Medical image compression using Embedded Zerotree Wavelet (EZW) coder

Abstract

The aim of this paper is to investigate and explore the viability of Embedded Zerotree (EZW) wavelet coder for therapeutic and medical image compression and high lights its performance based on quality evaluation measurements comparing to Mean square Error (MSE), Bit per pixel (BPP), Peak Signal to Noise Ratio (PSNR) and Compression Ratio (CR) for a particular set of medical images of different modalities. Discrete Wavelet Transform (DWT) has turned into a front line innovation in the spheres of picture processing in general and image compression in particular due to impressive and noteworthy change in picture quality at high compression quotient and better compaction of coefficients. The algorithm what is discussed in this paper has been implemented using the wavelet toolbox of MATLAB. The simulation results exposition that the proposed algorithm is not only an option for the image storage and retrieval on the cloud based medical image computing expeditiously, effectively and economically but it also supports to enhance the utility services in telediagnosis and teleconsultation.