Comparative analysis of Median filter family for Removing High-Density Noise in Magnetic Resonance Images


Magnetic Resonance Imaging (MRI) is a medical indicative test utilized fortaking images of the tissue points of interest of the human body. During imageacquisition, MRI images can be damaged by many noise signals such as impulsenoise. One reason for this noise may be a sharp or sudden disturbance in the imagesignal. The removal of impulse noise is one of the real difficulties. As of late,numerous image de-noising methods were produced for removing the impulse noisefrom images. Comparative analysis of known and modern methods of median filterfamily is presented in this paper. These filters can be categorized as follows:Standard Median Filter; Adaptive Median Filter; Progressive Switching MedianFilter; Noise Adaptive Fuzzy Switching Median Filter; and Different AppliedMedian Filter. The de-noising technique performance for each one is evaluated andcompared using Peak Signal Noise Ratio, Structural Similarity index Metric, andBeta metric as quantitative metrics. The experimental results showed that the latestde-noising technique, Different Applied Median Filter (DAMF), produced betterresults in removing impulse noise compared with the other de-noising techniques.However, this filter produced de-noised image with nonlinear edges in high-densitynoise. As a result, noise removal from images is one of the low-level imagesprocessing which is considered as a first step in many image applications. Therefore,the efficiency of any image processed depends on the efficiency of noise removaltechnique.