IMPROVED TECHNIQUES FOR SINGLE-PASS ADAPTIVE VECTOR QUANTIZATION

Constantinescu and Storer [4], [5] present a new single-pass adaptive vector quantization algorithm that learns a codebook of variable size and shape entries; they present experiments on a set of test images showing that with no training or prior knowledge of the data, for a given fidelity, the compression achieved typically equals or exceeds that of the JPEG standard. This paper presents improvements in speed (by employing K-D trees), simplicity of codebook entries, and visual quality with no loss in either the amount of compression or the SNR as compared to the original full-search version.