Spherical Vector Quantization for Low-Complexity Rotation Coding
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Solution Overview
Problem
Current methods for spherical vector quantization in spatialized sound coding, particularly for ambisonic formats, face challenges in efficiently representing rotation matrices and 3D source directions, leading to high computational costs and suboptimal quantization performance.
Innovation Solution
A method for coding and decoding spherical coordinates using a sequential scalar quantization approach that defines a spherical grid, optimizing the search for nearest neighbors by considering multiple candidates per coordinate, and using analytical methods to determine quantization levels and indices, thereby reducing computational complexity and storage requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional spherical vector quantization methods are used for coding rotation matrices and 3D source directions, then the representation of spatialized sound data can be achieved, but the computational cost increases and quantization performance becomes suboptimal
Solution Approach 1:
The patent segments the spherical coordinate space into discrete quantization levels for each coordinate (azimuth and elevation), creating a hierarchical grid structure. This segmentation allows the continuous spherical surface to be represented by discrete indices, reducing computational complexity while maintaining acceptable quantization precision for spatial audio applications.
Solution Approach 2:
The patent changes the representation parameters from continuous spherical coordinates to discrete quantization indices. By transforming the continuous azimuth and elevation angles into discrete levels (e.g., 18 azimuth levels × 9 elevation levels), the system reduces computational requirements while achieving acceptable measurement precision for spatial sound coding.
2Manufacturing precision
If detailed quantization of spherical coordinates is performed to improve reconstruction accuracy, then quantization error decreases, but storage requirements and computational overhead increase
Solution Approach 1:
The patent applies different quantization densities to different regions of the spherical coordinate system. The azimuth coordinate uses 18 levels while the elevation coordinate uses 9 levels, creating an asymmetric quantization grid that allocates more precision where needed. This local quality approach optimizes the balance between reconstruction accuracy and storage requirements.
Solution Approach 2:
The patent uses a partial quantization approach where not all possible spherical directions are represented with maximum precision. Instead, a manageable number of quantization levels (18×9=162 directions) is used, providing sufficient accuracy for spatial audio while keeping storage requirements low. This partial action approach avoids the excessive storage cost of full spherical coverage.
3Measurement precision
If exhaustive search methods are used to find nearest neighbors on the spherical grid, then quantization accuracy improves, but computational complexity increases significantly
Solution Approach 1:
The patent pre-computes and stores the spherical grid of quantization directions in advance, creating a lookup table of 18×9=162 pre-defined directions. During encoding, the system only needs to compare the input spherical coordinates against this pre-computed grid rather than performing complex real-time optimization, significantly improving computational efficiency while maintaining nearest neighbor accuracy.
Data Source
AI summary
Encoding at least one unit quaternion representing a rotation matrix used for coding a multichannel signal represented by an input point on a 4-dimensional sphere by encoding 3 spherical coordinates of the input point. The method includes sequential scalar quantization of the 3 spherical coordinates in order to obtain at most 4 candidates at the end of the sequential scalar quantization of the 3 coordinates; selecting the best candidate which minimizes a distance between the input point and the at most 4 candidates; determining the separate quantization indices resulting from the sequential scalar quantization of the spherical coordinates of the best candidate; determining a global quantization index by adding at least one item of cardinality information to the quantization index of a spherical coordinate; and coding of the global quantization index of said best candidate. A corresponding decoding method, an encoding device and a decoding device are also provided.