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Reseach Article

Adaptive Sigmoid Function to Enhance Low Contrast Images

by Saruchi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 55 - Number 4
Year of Publication: 2012
Authors: Saruchi

Saruchi . Adaptive Sigmoid Function to Enhance Low Contrast Images. International Journal of Computer Applications. 55, 4 ( October 2012), 45-49. DOI=10.5120/8747-2634

@article{ 10.5120/8747-2634,
author = { Saruchi },
title = { Adaptive Sigmoid Function to Enhance Low Contrast Images },
journal = { International Journal of Computer Applications },
issue_date = { October 2012 },
volume = { 55 },
number = { 4 },
month = { October },
year = { 2012 },
issn = { 0975-8887 },
pages = { 45-49 },
numpages = {9},
url = { },
doi = { 10.5120/8747-2634 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T20:56:26.798313+05:30
%A Saruchi
%T Adaptive Sigmoid Function to Enhance Low Contrast Images
%J International Journal of Computer Applications
%@ 0975-8887
%V 55
%N 4
%P 45-49
%D 2012
%I Foundation of Computer Science (FCS), NY, USA

Image enhancement is one of the most important issues in low-level image processing. Mainly, enhancement methods can be classified into two classes: global and local methods. Various enhancement schemes are used for enhancing an image which includes gray scale manipulation, filtering and Histogram Equalization (HE). Histogram Equalization (HE) has proved to be a simple and effective image contrast enhancement technique. In this paper, the global histogram equalization is improved by using sigmoid function combined with local enhancement statistics. Experimental results demonstrate that the proposed method can enhance the images effectively. The performances of the existing techniques and the proposed method are evaluated in terms of SNR, PSNR, CoC.

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Index Terms

Computer Science
Information Sciences


contrast enhancement sigmoid function Histogram Equalization image processing