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Reseach Article

Directional Adaptive Multilevel Median Filter for Salt�and-Pepper Noise Reduction

Published on July 2015 by Sandip Mehta, Jayashri Vajpai
National Conference on Intelligent Systems (NCIS 2014)
Foundation of Computer Science USA
NCIS2014 - Number 1
July 2015
Authors: Sandip Mehta, Jayashri Vajpai
6372034c-6578-417e-ae4a-343959ef7f99

Sandip Mehta, Jayashri Vajpai . Directional Adaptive Multilevel Median Filter for Salt�and-Pepper Noise Reduction. National Conference on Intelligent Systems (NCIS 2014). NCIS2014, 1 (July 2015), 28-31.

@article{
author = { Sandip Mehta, Jayashri Vajpai },
title = { Directional Adaptive Multilevel Median Filter for Salt�and-Pepper Noise Reduction },
journal = { National Conference on Intelligent Systems (NCIS 2014) },
issue_date = { July 2015 },
volume = { NCIS2014 },
number = { 1 },
month = { July },
year = { 2015 },
issn = 0975-8887,
pages = { 28-31 },
numpages = 4,
url = { /proceedings/ncis2014/number1/21880-3279/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Intelligent Systems (NCIS 2014)
%A Sandip Mehta
%A Jayashri Vajpai
%T Directional Adaptive Multilevel Median Filter for Salt�and-Pepper Noise Reduction
%J National Conference on Intelligent Systems (NCIS 2014)
%@ 0975-8887
%V NCIS2014
%N 1
%P 28-31
%D 2015
%I International Journal of Computer Applications
Abstract

This paper presents a novel two-stage adaptive noise reduction scheme for images corrupted by salt and pepper noise. The first stage identifies the impulse noise in the image by classifying the pixels into two classes- the 'noise-free pixels' and the 'noise corrupted pixels', based on the intensity values of the pixels. The second stage aims to reduce the impulse noise from the image by processing the 'noise corrupted pixels' while the 'noise-free pixels' are kept intact. This stage consists of two steps. In the first step, the denoised value of each 'noise corrupted pixel' is calculated using adaptive multilevel median filter. The second step enhances the image quality by applying directional filtering to the denoised image of the first step. Extensive computer simulations indicate that this technique provides significant improvement over many other existing techniques in terms of PSNR.

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Index Terms

Computer Science
Information Sciences

Keywords

Image Restoration Impulse Noise Adaptive Median Filter Noise Detection Denoising Directional Filtering