Fast algorithm for vector quantization in radiological image compression

Abstract

In Vector Quantization, the codebook generation requires a clustering scheme, where the number of the clusters (the codebook size) is pre-defined. There are several algorithms which resolve this problem. For example, we quote the well known Linde-Buzo-Gray (LBG) algorithm, and the recent finite state algorithm. Most of them are iterative, and thus, time consuming. Our purpose is to look for a fast one, which is necessary non-iterative and represents adequately the image to be coded. After a review of existing algorithms for codebook generation, we propose a Modified Decision-Directed Clustering (MDDC) technique for codebook generation and its application in radiological image. The Convergence of the (MDDC) algorithm to a globally sub-optimal codebook in finite time is proved.