Medical Image Compression using Lifting based New Wavelet Transforms

Abstract

In this paper, the construction of new lifting based wavelets by a new method of calculating lifting coefficients is presented. First of all, new basis functions are utilized to ease new orthogonal traditional wavelets. Then by using the decomposing poly-phase matrix the lifting steps are calculated using a simplified method. The interesting feature of lifting scheme is that the construction of wavelet is derived in spatial domain only; hence the difficulty in the design of traditional wavelets is avoided. Lifting scheme was used to generate second generation wavelets which are not necessarily translation and dilation of one particular function. Short and sharp basis functions are chosen so as to obtain the non-uniform nature of usual image classes. Implemented wavelets are applied on a number of medical images. It was found that the compression ratio (CR) and Peak Signal to Noise Ratio (PSNR) are far ahead of that are obtained with the popular traditional wavelets as well as the successful 5/3 and 9/7 lifting based wavelets. Set Partitioning in Hierarchical Trees (SPIHT) is used to incorporate compression.

DOI:http://dx.doi.org/10.11591/ijece.v4i5.5969