Hierarchical Audio Coding Least Significant Bit Enhancement
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Solution Overview
Problem
The existing PCM coding methods, such as G.711, suffer from inadequate signal-to-noise ratio (SNR) for wide dynamic range signals, particularly for high-fidelity applications, and increase complexity when attempting to improve quality through hierarchical coding, which is difficult due to the uncorrelated nature of the coding noise.
Innovation Solution
A method that stores and transmits the least significant bits not used in the quantization index binary frame as an enhancement bit stream, allowing for improved decoding precision without increasing coder complexity, by concatenating these bits during decoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional PCM coding (G.711) is used, then the coding complexity is low, but the signal-to-noise ratio is inadequate for wide dynamic range signals
Solution Approach 1:
The patent segments the quantization process into two parts: a base layer using conventional G.711 coding and an enhancement layer using the discarded least significant bits. This segmentation allows the system to maintain low base layer complexity while improving SNR through the additive enhancement layer, resolving the contradiction between low complexity and high reliability.
2Reliability
If hierarchical coding is implemented to improve quality, then the signal-to-noise ratio improves, but the coding complexity increases significantly
Solution Approach 1:
The patent extracts the least significant bits that were discarded during conventional quantization and uses them as an enhancement layer. This extraction approach allows hierarchical coding to be implemented without requiring complex multi-rate analysis-synthesis structures, thereby improving SNR while keeping the coding complexity manageable.
Solution Approach 2:
Instead of permanently discarding the least significant bits during quantization, the patent recovers and transmits them as an enhancement layer. This recovery process enables the decoder to reconstruct the original signal with higher precision, improving SNR without requiring complex encoding structures.
3Measurement precision
If more bits are allocated for quantization, then the decoding precision improves, but the bit rate increases
Solution Approach 1:
The patent implements dynamic bit allocation where the enhancement layer with least significant bits is transmitted conditionally based on channel conditions and receiver capabilities. This dynamic approach allows the system to achieve high decoding precision when needed while maintaining lower bit rates when the enhancement layer is not transmitted, resolving the contradiction between precision and bit rate.
Data Source
AI summary
The invention relates to a method for scalar quantization-based coding of the samples of a digital audio signal (S), the samples being coded over a pre-determined number of bits in order to obtain a binary frame of quantization indices (IPCM), the coding being carried out according to an amplitude compression law, where a pre-determined number of least significant bits are not taken into account in the binary frame of quantization indices. The coding method comprises the steps for storing (27) at least a part of the least significant bits that are not taken into account in the quantization index binary frame and for determination (28) of an enhancement bit stream (IEXT) comprising at least one bit thus stored.The invention also relates to an associated decoding method which comprises the steps for receiving (29) an enhancement bit stream (I′EXT) comprising one or more extension bits and for concatenation (30) of the extension bits behind the bits coming from the binary frame in order to obtain a decoded audio signal.The invention also relates to the coder and decoder implementing these methods.