Wavelet-based medical image compression using EZW

Abstract

The wavelet transform has emerged as a cutting edge technology, within the field of image compression research. Wavelet methods involve overlapping transforms with varying-length basis functions. This overlapping nature of the transform alleviates blocking artifacts, while the multiresolution character of the wavelet decomposition leads to superior energy compaction and perceptual quality of the decompressed image. The embedded zerotree wavelet (EZW) coder is the first algorithm to show the full power of wavelet-based image compression. The main purpose of this paper is to investigate the impact and quality of orthogonal wavelet filter for EZW. Meanwhile, we also look into the effect of the level of wavelet decomposition towards compression efficiency. The wavelet filters used are Haar and Daubechies (1992). The compression simulations are done on few modalities of medical images. The qualitative and quantitative results of these simulations are presented.