Multiple Image Compression in Medical Imaging Techniques using Wavelets for Speedy Transmission and Optimal Storage

Abstract

Multiple image compression using wavelet based methods including Discrete Wavelet Transform (DWT) through sub band coding (SBC) and decoding are reviewed for their comparative study. True color image compression measuring parameters like compression ratio (CR), peak to signal noise ratio (PSNR), mean square error (MSE), bits per pixel (BPP) are computed using MATLAB code for each algorithm employed. Gray scale image like Magnetic Resonance Imaging (MRI) is chosen for wavelet transform to achieve encoding and decoding using multiple wavelet families and resolutions to examine their relative merits and demerits. Our main objective is to establish advantages of multiple compression techniques (compressions using multiresolution) helpful in transmitting bulk of compressed medical images via different gadgets facilitating early detection and diagnosis followed by treatments or referrals to specialists residing in different parts of the world. Contemporary compression techniques based on wavelet transform can serve as revolutionary idea in medical field for the overall benefit of humanity.