CFP last date
20 January 2025
Reseach Article

Effect of Different Window Size on Median Filter Performance with Variable Noise Densities

by Asmaa Hameed Rasheed, Haneen Mohammed Hussein
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 178 - Number 2
Year of Publication: 2017
Authors: Asmaa Hameed Rasheed, Haneen Mohammed Hussein
10.5120/ijca2017915732

Asmaa Hameed Rasheed, Haneen Mohammed Hussein . Effect of Different Window Size on Median Filter Performance with Variable Noise Densities. International Journal of Computer Applications. 178, 2 ( Nov 2017), 22-27. DOI=10.5120/ijca2017915732

@article{ 10.5120/ijca2017915732,
author = { Asmaa Hameed Rasheed, Haneen Mohammed Hussein },
title = { Effect of Different Window Size on Median Filter Performance with Variable Noise Densities },
journal = { International Journal of Computer Applications },
issue_date = { Nov 2017 },
volume = { 178 },
number = { 2 },
month = { Nov },
year = { 2017 },
issn = { 0975-8887 },
pages = { 22-27 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume178/number2/28645-2017915732/ },
doi = { 10.5120/ijca2017915732 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:49:17.338201+05:30
%A Asmaa Hameed Rasheed
%A Haneen Mohammed Hussein
%T Effect of Different Window Size on Median Filter Performance with Variable Noise Densities
%J International Journal of Computer Applications
%@ 0975-8887
%V 178
%N 2
%P 22-27
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A noise removal (de-noising) is one of the important problems in image processing applications. The noise added to the original image by changes the intensity of some pixels while other remain unchanged. Salt-and-pepper noise is one of the impulse noises, to remove it a simplest way used by windowing the noisy image with a conventional median filter. Median filters are the most popular filters extensively applied to eliminate salt-and-pepper noise. This paper evaluates the performance of median filter based on the effective median per window by using different window sizes. The experimental results show that median filter has a good performance in low noise densities and also in high noise densities when using high level of window sizes, but with higher window size a degree of blurring effect will be added to filtered noise. The approach used is a windowing operator technique to cut the pixels of an image, and apply filtering processing to them that take different window sizes 3*3 and 5*5 and 7*7. The results obtain for image size of 250*400.

References
  1. R. Gonzalez and R.E. Woods, Digital Image Processing. Reading, MA: Prentice Hall,3rd edition, 2007.
  2. N.Rajesh Kumar, J.Uday Kumar,"A Spatial Mean and Median Filter For Noise Removal in Digital Images ",International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, Vol. 4, Issue 1, January 2015.
  3. S. Singh and N. R. Prakash, “Modified Adaptive Median Filter for Salt & Pepper Noise”, International Journal of Advanced Research in Computer and Communication Engineering, vol. 3, no. 1, (2014) January.
  4. M. Karaman, A. Atalar, “Design and Implementation of a General-Purpose Median Filter Unit in CMOS VLSI", IEEE Journal of Solid-State Circuits, Vol. 25, No. 2, April 1990.
  5. B. Deka and S. Choudhury, “A Multiscale Detection based Adaptive Median Filter for the Removal of Salt and Pepper Noise from Highly Corrupted Images”, International Journal of Signal Processing, Image Processing and Pattern Recognition, vol. 6, no. 2, (2013) April.
  6. M. S. Nair, K. Revath and R. Tatavarti, “Removal of Salt-and Pepper Noise in Images: A New Decision-Based Algorithm”, Proceedings of the International Multi Conference of Engineers and Computer Scientists, vol 1, (2008), Hong Kong.
  7. Eskicioglu AM, Fisher PS. Image quality measures and their performance. IEEE Trans Commun. 1995;43:2959–65.
Index Terms

Computer Science
Information Sciences

Keywords

Image filtering median filter gray image salt & pepper noise