Medical Image Compression using Different Wavelet Families

Author : Munish Kumar and Priyanka

Abstract

The study presents the importance of image compression in medical images. There are different types of medical images that are used for diagnosed. So we need to store all the diagnostic images regarding the patient. This paper is focused on selecting the most appropriate wavelet function for biomedical images. In this paper we perform compression by using different type of wavelet function with different type of biomedical images and suggested the most appropriate wavelet function that can perform optimum compression for a given type of biomedical image. To analyze the performance of the wavelet function with the biomedical images we fixed the loss amount of the data in the compressed image (Quality of the compressed image will be same for each wavelet function) and calculated their respective compression ratio. The wavelet function that gives the maximum compression for a specific type of biomedical image will be the most appropriate wavelet for that type of biomedical image compression.

Keywords: Maximum error (MSE), peak signal to noise ratio, (PSNR), Threshold, wavelet transform and mean square error.