Entropy Encoding with Partitioned Symbols for Adaptive Compression
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Solution Overview
Problem
Current entropy coding schemes, such as Huffman codes and arithmetic coding, face challenges in adapting to time-varying source statistics and higher-order probability modeling, leading to inefficiencies in compression and increased complexity.
Innovation Solution
The proposed solution involves decomposing syntax elements into multiple source symbols and categorizing them into two streams: one for VLC coding and the other for PIPE or arithmetic coding, allowing for better adaptation to statistical changes and improved compression efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If Huffman codes with VLC tables are used for entropy coding, then implementation simplicity is improved, but adaptability to time-varying source statistics deteriorates
Solution Approach 1:
The patent segments the source symbols into multiple categories based on their statistical characteristics. Different VLC tables are prepared for different symbol categories, allowing the system to select appropriate tables based on current source statistics. This segmentation enables both simple VLC implementation and adaptability to varying statistics.
Solution Approach 2:
The patent introduces dynamic adaptation mechanisms where VLC tables are updated or switched based on changing source statistics. The system can adaptively select among multiple VLC tables or update table contents to match current symbol probability distributions, maintaining simplicity while achieving adaptability to time-varying conditions.
2Adaptability or versatility
If arithmetic coding is used for entropy coding, then adaptability to time-varying source statistics is improved, but implementation complexity deteriorates
Solution Approach 1:
The patent uses pre-computed VLC tables that can be quickly switched between rather than performing complex arithmetic coding operations. These tables act as disposable lookup structures that provide arithmetic-coding-like adaptability through simple table selection and lookup, avoiding the computational complexity of actual arithmetic coding while maintaining adaptability benefits.
Solution Approach 2:
The patent changes the parameter representation by using multiple VLC tables with different characteristics instead of a single static table. The system selects or switches between tables based on source statistics, effectively changing the coding parameters to match current conditions without implementing full arithmetic coding complexity.
3Productivity
If multiple VLC tables are used for higher-order probability modeling, then compression efficiency is improved, but device complexity deteriorates
Solution Approach 1:
The patent segments higher-order probability modeling into multiple category-specific VLC tables. Each table handles a specific category of symbols with its own probability distribution characteristics. This segmentation allows efficient compression for each category while keeping individual tables manageable in size and complexity.
Solution Approach 2:
The patent creates a universal framework where a set of VLC tables serves multiple purposes: different tables handle different symbol categories, and the same framework can be applied to various types of data sources. This multi-functionality achieves high compression efficiency across different scenarios without proportionally increasing complexity.
Data Source
AI summary
Decomposing a value range of the respective syntax elements into a sequence of n partitions with coding the components of z laying within the respective partitions separately with at least one by VLC coding and with at least one by PIPE or entropy coding is used to greatly increase the compression efficiency at a moderate coding overhead since the coding scheme used may be better adapted to the syntax element statistics. Accordingly, syntax elements are decomposed into a respective number n of source symbols si with i=1 . . . n, the respective number n of source symbols depending on as to which of a sequence of n partitions into which a value range of the respective syntax elements is sub-divided, a value z of the respective syntax elements falls into, so that a sum of values of the respective number of source symbols si yields z, and, if n>1, for all i=1 . . . n−1, the value of si corresponds to a range of the ith partition.