Stochastic vector quantization of images

Abstract

The vector quantization scheme has proven to be very effective in image coding. One of the most important steps in the whole process is the design of the codebook. The codebook is generally designed using the Linde-Buzo-Gray algorithm, which is in essence a clustering algorithm that uses a large training set of empirical data that are statistically representative of the image to be quantized. The problem addressed is the stochastic generation of the codebook. The approach is to model the codebook according to some previous model defined for the image to be encoded and then to generate the training set according to the same model and not according to some specific data sequence. The model used is the well-known autoregressive model. Good visual results are shown in the range of 0.5-0.8 b/pixel.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>