An anatomization of noise removal techniques on medical images

In applications of signal processing such as medicine, communications and satellites, preprocessing is considered as a vital step which focuses on reduction or removal of the level of the noise contained in the image. The process of denoising helps in preserving the finer details and useful information. Medical images like MRI, CT and X-ray contain very fine details that need to be correct and free from noise so that the information and features of interests are not lost during the diagnosis. In this paper, various noise reduction techniques such as wavelet transform, Neural Network, PCA, ICA and mean and median filters over medical images has been discussed. In this paper we tried to highlight the strength and weakness of various noise removal techniques over processing of the medical images.