CN-121985130-A - Decoding and encoding method, device and equipment

CN121985130ACN 121985130 ACN121985130 ACN 121985130ACN-121985130-A

Abstract

The application provides a decoding and encoding method, a device and equipment thereof, wherein the decoding method comprises the steps of decoding a first code stream corresponding to a current image block to obtain a coefficient super-parameter characteristic; determining probability distribution parameters based on the coefficient super-parameter characteristics, decoding a second code stream corresponding to the current image block based on the probability distribution parameters to obtain initial reconstruction characteristics, determining initial reconstruction image blocks corresponding to the current image block based on the initial reconstruction characteristics, wherein the initial reconstruction image blocks comprise initial brightness reconstruction image blocks and initial chromaticity reconstruction image blocks, and carrying out brightness edge enhancement on the initial brightness reconstruction image blocks to obtain target brightness reconstruction image blocks. By the technical scheme of the application, the coding performance and decoding performance can be improved.

Inventors

LIU YUNZHUO
CHEN FANGDONG
WU XIAOYANG

Assignees

杭州海康威视数字技术股份有限公司

Dates

Publication Date: 20260505
Application Date: 20231025

Claims (11)

1. An image decoding method, the method comprising: determining an initial reconstruction image block corresponding to a current image block, wherein the initial reconstruction image block comprises an initial chroma reconstruction image block; performing self-adaptive upsampling on the initial chroma reconstruction image block to obtain an upsampled chroma reconstruction image block; And performing filtering operation on the upsampled reconstructed image block to obtain a target reconstructed image block, wherein the target reconstructed image block is used for generating a target reconstructed image block corresponding to the current image block.
2. The method of claim 1, wherein said adaptively upsampling the initial reconstructed chroma block to obtain an upsampled reconstructed chroma block comprises: And if the initial reconstructed image block further comprises an initial brightness reconstructed image block, carrying out self-adaptive upsampling on the initial chroma reconstructed image block based on the initial brightness reconstructed image block to obtain an upsampled chroma reconstructed image block, wherein the upsampled chroma reconstructed image block has the same resolution as the initial brightness reconstructed image block.
3. The method of claim 1, wherein the step of determining the position of the substrate comprises, The filtering operation is performed on the upsampled reconstructed chroma image block to obtain a target reconstructed chroma image block, which comprises the following steps: performing cross-channel filtering on the upsampled reconstructed image block to obtain a target reconstructed image block, or Non-linear chroma filtering is carried out on the chroma reconstruction image block after upsampling to obtain a target chroma reconstruction image block, or Cross-channel filtering is carried out on the up-sampled chroma reconstruction image block to obtain a cross-channel filtered chroma reconstruction image block, and nonlinear chroma filtering is carried out on the cross-channel filtered chroma reconstruction image block to obtain a target chroma reconstruction image block, or And performing nonlinear chroma filtering on the upsampled chroma reconstruction image block to obtain a nonlinear chroma filtered chroma reconstruction image block, and performing cross-channel filtering on the nonlinear chroma filtered chroma reconstruction image block to obtain a target chroma reconstruction image block.
4. A method according to claim 3, wherein cross-channel filtering the upsampled reconstructed image block to obtain a target reconstructed image block or a cross-channel filtered reconstructed image block comprises: The method comprises the steps of carrying out wavelet transformation on an upsampled chroma reconstruction image block, carrying out wavelet transformation on an initial brightness reconstruction image block, connecting the upsampled chroma reconstruction image block after wavelet transformation and the initial brightness reconstruction image block after wavelet transformation in a channel dimension, inputting characteristics after channel dimension connection into a residual block network, and carrying out wavelet inverse transformation on the characteristics output by the residual block network to obtain a cross-channel filtered chroma reconstruction image block or a cross-channel filtered chroma reconstruction image block.
5. An image encoding method, the method comprising: Determining probability distribution parameters based on the coefficient super-parameter characteristics, and encoding initial image characteristics corresponding to the current image block based on the probability distribution parameters; Determining an initial reconstructed image block corresponding to the current image block based on initial reconstructed features corresponding to the initial image features, wherein the initial reconstructed image block comprises an initial chroma reconstructed image block; performing self-adaptive upsampling on the initial chroma reconstruction image block to obtain an upsampled chroma reconstruction image block; And performing filtering operation on the upsampled reconstructed image block to obtain a target reconstructed image block, wherein the target reconstructed image block is used for generating a target reconstructed image block corresponding to the current image block.
6. An image decoding apparatus, characterized in that the apparatus comprises: the determining module is used for determining an initial reconstruction image block corresponding to the current image block, wherein the initial reconstruction image block comprises an initial chroma reconstruction image block; The enhancement module is used for carrying out self-adaptive up-sampling on the initial chroma reconstruction image block to obtain an up-sampled chroma reconstruction image block, and carrying out filtering operation on the up-sampled chroma reconstruction image block to obtain a target chroma reconstruction image block, wherein the target chroma reconstruction image block is used for generating a target reconstruction image block corresponding to the current image block.
7. An image encoding apparatus, the apparatus comprising: The coding module is used for coding the coefficient super-parameter characteristics corresponding to the current image block, determining probability distribution parameters based on the coefficient super-parameter characteristics, and coding the initial image characteristics corresponding to the current image block based on the probability distribution parameters; The determining module is used for determining an initial reconstruction image block corresponding to the current image block based on initial reconstruction features corresponding to the initial image features, wherein the initial reconstruction image block comprises an initial chroma reconstruction image block; The enhancement module is used for carrying out self-adaptive up-sampling on the initial chroma reconstruction image block to obtain an up-sampled chroma reconstruction image block, and carrying out filtering operation on the up-sampled chroma reconstruction image block to obtain a target chroma reconstruction image block, wherein the target chroma reconstruction image block is used for generating a target reconstruction image block corresponding to the current image block.
8. An image decoding device comprising a processor and a machine-readable storage medium storing machine-executable instructions executable by the processor; the processor is configured to execute machine executable instructions to implement the method of any of claims 1-4.
9. An image encoding device comprising a processor and a machine-readable storage medium storing machine-executable instructions executable by the processor; the processor is configured to execute machine-executable instructions to implement the method of claim 5.
10. A machine-readable storage medium having stored thereon computer instructions which, when executed by a processor, implement the method of any of claims 1-4 or which, when executed by a processor, implement the method of claim 5.
11. A computer program product, characterized in that the computer program product comprises a computer program which, when executed by a processor, implements the method of any of claims 1-5.

