<title>Fast finite-state codebook design algorithm for vector quantization</title>

Abstract

The Linde-Buzo-Gray (LBG) algorithm is usually used to design a codebook for encoding images in the vector quantization. In each iteration of this algorithm, we must search the full codebook in order to assign the training vectors to their corresponding codewords. Therefore, the LBG algorithm needs large computation effort to obtain a good codebook from the training set. In this paper, we propose a finite-state LBG (FSLBG) algorithm for reducing the computation time. Instead of searching the whole codebook, we search only those codewords that are close to the codeword for a training vector in its previous iteration. In general, the number of these possible codewords can be very small without sacrificing performance. Because of searching only a small part of the codebook, the computation time is reduced. In our experiment, the performance of the FSLBG algorithm in terms of the signal-to-noise ratio is very close to that of the LBG algorithm. However, the computation time of the FSLBG algorithm is only about 10 percent of the time required by the LBG algorithm.