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Comparison of Fuzzy Contrast Enhancement Techniques

by G. Sudhavani, M. Srilakshmi, P. Venkateswara Rao, K. Satya Prasad
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 95 - Number 22
Year of Publication: 2014
Authors: G. Sudhavani, M. Srilakshmi, P. Venkateswara Rao, K. Satya Prasad
10.5120/16728-6986

G. Sudhavani, M. Srilakshmi, P. Venkateswara Rao, K. Satya Prasad . Comparison of Fuzzy Contrast Enhancement Techniques. International Journal of Computer Applications. 95, 22 ( June 2014), 26-31. DOI=10.5120/16728-6986

@article{ 10.5120/16728-6986,
author = { G. Sudhavani, M. Srilakshmi, P. Venkateswara Rao, K. Satya Prasad },
title = { Comparison of Fuzzy Contrast Enhancement Techniques },
journal = { International Journal of Computer Applications },
issue_date = { June 2014 },
volume = { 95 },
number = { 22 },
month = { June },
year = { 2014 },
issn = { 0975-8887 },
pages = { 26-31 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume95/number22/16728-6986/ },
doi = { 10.5120/16728-6986 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:20:36.442295+05:30
%A G. Sudhavani
%A M. Srilakshmi
%A P. Venkateswara Rao
%A K. Satya Prasad
%T Comparison of Fuzzy Contrast Enhancement Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 95
%N 22
%P 26-31
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The aim of the image enhancement is to improve the interpretability or perception of the information in images for human viewers, or to provide 'better' input for other automated image processing techniques. It is an indispensable tool for researchers in wide verity of fields including art studies, medical imaging, forensics and atmospheric sciences. Most of images like satellite images, medical images and even real life photographs may suffer from poor contrast due to the inadequate or insufficient lighting during image acquiring. So it is necessary to enhance the contrast of an image. In this paper two enhancement techniques namely fuzzy rule based contrast enhancement, and contrast enhancement using intensification operator (INT) are presented for the low contrast grayscale images. In first technique fuzzy system response function is obtained by simple if-then rules, and in second technique the fuzzy contrast intensification operator is taken as a tool for the enhancement in the fuzzy property domain. Comparative analysis of these enhancement techniques is carried out by means of index of fuzziness (IOF) and processing time.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Image enhancement contrast enhancement fuzzy logic membership function intensification operator fuzzy expected value fuzzifiers index of fuzziness processing time.

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