Implementation of LBG Algorithm for Image Compression

摘要

This paper presents an implementation of LBG algorithm for image compression which makes it possible for creating file sizes of manageable, storable and transmittable dimensions. Image Compression techniques fall under two categories, namely, Lossless and Lossy. The Linde, Buzo, and Gray (LBG) algorithm is an iterative algorithm which alternatively solves the two optimality criteria i.e. Nearest neighbor condition and centroid condition. The algorithm requires an initial codebook to start with. Codebook is generated using a training set of images. There are different methods like Random Codes and Splitting in which the initial code book can be obtained. This initial codebook is obtained by the splitting method in LBG algorithm. In this method an initial code vector is set as the average of the entire training sequence. This code vector is then split into two. The iterative algorithm is run with these two vectors as the initial codebook. The final two code vectors are splitted into four and the process is repeated until the desired number of code vector is obtained. The LBG algorithm is measured by calculating performances such as Compression Ratio (CR), Mean square error (MSE), Peak SignaltoNoise Ratio (PSNR).