De-noising analysis of mammogram images in the wavelet domain using hard and soft thresholding

Abstract

The noisy nature of digital mammograms and low contrast of suspicious areas which make medical images de-noising a challenging problem. Therefore, image de-noising is an important task in image processing, thus the use of wavelet transform provides better and improved quality of an image and reduces noise level. For medical images, many wavelets like db1, sym8, coif1, coif3 etc can be used for de-noising of a medical image. However, in this paper, haar, sym8 daubechies db3 (mallat), daubechies db4 at certain level of soft and hard threshold have been calculated. Later, peak signal to noise ratio (PSNR) values are calculated for these wavelet methods. These experiments help to select the best wavelet transform for the de-noising of particular medical images such as mammogram images.