Image Compression using Classical and Lifting based Wavelets

Abstract: In this paper the use of classical and lifting based wavelets for image compression was presented. Both classical and lifting based wavelets are considered. Classical wavelets considered in this work are Haar wavelet, Daubechie wavelet, Coiflet wavelet, Biorthognal wavelet, Demeyer wavelet, and Symlet wavelet. Lifting based wavelet transforms considered are (5,3) and (9,7). Large number of images, including both color and monochrome images are considered. These wavelet transforms are used to compress the input images by Set Partitioning In Hierarchical Trees (SPIHT) algorithm and by incorporating lifting concepts. SPIHT is a new algorithm based on wavelet transform which is gaining attention due to many potential commercial advantages in the area of image compression. The SPIHT coder is also a refined version of the EZW algorithm and is a powerful image compression algorithm, that produces an embedded bit stream, in which the best reconstructed images, shows a significant compression improvement as well as an increased PSNR.

Keywords: Image compression, SPIHT, Wavelet, Lifting Scheme