Entropy Encoding Partitioning for Adaptive Compression Efficiency
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing 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 efficiency and complexity.
Innovation Solution
The proposed solution involves decomposing syntax elements into multiple source symbols and categorizing them into substreams for VLC and PIPE coding, allowing for better adaptation to statistical changes and improved compression efficiency through separate encoding and decoding processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If Huffman codes with VLC tables are used for entropy coding, then implementation is efficient and easy to construct, but adaptation to time-varying source statistics is demanding in terms of algorithmic complexity and implementation costs
Solution Approach 1:
The patent segments the source symbols into multiple categories based on their probability characteristics. Different VLC tables are constructed for different symbol categories, allowing each table to be optimized for specific probability distributions. This segmentation enables efficient construction of specialized tables while improving adaptability to varying statistics through category-based selection.
Solution Approach 2:
The patent implements dynamic adaptation by maintaining multiple VLC tables that can be switched between based on the current statistical characteristics of the source. The system dynamically selects appropriate tables or interpolates between them to match time-varying probability distributions, resolving the contradiction between static table efficiency and dynamic adaptability.
2Productivity
If arithmetic coding is used to handle adaptive and higher-order probability modeling, then compression efficiency is improved, but implementation complexity increases substantially compared to VLC
Solution Approach 1:
The patent applies local quality by using different coding methods for different symbol categories. High-probability symbols are encoded using simple VLC tables, while lower-probability symbols use more sophisticated arithmetic coding or interpolated tables. This localized application of complexity achieves good compression efficiency without requiring the entire system to be complex.
Solution Approach 2:
The patent changes parameters by interpolating between multiple pre-computed VLC tables based on the current probability estimates. Instead of implementing full arithmetic coding, the system adjusts which table to use or how to combine tables, achieving adaptive compression with reduced complexity through parameter-based table selection and interpolation.
3Measurement precision
If multiple sets of VLC tables are used for higher-order probability modeling, then modeling accuracy is improved, but memory requirements and table management complexity increase
Solution Approach 1:
The patent creates VLC tables that serve multiple purposes through interpolation. Each table is designed to work in combination with others, allowing the same set of tables to handle different probability distributions and symbol categories. This multi-functionality reduces the total number of tables needed while maintaining high modeling accuracy.
Solution Approach 2:
The patent introduces table interpolation as an intermediary mechanism between discrete VLC tables. Instead of directly managing multiple complete tables for different scenarios, the system uses interpolation to create virtual tables on-demand, reducing memory requirements and simplifying table management while maintaining accuracy.
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.