Video Coefficient Scanning and Grouping for Lower-Complexity Decoding
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Solution Overview
Problem
Current video coding and decoding technologies suffer from low efficiency and high algorithm complexity, particularly in lossless and near lossless compression, due to the complexity of context-based adaptive binary arithmetic coding and redundant calculations in Golomb-Rice coding.
Innovation Solution
A video coding and decoding method that employs various scanning and grouping manners, including fixed-length and semi-fixed length grouping, along with coding methods like unary, truncated unary, and Golomb-Rice coding, to optimize the decoding process and reduce complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If context-based adaptive binary arithmetic coding (CABAC) is used for lossless compression, then compression efficiency is improved, but algorithm complexity increases significantly
Solution Approach 1:
The patent divides the coefficient sequence into multiple groups based on different criteria (magnitude, position, scanning order). Each group is processed using different coding strategies, avoiding the need for complex context modeling across the entire sequence while maintaining compression efficiency through localized adaptation.
Solution Approach 2:
The patent changes the coding parameters dynamically based on group characteristics. Different groups use different coding modes (unary, truncated unary, Golomb-Rice with different k values), allowing the system to adapt to local data characteristics without the overhead of full CABAC context adaptation.
2Speed
If Golomb-Rice coding is used for compression, then decoding speed is improved, but redundant calculations increase algorithm complexity
Solution Approach 1:
The patent makes the Golomb-Rice parameter k dynamic rather than fixed. The value of k is selected based on the statistical characteristics of each coefficient group, allowing the decoding process to adapt to local data distributions and reduce redundant calculations while maintaining high decoding speed.
Solution Approach 2:
Different regions of the coefficient sequence are assigned different Golomb-Rice parameters based on their local characteristics. This localized adaptation reduces the need for complex global context modeling while maintaining decoding efficiency in each specific region.
3Productivity
If multiple coding methods are used for different groups, then coding performance is improved, but device complexity increases
Solution Approach 1:
The patent segments the coefficient sequence into multiple groups and applies different coding methods to each segment. This segmentation allows the system to achieve high coding performance through method diversity while keeping the complexity manageable by processing each segment independently with simpler, specialized coding techniques.
Data Source
AI summary
The present application provides a video encoding/decoding method and apparatus. The method includes: obtaining, by a decoding end, a code stream of a unit to be decoded; determining a scanning manner and a grouping manner of the unit to be decoded, and an coding manner corresponding to each group; decoding according to the coding manner of each group to obtain one or more coefficient blocks corresponding to the unit to be decoded; and recovering one or more coefficients in each of the coefficient blocks in each group one by one according to the scanning manner of the unit to be decoded to obtain one or more reconstructed data blocks corresponding to the unit to be decoded.