Design and Implementation of Multistage Vector Quantization Algorithm of Image compression assistant by Multiwavelet Transform

Abstract

This paper presents a new coding technique based on contourlet transform and multistage vectorquantization. Multiwavelet based Algorithms for image compression results in high compressionratios compared to other compression techniques. Multiwavelet have shown their ability inrepresenting natural images that contain smooth areas separated withedges. However, wavelets cannot efficiently take advantage of the fact that the edges usually foundin natural images are smooth curves.This issue is addressed by directional transforms, known as contourlets, which have the propertyof preserving edges. The contourlet transform is a new extension to the Multiwavelet transform intwo dimensions using nonseparable and directional filter banks.The computation and storage requirements are the major difficulty in implementing a vectorquantizer. In the full-search algorithm, the computation and storage complexity is an exponentialfunction of the number of bits used in quantizing each frame of spectral information. The storagerequirement in multistage vector quantization is less when compared to full search vectorquantization. The coefficients of contourlet transform are quantized by multistage vectorquantization. The quantized coefficients are encoded by Huffman coding to get better quality i.e.,high peak signal to noise ratio (PSNR). The results obtained are tabulated and compared with theexisting Multiwavelet based ones