Variable Dimension Weighted Universal Vector Quantization and Noiseless Coding

A new algorithm for variable dimension weighted universal coding is introduced. Combining the multi-codebook system of weighted universal vector quantization (WUVQ), the partitioning technique of variable dimension vector quantization, and the optimal design strategy common to both, variable dimension WUVQ allows mixture sources to be effectively carved into their component subsources, each of which can then be encoded with the codebook best matched to that source. Application of variable dimension WUVQ to a sequence of medical images provides up to 4.8 dB improvement in signal to quantization noise ratio over WUVQ and up to 11 dB improvement over a standard full-search vector quantizer followed by an entropy code. The optimal partitioning technique can likewise be applied with a collection of noiseless codes, as found in weighted universal noiseless coding (WUNC). The resulting algorithm for variable dimension WUNC is also described.