Comparative Analysis of Wavelet Filters Using Objective Quality Measures

In wavelet based image coding, a variety of orthogonal and biorthogonal filters have been developed by researchers for signal analysis and compression. The selection of wavelet filters plays a crucial part in achieving an effective coding performance, because there is no filter that performs the best for all images. The aim of this paper is to examine a set of wavelet filters from different families for implementation in still image compression system and to analyze their effects on image quality. Three quality measures viz. peak signal to noise ratio (PSNR), picture quality scale (PQS) and a recently developed quality measure structural similarity index (SSIM), which compares local patterns of pixel intensities that have been normalized for luminance and contrast, are used for comparison at various bit rates on selected test images. Our aim here is to suggest the most suitable wavelet filter for different test images based upon these quality measures.