Huffman Coding Tables for Variable Audio Signal Statistics
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Huffman coding is not optimal for audio signals with varying statistics, often consuming more bits than fixed-length coding, and existing solutions do not adequately address this issue for all input signals with different statistics from the predefined Huffman table.
Innovation Solution
The solution involves exploring auditory masking properties to narrow the range of differential indices, allowing for the design of Huffman tables with fewer code words and shorter lengths, which reduces the total bits consumption for encoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If Huffman coding is used for encoding audio signals with varying statistics, then encoding efficiency is improved for signals matching the Huffman table statistics, but bit consumption increases for signals with different statistics compared to fixed-length coding
Solution Approach 1:
The patent implements dynamic selection between Huffman coding and fixed-length coding based on statistical matching. The encoder evaluates whether the input signal statistics match the predefined Huffman table statistics and adaptively switches coding methods, making the system dynamic rather than static to optimize for varying signal characteristics
Solution Approach 2:
The patent changes the coding parameter (variable-length vs fixed-length) based on signal statistics. By monitoring signal characteristics and adjusting the coding approach accordingly, the system optimizes compression efficiency while preventing bit consumption increases for mismatched signals
2Ease of operation
If a single predefined Huffman table is used for all audio signals, then encoding simplicity is maintained, but encoding optimality deteriorates for signals with statistics different from the predefined table
Solution Approach 1:
The patent segments the encoding process into distinct phases: statistical evaluation, matching determination, and coding execution. By dividing the encoding workflow, the system maintains simplicity in each individual step while achieving optimality through the coordinated sequence of operations
Solution Approach 2:
The patent performs preliminary statistical evaluation and matching determination before actual coding. This advance assessment allows the system to select the appropriate coding method in advance, ensuring encoding optimality without complicating the actual coding operation
3Loss of energy
If Huffman coding is selected for signals with different statistics from the Huffman table, then some compression benefit is maintained, but bit consumption remains higher than necessary compared to adaptive selection
Solution Approach 1:
The patent incorporates feedback through statistical monitoring and matching evaluation. The encoder continuously assesses signal statistics against Huffman table characteristics and uses this feedback to determine the optimal coding method, preventing unnecessary bit consumption while maintaining compression benefits where applicable
Data Source
Figure 1
Figure 2
Figure 3~4
AI summary
In this invention, the design of the Huffman table can be done offline with a large input sequence database. The range of the quantization indices (or differential indices) for Huffman coding is identified. For each value of range, all the input signal which have the same range will be gathered and the probability distribution of each value of the quantization indices (or differential indices) within the range is calculated. For each value of range, one Huffman table is designed according to the probability. And in order to improve the bits efficiency of the Huffman coding, apparatus and methods to reduce the range of the quantization indices (or differential indices) are also introduced.