Comparison of Wavelet Transform Filters Using Image Compression

The wavelet transform has become a useful computational tool for a variety of signal and image processing applications. The aim of this paper is to present the comparative study of various wavelet filters. Eleven different wavelet filters (Haar, Mallat, Symlets, Integer, Conflict, Daubechi 1, Daubechi 2, Daubechi 4, Daubechi 7, Daubechi 12 and Daubechi 20) are used to compress seven true color images of 256x256 as a samples. Image quality , parameters such as peak signal-tonoise ratio (PSNR), normalized mean square error have been used to evaluate the performance of wavelet filters. In our work PSNR is used as a measure of accuracy performance. We use two values of compression factors (4.3 and 5.1) to test the wavelet filters [1]. The experimental shows different results but in general the Daubechi Family sp ecialy Daubechi 4, Daubechi 7, Daubechi 12 and Daubechi 20 give better performance in term of PSNR. M atlab 9.0 is used to implement the experiments.