Audio Quantization Border Shifting for Lower Entropy Bit Demand
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Solution Overview
Problem
Existing audio coding methods do not effectively account for the bit demand differences in quantized values during the quantization of spectral coefficients, leading to suboptimal bit allocation and noise levels in the encoding process.
Innovation Solution
A modified quantization method that adjusts the borders between quantizer representatives to prioritize reduced bit usage in entropy coding, considering quantization distortion and bit requirements, allowing for increased probability of outputting quantized values that require fewer bits, and incorporating a detection algorithm to choose between normal and modified quantization based on noise and other criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the quantization step size is decreased to reduce quantization noise, then the quantization noise is reduced, but the number of bits required for entropy coding increases
Solution Approach 1:
The patent applies local quality by making the quantization border adjustment specific to each scalefactor band based on local signal characteristics. The detection algorithm evaluates individual bands to determine where border modifications will be most beneficial, allowing different quantization strategies for different frequency regions rather than applying a uniform approach across the entire spectrum.
Solution Approach 2:
The patent modifies the quantization parameter (the border position) to optimize the trade-off between quantization noise and bit consumption. By shifting the border away from the midpoint between quantizer representatives, the system changes the quantization decision boundary to favor outcomes that reduce entropy coding bit requirements while maintaining acceptable noise levels.
2Measurement precision
If the quantization border is positioned at the midpoint between quantizer representatives to minimize quantization error, then the quantization error is minimized, but the bit demand for entropy coding is not optimized
Solution Approach 1:
The patent changes the quantization border parameter from the traditional midpoint position to an optimized position that considers entropy coding bit demand. This parameter modification allows the system to accept slightly higher quantization error in exchange for significant reductions in the number of bits required for entropy coding, achieving better overall compression efficiency.
Solution Approach 2:
The patent introduces dynamic adjustment of the quantization border based on signal characteristics and bit rate constraints. The detection algorithm dynamically determines whether to use the traditional midpoint border or the modified border for each scalefactor band, allowing the system to adapt to different coding conditions and optimize performance across varying input signals.
3Productivity
If a detection algorithm is added to choose between normal and modified quantization, then bit efficiency is improved, but the device complexity increases
Solution Approach 1:
The patent implements feedback through the detection algorithm that evaluates quantization results and adjusts the quantization border accordingly. The algorithm uses feedback from signal characteristics and quantization outcomes to determine whether modified quantization should be applied, creating a closed-loop system that optimizes bit efficiency based on actual performance.
Solution Approach 2:
The detection algorithm is designed to be computationally efficient and self-contained, requiring minimal additional processing resources. The algorithm uses simple criteria and heuristics to make border modification decisions without requiring complex external control systems, allowing the encoder to largely manage its own optimization process with minimal additional complexity.
Data Source
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AI summary
An apparatus for encoding an information signal having discrete values comprises a quantizer having a quantizer border, wherein the quantizer is adapted so that a discrete value above the quantization border is quantized to a quantization index, which is different from a quantization index obtained by quantizing a discrete value below the quantization border, a controller for modifying the quantization border, wherein the quantizer having a first quantization border setting is adapted to generate a first set of quantization indices for the discrete values, and wherein the quantizer having a second modified quantization border setting is adapted to generate a second set of quantization indices, and an output interface for outputting an encoded information signal which is either based on the first set of quantization indices or the second set of quantization indices dependent on a decision function.