Vector Permutation Encoding for the Uniform Sources
DCC '04 Proceedings of the Conference on Data Compression
IEEE Transactions on Information Theory
Gaussian source coding with spherical codes
IEEE Transactions on Information Theory
Low-resolution scalar quantization for Gaussian sources and squared error
IEEE Transactions on Information Theory
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Permutation codes are a class of structured vector quantizers with a computationally-simple encoding procedure based on sorting the scalar components. Using a codebook comprising several permutation codes as subcodes preserves the simplicity of encoding while increasing the number of rate-distortion operating points, improving the convex hull of operating points, and increasing design complexity. We show that when the subcodes are designed with the same composition, optimization of the codebook reduces to a lower-dimensional vector quantizer design within a single cone. Heuristics for reducing design complexity are presented, including an optimization of the rate allocation in a shape-gain vector quantizer with gain-dependent wrapped spherical shape codebook.