CABAC Context Sharing for Last Coefficient Position Coding
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current video coding techniques face inefficiencies in encoding and decoding transform coefficients, particularly in reducing the number of contexts required for entropy coding, which affects compression efficiency and storage needs.
Innovation Solution
The proposed solution involves using context adaptive binary arithmetic coding (CABAC) to encode and decode binary strings indicating the position of the last significant coefficient within a block of transform coefficients, determining contexts based on video block sizes to assign shared contexts to multiple binary indices, thereby reducing the total number of contexts needed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If separate contexts are assigned to each binary index for different video block sizes, then coding precision is improved, but device complexity increases due to the large number of contexts required
Solution Approach 1:
The patent merges contexts across different video block sizes by determining a representative block size and assigning the same context to multiple binary indices corresponding to different block sizes. This reduces the total number of contexts while maintaining coding precision through the use of context adaptation based on the representative block size.
Solution Approach 2:
The patent makes contexts universal by creating a context assignment mechanism where a single context can serve multiple binary indices for different video block sizes. The context is adapted based on the representative block size, allowing one context to function across multiple block size scenarios, thereby reducing device complexity.
2Device complexity
If the number of contexts is reduced by sharing contexts across different video block sizes, then device complexity is reduced, but coding precision may deteriorate
Solution Approach 1:
The patent changes the parameter of context assignment by introducing a representative block size parameter. Instead of using fixed separate contexts for each block size, the system determines a representative block size and uses it to adaptively adjust the context for multiple binary indices, maintaining coding precision while reducing the number of contexts.
Solution Approach 2:
The patent introduces dynamics into the context assignment process by making context selection adaptive rather than static. The context is dynamically determined based on the representative block size, allowing the system to optimize coding precision for different block size scenarios using a reduced set of contexts.
3Productivity
If more contexts are used for entropy coding of transform coefficients, then compression efficiency is improved, but storage needs increase
Solution Approach 1:
The patent merges the storage requirements for contexts by consolidating multiple block-size-specific contexts into a reduced set of shared contexts. This reduces the storage needs for context tables while maintaining compression efficiency through adaptive context selection based on the representative block size.
Data Source
AI summary
A video encoder is configured to encode a binary sting indicating a position of a last significant coefficient within a video block. A video decoder is configured to decode the encoded binary string. The string may be coded using context adaptive binary arithmetic coding (CABAC). Binary indices of the binary string may be assigned a context. The context may be determined according to a mapping function. A context may be a assigned to one or more binary indices where each index is associated with a different block size. The last binary index of a 16×16 video block may share a context with the last binary index of a 32×32 video block.