A Pragmatic Review of Denoising Techniques Applied for Medical Images

Medical images are complex and unfortunately are often affected by noise. Different types of noise encountered include Gaussian, Poisson, Speckle, Racian and Impulse noise (salt and pepper noise) which can decrease the quality of these images. Denoising aims at enhancing the quality of an image either to a human observer or as a preprocessing step for a computer vision system. Selection of the denoising algorithm is application dependent. Hence, it is necessary to have knowledge about the noise present in the image so as to select the appropriate denoising algorithm. The objective of this paper is to review some significant work in the area of image denoising techniques and algorithms applied to medical images. The paper outlines different medical imagining modalities, various types of noise in medical images and then the review of different denoising techniques and their approaches to remove the noise.