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Performance Analysis of Denoising Algorithms for Human Brain Image
Int. J. Fuzzy Log. Intell. Syst. 2018;18(3):175-181
Published online September 25, 2018
© 2018 Korean Institute of Intelligent Systems.

Nishant Chauhan and Byung-Jae Choi

Department of Electronic Engineering, Daegu University, Gyeongsan, Korea
Correspondence to: Byung-Jae Choi
(bjchoi@daegu.ac.kr)
Received May 29, 2018; Revised September 3, 2018; Accepted September 18, 2018.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Digital images have an important role in areas like X-ray, face recognition, and so on. Different image capturing devices inherit different types of noises. Sometimes low image quality is an obstacle for analysis and measurement. The denoising of an image is an important task. An ideal denoising technique should be able to remove the noise while preserving the quality of the image. In this paper, we examine four noise removal algorithms and present a performance analysis of PSNR and RMSE of several filters for various noises and simulate the performance using MATLAB for human brain image.
Keywords : Human brain image, Denoising, Filter, PSNR, RMSE, Performance analysis