Rotated partial distance search for faster vector quantization encoding

摘要

Partial distance search (PDS) is a method of reducing the amount of computation required for vector quantization encoding. The method is simple and general enough to be incorporated into many fast encoding algorithms. This paper describes a simple improvement to PDS based on principal components analysis (PCA), which rotates the codebook without altering the interpoint distances. Like PDS, this new method can be used to improve many fast encoding algorithms. The algorithm decreases the decoding time of PDS by as much as 44%, and decreases the decoding time of k-d trees by as much as 66% on common vector quantization benchmarks.