Residual Coefficient Coding with Extended Precision Constraints
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing video coding standards like HEVC and VVC face challenges in achieving superior coding efficiency and compression while maintaining video quality, particularly in handling large block-size transforms and virtual pipeline data units (VPDUs) in hardware decoders.
Innovation Solution
Implementations in the VVC standard include enhanced coding techniques such as multi-type tree structures, large block-size transforms, high-frequency zeroing, and virtual pipeline data unit (VPDU) size management, along with improved transform coefficient coding methods to optimize video compression.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If large block-size transforms are used to improve coding efficiency, then compression performance is improved, but hardware decoder complexity increases
Solution Approach 1:
The transform block is divided into multiple sub-blocks for independent processing. Each sub-block can be transformed separately using smaller transform kernels, reducing the computational complexity of large block transforms while maintaining coding efficiency through adaptive sub-block processing
Solution Approach 2:
The transform block size is made dynamic and adaptive rather than fixed. The encoder can select different transform block sizes and configurations based on local image characteristics, allowing optimization of coding efficiency while controlling hardware complexity through flexible, context-dependent processing
2Productivity
If virtual pipeline data unit (VPDU) size is increased to improve processing throughput, then productivity is improved, but memory requirements and complexity increase
Solution Approach 1:
The video data stream is divided into virtual pipeline data units of optimized sizes that balance throughput and memory usage. Each VPDU is processed independently through the transformation pipeline, enabling parallel processing while controlling memory buffer requirements through appropriate VPDU dimension selection
3Productivity
If adaptive rice parameter derivation is used to improve compression efficiency, then bit rate is reduced, but computational complexity increases
Solution Approach 1:
Rice parameters are pre-derived and prepared based on local image characteristics before the actual coefficient coding process. This preliminary computation allows the decoder to use simple lookup operations during decoding, reducing real-time computational complexity while maintaining the compression efficiency benefits of adaptive parameter selection
Solution Approach 2:
The Rice parameters (k values) are dynamically adjusted based on local statistical properties of transform coefficients. By changing these parameters adaptively according to local variance and coefficient distribution, the encoding achieves better compression efficiency while the parameter adjustment follows simple rules that limit computational complexity
Data Source
AI summary
Methods, apparatuses, and non-transitory computer-readable storage mediums are provided for video encoding. The method for video encoding includes: determining an extended precision processing flag that indicates whether an extended dynamic range is used for transform coefficients in transform processes based on a value of the extended precision processing flag; determining an extended precision processing constraint flag in general constraint information syntax to provide general constraint controls for the extended precision processing flag, where a value of the extended precision processing constraint flag being equal to 1 indicates that the value of the extended precision processing flag shall be equal to 0; and signaling the extended precision processing flag and the extended precision processing constraint flag.