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Reseach Article

Devlopment of Fuzzy Based Image Filtering Techniques to Enhance Lung lobe Images

Published on March 2012 by Aparna D. Desmukh, Sapna S. Khapre, Pooja B. Aher
2nd National Conference on Innovative Paradigms in Engineering and Technology (NCIPET 2013)
Foundation of Computer Science USA
NCIPET - Number 3
March 2012
Authors: Aparna D. Desmukh, Sapna S. Khapre, Pooja B. Aher
91d0cfe1-55bb-4bbe-9b7e-ec7f8d0cd24b

Aparna D. Desmukh, Sapna S. Khapre, Pooja B. Aher . Devlopment of Fuzzy Based Image Filtering Techniques to Enhance Lung lobe Images. 2nd National Conference on Innovative Paradigms in Engineering and Technology (NCIPET 2013). NCIPET, 3 (March 2012), 26-29.

@article{
author = { Aparna D. Desmukh, Sapna S. Khapre, Pooja B. Aher },
title = { Devlopment of Fuzzy Based Image Filtering Techniques to Enhance Lung lobe Images },
journal = { 2nd National Conference on Innovative Paradigms in Engineering and Technology (NCIPET 2013) },
issue_date = { March 2012 },
volume = { NCIPET },
number = { 3 },
month = { March },
year = { 2012 },
issn = 0975-8887,
pages = { 26-29 },
numpages = 4,
url = { /proceedings/ncipet/number3/5212-1024/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 2nd National Conference on Innovative Paradigms in Engineering and Technology (NCIPET 2013)
%A Aparna D. Desmukh
%A Sapna S. Khapre
%A Pooja B. Aher
%T Devlopment of Fuzzy Based Image Filtering Techniques to Enhance Lung lobe Images
%J 2nd National Conference on Innovative Paradigms in Engineering and Technology (NCIPET 2013)
%@ 0975-8887
%V NCIPET
%N 3
%P 26-29
%D 2012
%I International Journal of Computer Applications
Abstract

A new fuzzy filter is presented for the noise reduction of images corrupted with additive noise. The filter consists of two stages. The first stage computes a fuzzy derivative for eight different directions. The second stage uses these fuzzy derivatives to perform fuzzy smoothing by weighting the contributions of neighboring pixel values. Both stages are based on fuzzy rules which make use of membership functions. The filter can be applied iteratively to effectively reduce heavy noise. In particular, the shape of the membership functions is adapted according to the remaining noise level after each iteration, making use of the distribution of the homogeneity in the image. A statistical model for the noise distribution can be incorporated to relate the homogeneity to the adaptation scheme of the membership functions. Experimental results are obtained to show the feasibility of the proposed approach. These results are also compared to other filters by numerical measures and visual inspection.

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Index Terms

Computer Science
Information Sciences

Keywords

Devlopment Fuzzy