Sphere-packings, lattices, and groups
Sphere-packings, lattices, and groups
Vector quantization and signal compression
Vector quantization and signal compression
Length-Limited Variable-to-Variable Length Codes For High-Performance Entropy Coding
DCC '04 Proceedings of the Conference on Data Compression
Necessary conditions for the optimality of variable-rate residual vector quantizers
IEEE Transactions on Information Theory - Part 2
System-on-a-chip test-data compression and decompression architectures based on Golomb codes
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Successive refinement lattice vector quantization
IEEE Transactions on Image Processing
A new, fast, and efficient image codec based on set partitioning in hierarchical trees
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Circuits and Systems for Video Technology
A family of efficient and channel error resilient wavelet/subband image coders
IEEE Transactions on Circuits and Systems for Video Technology
Efficient, low-complexity image coding with a set-partitioning embedded block coder
IEEE Transactions on Circuits and Systems for Video Technology
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Lattice vector quantization (LVQ) reduces coding complexity and computation due to its regular structure. A new multistage LVQ (MLVQ) using an adaptive subband thresholding technique is presented and applied to image compression. The technique concentrates on reducing the quantization error of the quantized vectors by "blowing out" the residual quantization errors with an LVQ scale factor. The significant coefficients of each subband are identified using an optimum adaptive thresholding scheme for each subband. A variable length coding procedure using Golomb codes is used to compress the codebook index which produces a very efficient and fast technique for entropy coding. Experimental results using the MLVQ are shown to be significantly better than JPEG 2000 and the recent VQ techniques for various test images.