quantization value. The flag code represents the grouping of the quantization value. The number of bits of all flag codes and the number of bits of all quantization codes are not exactly the same. The preset rule is stored in the memory. The preset rule includes the correspondence between the number of bits of each flag code and each data group.

17. The data processing circuit according to claim 11, wherein, The data processing circuit includes multiple decoding units, each of which outputs a sub-pixel brightness compensation data. The multiple sub-pixel brightness compensation data output by the multiple decoding units are different types of compensation data provided to the same area of ​​the pixel unit of the display screen.

18. The data processing circuit according to claim 11, further comprising: A line buffer, connected to the decoder and the inverse transformer, stores the intermediate data and transmits the intermediate data to the inverse transformer. Furthermore, the intermediate data is directly passed through the inverse transformer for the first inverse transformation operation to obtain the first sub-pixel brightness compensation data, so as to perform brightness compensation on an odd-numbered row of the pixel unit of the display screen; while the intermediate data extracted from the row buffer is passed through the inverse transformer for the second inverse transformation operation to obtain the second sub-pixel brightness compensation data, so as to perform brightness compensation on an even-numbered row of the pixel unit of the display screen, wherein the odd-numbered row and the even-numbered row are adjacent.

19. The data processing circuit according to claim 11, further comprising: The compensation circuit acquires the brightness compensation data of the sub-pixels corresponding to the three-color sub-pixels respectively, processes the brightness compensation data of the sub-pixels to obtain the actual brightness compensation data, and provides it to the display screen.

20. A data processing apparatus, comprising: The data processing circuit according to any one of claims 11-19; A cache unit stores the variable-length binary encoded data; as well as A controller, connected between the cache unit and the data processing circuit, reads the variable-length binary encoded data from the cache unit and distributes it to each data channel.

21. The data processing apparatus according to claim 20, wherein, The variable-length binary encoded data is stored in the cache unit in the form of a lookup table, and the variable-length binary encoded data corresponding to each lookup table is transmitted by the controller to a corresponding decoding unit.

22. The data processing apparatus according to claim 20, further comprising: A memory, connected to the cache unit, is used to store all the variable-length binary encoded data and preset rules corresponding to the three-color sub-pixels, and the memory includes a flash memory.

23. The data processing apparatus according to claim 20, wherein, The data processing circuit is located inside the driver chip of the display screen, while the cache unit and the controller are located outside the driver chip.

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