A fast tree-structured vector quantization method for medical image compression

This paper presents a tree-based search method to speed up the encoding process for vector quantization. The method is especially designed for very large codebooks and is based on a local search rather than on a global search including the whole feature space. The relations between the proposed method and several existing fast algorithms are discussed. Simulation results demonstrate that with little preprocessing and memory cost, the encoding time of the new algorithm has been reduced significantly while encoding quality remains the same with respect to other existing fast algorithms.