Exponent-Residual Audio Coding for Skewed Bitrate Distributions
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Solution Overview
Problem
Existing data coding methods, such as Huffman coding, often perform poorly in scenarios with flat or skewed probability distributions, leading to inefficiencies in transmitting data across channels with bit rate restrictions, particularly in applications like low bit rate audio and video coding, where efficient compression and transmission are crucial.
Innovation Solution
The implementation of a Hybrid Golomb Coder (HGC) that uses a Huffman Variable Length Code to efficiently encode exponent values, reducing the average length of codes by adapting to the frequency of occurrence of symbols and employing a Raw Code for residual values, thereby optimizing data transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional Huffman coding is used, then the coding is simple to implement, but the transmission efficiency deteriorates in scenarios with flat or skewed probability distributions
Solution Approach 1:
The patent segments the data coding process into two distinct parts: exponent coding and residual coding. The exponent represents the magnitude order while the residual represents the offset from that order. This segmentation allows each part to be optimized independently - the exponent can be coded efficiently regardless of probability distribution, while the residual handles the variability. This resolves the contradiction by maintaining good performance across different distributions without requiring complex adaptive mechanisms.
Solution Approach 2:
The patent changes the parameter representation from direct symbol coding to a two-component representation (exponent and residual). By transforming the coding parameter space, the system achieves better adaptability to different probability distributions. The exponent captures the scale information while the residual captures the distribution-specific variations, allowing efficient coding across diverse scenarios without sacrificing simplicity.
2Productivity
If Golomb coding is used, then the performance improves in some scenarios, but the average code length increases compared to optimal coding
Solution Approach 1:
The patent applies local quality by treating the exponent and residual with different coding strategies. The exponent, which determines the magnitude order, is coded with fixed-length or simple variable-length codes. The residual, which varies locally based on the specific value, is coded with Golomb or similar adaptive codes. This localized optimization allows the system to achieve near-optimal average code length while maintaining robust performance across different probability distributions.
3Productivity
If adaptive coding is used to match probability distributions, then the transmission efficiency improves, but the system complexity increases
Solution Approach 1:
The patent performs preliminary action by pre-defining the exponent-residual decomposition structure and the coding schemes for each component. Rather than adapting to probability distributions in real-time, the system is pre-configured with the two-component coding framework that naturally adapts to different distributions through the mathematical properties of exponent and residual decomposition. This eliminates the need for complex adaptive mechanisms while maintaining high transmission efficiency.
Data Source
AI summary
A method of coding audio and/or video data. A data symbol may be coded using an exponent and a residual, in which the exponent is coded using a variable length code, such as but not limited to a Huffman code or a Golomb code. The variable length code may be adaptive and may code according to probabilities or frequencies of occurrence of the data symbol.