Paper Info
Title
Comparative analysis of median filter and its variants for removal of impulse noise from gray scale images
Abstract
Image denoising is a vital pre-processing phase, used to refine the image quality and make it more informative. Many image-denoising algorithms have been proposed with their own pros and cons. This paper presents a comprehensive study of the median filter and its different variants to reduce or remove the impulse noise from gray scale images. These filters are compared with respect to their functionality, time complexity and relative performance. For performance evaluation of the existing algorithms, extensive MATLAB based simulations have been carried out on a set of images. For benchmarking the relative performance, we have used Peak Signal to Noise Ratio (PSNR), Root Mean Square Error (RMSE), Universal Image Quality Index (UQI), Structural Similarity Index (SSIM) and Edge-strength Similarity (ESSIM) as quality assessment metrics. The Extended median filter (EMF) and Modified BDND are best in terms of relative statistical ratios and pleasant visual results where IAMF is having the best time complexity among existing algorithms.(c) 2020 The Authors. Production and hosting by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Year
DOI
Venue
2022
10.1016/j.jksuci.2020.03.007
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
Keywords
DocType
Volume
Image denoising, Pre-processing, Impulse noise, Median filter, Functionality, Time complexity, Relative performance
Journal
34
Issue
ISSN
Citations 
3
1319-1578
0
PageRank 
References 
Authors
0.34
0
7
Name
Order
Citations
PageRank
Anwar Shah100.34
Javed Iqbal Bangash2394.11
Abdul Waheed Khan300.34
Imran Ahmed400.34
Abdullah Khan53910.53
Asfandyar khan6105.93
Arshad Khan7234.73