Abstract: Disclosed are parallel encoding and decoding method and apparatus, a computer device, a storage medium, and a computer program product. The method includes: acquiring a synchronization node corresponding to a codec core, and transmitting a frame synchronization detection request to the synchronization node based on a frame to be encoded and decoded; acquiring a frame synchronization result corresponding to the frame synchronization detection request; and determining a encoding and decoding mode for the frame to be encoded and decoded based on the frame synchronization result, and encoding and decoding the frame to be encoded and decoded based on the encoding and decoding mode. By using the method, a plurality of codec cores can be employed to code and decode different frames in the same video in parallel, thereby improving the frame rate.

Abstract: A method for compressing Demura compensation value including: acquiring original compensation values of a target panel; inputting the original compensation values into a spatial domain sampling model, performing a down-sampling to obtain spatial domain sampling values, inputting the original compensation values into a prediction mode overall model, and performing a numerical processing to obtain a plurality of mode characteristic values; performing a data reconstruction on the spatial sampling values and the plurality of mode characteristic values to obtain a reconstructed value set; performing a syntactic encoding on the spatial sampling values and the plurality of mode characteristic values to obtain a syntactic element code set; performing a mode selection according to the reconstructed value set and the syntactic element code set to obtain an optimal prediction mode; and acquiring and outputting a syntactic element code corresponding to the optimal prediction mode to obtain a Demura compensation value com

Abstract: A method for compressing Demura compensation value including: acquiring original compensation values of a target panel; inputting the original compensation values into a spatial domain sampling model, performing a down-sampling to obtain spatial domain sampling values, inputting the original compensation values into a prediction mode overall model, and performing a numerical processing to obtain a plurality of mode characteristic values; performing a data reconstruction on the spatial sampling values and the plurality of mode characteristic values to obtain a reconstructed value set; performing a syntactic encoding on the spatial sampling values and the plurality of mode characteristic values to obtain a syntactic element code set; performing a mode selection according to the reconstructed value set and the syntactic element code set to obtain an optimal prediction mode; and acquiring and outputting a syntactic element code corresponding to the optimal prediction mode to obtain a Demura compensation value com

Abstract: Disclosed is a method and a device for decompressing Demura compensation value based on random-access bit stream. The method includes reading a target compression code corresponding to a target pixel set according to a screen refresh instruction in response to the screen refresh instruction, and decoding the target compression code to obtain Demura compensation values.

Abstract: Control methods of sample adaptive offset (SAO) filtering applied to an image processing system with an SAO filter are provided. The method includes the steps of: receiving video signal, wherein the video signal includes at least one group of picture (GOP) and the GOP has multiple frames, each having multiple coding tree units (CTUs); determining whether current frame is an intra-picture frame (I frame); turning on the SAO filter in response to determining that the current frame is the I frame to enable the SAO filter to perform an SAO filtering on the current frame and determining a CTU ratio of the CTUs being not performed with the SAO filtering for the current frame; and selectively turning off the SAO filter based on the CTU ratio, such that the SAO filter does not perform the SAO filtering on subsequent non-I frames in the GOP including the current frame.

Abstract: Control methods of sample adaptive offset (SAO) filtering applied to an image processing system with an SAO filter are provided. The method includes the steps of: receiving video signal, wherein the video signal includes at least one group of picture (GOP) and the GOP has multiple frames, each having multiple coding tree units (CTUs); determining whether current frame is an intra-picture frame (I frame); turning on the SAO filter in response to determining that the current frame is the I frame to enable the SAO filter to perform an SAO filtering on the current frame and determining a CTU ratio of the CTUs being not performed with the SAO filtering for the current frame; and selectively turning off the SAO filter based on the CTU ratio, such that the SAO filter does not perform the SAO filtering on subsequent non-I frames in the GOP including the current frame.

Abstract: A method for RDO (Rate-Distortion Optimization) based on fit-curves contains at least the following steps: calculating a first fit-curve and a second fit-curve according to information regarding a first frame; carrying information regarding a second frame into the first and second fit-curves to calculate fit distortions and fit bit counts; calculating costs according to the fit distortions and the fit bit counts; determining the best block-division mode for the second frame according to the costs; and dividing the second frame into blocks according to the best block-division mode and encoding the second frame.

Abstract: A method for RDO (Rate-Distortion Optimization) based on fit-curves contains at least the following steps: calculating a first fit-curve and a second fit-curve according to information regarding a first frame; carrying information regarding a second frame into the first and second fit-curves to calculate fit distortions and fit bit counts; calculating costs according to the fit distortions and the fit bit counts; determining the best block-division mode for the second frame according to the costs; and dividing the second frame into blocks according to the best block-division mode and encoding the second frame.

Abstract: An advanced video coding and decoding chip and a method with an optimized processing sequence for the sub-blocks, each including 4×4 pixels, of a macroblock in a discrete cosine transform (DCT) and an inverse DCT are disclosed, wherein the compression hardware and the reconstruction hardware execute the compression and the reconstruction of at least part of a field in parallel.

Abstract: An advanced video coding and decoding chip and a method with a hardware design that calculates direct current coefficients in discrete-cosine-transformed residual blocks corresponding to sixteen sub-blocks within a macroblock and alternating current coefficients in the discrete-cosine-transformed residual blocks corresponding to the sixteen sub-blocks within the macroblock separately and in parallel.

Abstract: An advanced video coding and decoding chip and a method with an optimized processing sequence for the sub-blocks, each including 4×4 pixels, of a macroblock in a discrete cosine transform (DCT) and an inverse DCT are disclosed, wherein the compression hardware and the reconstruction hardware execute the compression and the reconstruction of at least part of a field in parallel.

Abstract: An advanced video coding and decoding chip and a method with a hardware design that calculates direct current coefficients in discrete-cosine-transformed residual blocks corresponding to sixteen sub-blocks within a macroblock and alternating current coefficients in the discrete-cosine-transformed residual blocks corresponding to the sixteen sub-blocks within the macroblock separately and in parallel.