TY - JOUR ID - 110 TI - An Enhanced Median Filter for Removing Noise from MR Images JO - Journal of AI and Data Mining JA - JADM LA - en SN - 2322-5211 AU - Arastehfar, S. AU - Pouyan, Ali A. AU - Jalalian, A. AD - National University of Singapore (NUS) AD - School of Computer Engineering, Shahrood University of Technology Y1 - 2013 PY - 2013 VL - 1 IS - 1 SP - 13 EP - 17 KW - Median filter KW - Impulse noise KW - Magnetic Resonance Image DO - 10.22044/jadm.2013.110 N2 - In this paper, a novel decision based median (DBM) filter for enhancing MR images has been proposed. The method is based on eliminating impulse noise from MR images. A median-based method to remove impulse noise from digital MR images has been developed. Each pixel is leveled from black to white like gray-level. The method is adjusted in order to decide whether the median operation can be applied on a pixel. The main deficiency in conventional median filter approaches is that all pixels are filtered with no concern about healthy pixels. In this research, to suppress this deficiency, noisy pixels are initially detected, and then the filtering operation is applied on them. The proposed decision method (DM) is simple and leads to fast filtering. The results are more accurate than other conventional filters. Moreover, DM adjusts itself based on the conditions of local detections. In other words, DM operation on detecting a pixel as a noise depends on the previous decision. As a considerable advantage, some unnecessary median operations are eliminated and the number of median operations reduces drastically by using DM. Decision method leads to more acceptable results in scenarios with high noise density. Furthermore, the proposed method reduces the probability of detecting noise-free pixels as noisy pixels and vice versa.   UR - https://jad.shahroodut.ac.ir/article_110.html L1 - https://jad.shahroodut.ac.ir/article_110_4b3efdd1562a00a00833a9a15ffbd83e.pdf ER -