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Reseach Article

Removal of High Density Impulse Noise using Efficient Median Filter for Digital Image

by Trapti Soni, Narendra Rathor
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 115 - Number 5
Year of Publication: 2015
Authors: Trapti Soni, Narendra Rathor
10.5120/20148-2280

Trapti Soni, Narendra Rathor . Removal of High Density Impulse Noise using Efficient Median Filter for Digital Image. International Journal of Computer Applications. 115, 5 ( April 2015), 25-31. DOI=10.5120/20148-2280

@article{ 10.5120/20148-2280,
author = { Trapti Soni, Narendra Rathor },
title = { Removal of High Density Impulse Noise using Efficient Median Filter for Digital Image },
journal = { International Journal of Computer Applications },
issue_date = { April 2015 },
volume = { 115 },
number = { 5 },
month = { April },
year = { 2015 },
issn = { 0975-8887 },
pages = { 25-31 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume115/number5/20148-2280/ },
doi = { 10.5120/20148-2280 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:53:57.036159+05:30
%A Trapti Soni
%A Narendra Rathor
%T Removal of High Density Impulse Noise using Efficient Median Filter for Digital Image
%J International Journal of Computer Applications
%@ 0975-8887
%V 115
%N 5
%P 25-31
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

An Efficient Median Filter (EMF) algorithm for removal or enhancement of gray scale images are highly corrupted impulse noise is proposed in this paper. Noise in image are represent the pixel value 0's and 255's are ensures that black and white dot in image. In proposed algorithm take an image and select 3x3 size window and target or center pixel value check if its value is 0's or 255's then image is corrupted otherwise noise free image. If image is noisy and target pixels neighboring pixel value is between 0's and 255's then we replace pixel value with the median value and if target pixels neighboring pixel value is 0's or 255's then we replace pixel value with the mean value. Else increased the window size and again repeat this process until image is denoised. The proposed filter algorithm shows better simulation result as compare the existing algorithms. The simulation result shows better and efficient performance of PSNR and MSE and computation time.

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Index Terms

Computer Science
Information Sciences

Keywords

Impulse Noise Digital Image Median Filter PSNR and MSE.