Description

Decoding and encoding method, device and equipment The application is based on the application number 2023113966936 and the application date 2023, 10 and 25, and creates a divisional application of Chinese patent application named as a decoding and encoding method, a decoding and encoding device and equipment thereof. Technical Field The present application relates to the field of coding and decoding technologies, and in particular, to a decoding and encoding method, apparatus and device thereof. Background For space saving purposes, video images are encoded before transmission, and complete video encoding may include prediction, transformation, quantization, entropy encoding, filtering, and the like. For the prediction process, the prediction process may include intra-frame prediction and inter-frame prediction, where inter-frame prediction refers to predicting a current pixel using pixels adjacent to an encoded image using correlation in the video time domain, so as to achieve the purpose of effectively removing video time domain redundancy. Intra prediction refers to predicting a current pixel by using pixels of an encoded block of a current frame image by utilizing correlation of a video spatial domain, so as to achieve the purpose of removing video spatial redundancy. With the rapid development of deep learning, the deep learning has been successful in many high-level computer vision problems, such as image classification, object detection, etc., and the deep learning is gradually started to be applied in the field of coding and decoding, i.e. the neural network can be used for coding and decoding images. Although the coding and decoding method based on the neural network shows huge performance potential, the coding and decoding method based on the neural network still has the problems of poor coding performance, poor decoding performance, high complexity and the like. Disclosure of Invention In view of the above, the present application provides a decoding and encoding method, apparatus and device thereof, which improves the encoding performance and decoding performance. The application provides a decoding method, which is applied to a decoding end, and comprises the following steps: decoding a first code stream corresponding to a current image block to obtain a coefficient super-parameter characteristic corresponding to the current image block; Determining probability distribution parameters based on the coefficient super-parameter characteristics, and decoding a second code stream corresponding to the current image block based on the probability distribution parameters to obtain initial reconstruction characteristics corresponding to the current image block; Determining an initial reconstruction image block corresponding to the current image block based on the initial reconstruction characteristics, wherein the initial reconstruction image block comprises an initial brightness reconstruction image block and an initial chromaticity reconstruction image block; And carrying out brightness edge enhancement on the initial brightness reconstruction image block to obtain a target brightness reconstruction image block. The application provides a coding method, which is applied to a coding end, and comprises the following steps: coding the coefficient super-parameter characteristic corresponding to the current image block to obtain a first code stream corresponding to the current image block; determining probability distribution parameters based on the coefficient super-parameter characteristics, and encoding initial image characteristics corresponding to the current image block based on the probability distribution parameters to obtain a second code stream corresponding to the current image block; Determining an initial reconstruction image block corresponding to the current image block based on initial reconstruction features corresponding to the initial image features, wherein the initial reconstruction image block comprises an initial brightness reconstruction image block and an initial chromaticity reconstruction image block; For each candidate image domain enhancement parameter, carrying out brightness edge enhancement on the initial brightness reconstruction image block based on the candidate image domain enhancement parameter and the probability distribution parameter to obtain a target brightness reconstruction image block; And selecting the image domain enhancement parameters corresponding to the current image block from all the candidate image domain enhancement parameters based on the cost value corresponding to each candidate image domain enhancement parameter, and encoding the image domain enhancement parameters to obtain a third code stream corresponding to the current image block. The application provides a decoding device, which is applied to a decoding end, and comprises: The decoding module is used for decoding a first code stream corresponding to a current image block to obtain a coeffici