Entropy Encoding Partitions for Adaptive Syntax Compression
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Solution Overview
Problem
Existing entropy coding schemes face challenges in achieving a balance between coding complexity and compression efficiency, particularly when dealing with time-varying source statistics and higher-order probability modeling, as they often require substantial algorithmic complexity and implementation costs.
Innovation Solution
The proposed solution involves decomposing the value range of syntax elements into a sequence of n partitions, where components within each partition are coded separately using a combination of Variable-Length Coding (VLC) and Arithmetic Coding, allowing for adaptive encoding based on the partition each value falls into.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If arithmetic coding is used to handle time-varying source statistics and higher-order probability modeling, then compression efficiency is improved, but device complexity increases substantially
Solution Approach 1:
The patent segments the probability distribution into multiple discrete probability levels (e.g., 8 levels from 1/256 to 128/256). Each level is handled by a dedicated VLC table, avoiding the need for complex arithmetic coding while still adapting to varying source statistics. This segmentation transforms the continuous probability space into discrete bins that can be efficiently encoded.
Solution Approach 2:
The patent changes the parameter representation by using discrete probability levels instead of continuous probability values. Each syntax element is associated with a probability level parameter that selects one of the predefined VLC tables. This parameter change enables adaptive coding without requiring complex arithmetic operations.
2Productivity
If Huffman codes are adapted to handle time-varying source statistics, then compression efficiency is improved, but device complexity and implementation costs increase
Solution Approach 1:
The patent performs preliminary action by pre-computing and storing multiple VLC tables corresponding to different probability levels before actual encoding begins. These tables are prepared in advance and selected based on the current probability level, eliminating the need for real-time adaptation calculations during encoding.
Solution Approach 2:
The patent introduces dynamics by making the VLC table selection adaptive to the current probability level of the syntax element. The system dynamically switches between different VLC tables based on the estimated probability, allowing efficient adaptation to time-varying source statistics without complex real-time computation.
3Productivity
If multiple sets of VLC tables are used for higher-order probability modeling, then compression efficiency is improved, but device complexity increases
Solution Approach 1:
The patent makes the VLC tables universal by designing them to handle multiple probability levels and different syntax element types. The same set of VLC tables can be used for different probability distributions by simply selecting the appropriate table based on the probability level, rather than requiring separate tables for each specific case.
Data Source
Figure 1A
Figure 1B~1C
Figure 2A
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 VCL 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, in accordance with embodiments, 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 (1401-3) 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.