Review of Wavelet Theory and Its Application Toimage Data Compression

The fast development of computing multimedia has led to the demand of using digital images. The manipulation, storage and transmission of these images in their raw form is very expensive, it significantly slows the transmission and makes storage costly. In this paper, a brief review of wavelet transform theory is given using filters as examples to show the related multiresolution analysis. Advantages over Fourier transform is investigated and several results are derived. The pyramid algorithm is also presented and some features of wavelets in image data compression are given. A modified version of Lind Boze and Gray (LBG) algorithm using Partial Search Partial Distortion (PSPD) is presented for coding the wavelet coefficients to speed up the codebook generation and the search required for nearest neighbour codevector of input image. The proposed scheme can save 70 - 80 % of the Vector Quantization (VQ) encoding time as compared to fully search VQ and reduced arithmetic complexity with less sacrificing performance. Key Words: Image compression, Wavelets transform, Vector qQuantization