Multichannel Audio Coding with Eigen-Decomposition for Spatial Fidelity
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Solution Overview
Problem
Existing coding methods for ambisonic signals, such as multi-mono and parametric coding, result in spatial distortions and degradation of the sound scene due to the lack of consideration for channel correlations, leading to artifacts like phantom sound sources and diffuse noise.
Innovation Solution
A method involving the decomposition of covariance matrices into eigenvalues and eigenvectors, followed by quantization of these parameters in the Euler angle or quaternion domain, to optimize the coding rate and reduce spatialization distortions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If multi-mono or parametric coding methods are used for ambisonic signals, then the coding rate is reduced, but spatial distortions and degradation occur due to lack of channel correlation consideration
Solution Approach 1:
The patent transforms the covariance matrix parameters (eigenvalues and eigenvectors) into Euler angle parameters for coding. This parameter transformation allows the spatial correlation information to be efficiently represented with fewer bits while maintaining spatial accuracy, resolving the contradiction between coding rate reduction and spatial precision preservation
Solution Approach 2:
The patent extracts the essential spatial correlation information from the covariance matrix by computing its eigenvalues and eigenvectors, and further extracts the rotational information as Euler angles. This extraction process separates the critical spatial parameters from the full covariance matrix, enabling efficient coding without losing spatial accuracy
2Manufacturing precision
If covariance matrices are coded directly without decomposition, then spatial information is preserved, but the coding rate increases significantly
Solution Approach 1:
The patent extracts only the essential rotational information from the covariance matrix through eigen-decomposition and Euler angle transformation. This extraction eliminates redundant information while preserving the spatial correlation structure, achieving efficient coding with reduced bit rate
Solution Approach 2:
The patent changes the parameter representation from the full covariance matrix elements to Euler angles derived from eigen-decomposition. This parameter transformation reduces the number of parameters to be coded while maintaining the spatial information, resolving the contradiction between fidelity and coding efficiency
3Device complexity
If channel correlations are not considered in coding, then the coding process is simpler, but spatial distortions and artifacts occur
Solution Approach 1:
The patent extracts the channel correlation information through covariance matrix computation and eigen-decomposition. By taking out this essential correlation information in the form of Euler angles, the method maintains spatial image quality while keeping the coding process manageable through systematic processing steps
Data Source
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AI summary
The invention relates to a method for the optimised coding of a multichannel sound signal, comprising the following steps: coding at least one audio signal channel from the original multichannel signal; dividing the original multichannel signal into frequency sub-bands; determining one covariance matrix for each frequency sub-band, representative of a spatial image of the original multichannel signal; decomposing the predetermined covariance matrices into eigenvalues; coding by quantisation of the parameters from the decomposition into eigenvalues comprising both eigenvalues and eigenvectors. The invention also relates to a decoding method for decoding the parameters from the decomposition into eigenvalues of the covariance matrix of the original multichannel signal. It relates to coding and decoding devices implementing the respective methods.