Comparative Performance Analysis of Haar, Symlets and Bior wavelets on Image compression using Discrete Wavelet Transform

This paper aims at performing wavelet analysis on jpeg images using discrete wavelet transform for implementation in a still image compression system and to highlight the benefit of this transform relating to other techniques (DCT). The paper discusses important features of wavelet transform in compression of still images, including the extent to which the quality of image is degraded by the process of wavelet compression and decompression and checks the results in terms of image quality metrics PSNR and also computes compression ratios at different level of decompositions of DWT. Haar, Symlets and Biorthogonal wavelets have been applied to an image and results have been compared in the form of qualitative and quantitative analysis in terms of PSNR values and compression ratios. Elapsed times for compression of image for different wavelets have also been computed to get the fast image compression method. Algorithm follows a quantization approach that divides the input image in 4 filter coefficients and then performs further quantization on the lower order filter or window of the previous step that has been developed using MATLAB software. Image quality is measured objectively, using peak signal-to-noise ratio or picture quality scale, and subjectively, using perceived image quality. These results provide a good reference for application developers to choose a good wavelet compression system for their application.