Entropy Coding with Dynamic Probability Mapping for Compression
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Solution Overview
Problem
Existing entropy coding techniques do not effectively utilize the known entropy characteristic of a data stream to optimize compression without increasing processing throughput or system complexity.
Innovation Solution
An improved entropy coding system that maps symbols to unique input-state pairs based on a probability distribution, allowing for dynamic adjustment of the probability distribution to enhance compression efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of substance
If traditional entropy coding techniques are used, then system complexity remains manageable, but data compression efficiency is suboptimal when entropy characteristics are known
Solution Approach 1:
The patent applies preliminary action by pre-determining the mapping of symbols to codewords based on known entropy characteristics and probability distributions before the actual encoding process. This allows the system to achieve optimal compression without increasing runtime complexity, as the optimal mapping is calculated in advance when entropy information is available.
2Productivity
If fixed-length encoding is used, then processing throughput is maintained, but compression efficiency is reduced
Solution Approach 1:
The patent changes the parameter of codeword length from fixed to variable based on symbol probability. By adjusting codeword lengths according to the probability distribution of symbols (shorter codes for high-probability symbols, longer codes for low-probability symbols), the system achieves both improved compression efficiency and maintained processing throughput through efficient lookup operations.
3Loss of substance
If variable-length codes are assigned based on probability, then compression improves, but decoding complexity increases
Solution Approach 1:
The patent uses copying by creating a pre-computed mapping table that stores the relationship between symbols and their optimal variable-length codewords. This mapping is copied into both encoder and decoder, allowing both devices to use simple table lookup operations instead of complex probability calculations during encoding and decoding, thus reducing decoding complexity while maintaining compression efficiency.
Data Source
AI summary
Systems and methods for an entropy coding system are described. The entropy coding systems include an encoding apparatus and a decoding apparatus. The encoding apparatus is configured to receive an original input stream comprising a plurality of symbols having a known entropy characteristic according to a probability distribution of each of the symbols appearing in the original input stream, determine an input and respective state for each symbol read from the original input stream, append the determined input to the encoded output stream, and provided the encoded output stream to the decoding apparatus. The decoding apparatus is configured to receive the encoded output stream, process the encoded output stream, and for each read input: determine an output symbol and a respective output, persist the respective output state to the encoded output stream, and append the determined output symbol to the results output stream.