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Image Inversion and Bi Level Histogram Equalization for Contrast Enhancement

by P. Shanmugavadivu, K. Balasubramanian
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 1 - Number 15
Year of Publication: 2010
Authors: P. Shanmugavadivu, K. Balasubramanian
10.5120/320-488

P. Shanmugavadivu, K. Balasubramanian . Image Inversion and Bi Level Histogram Equalization for Contrast Enhancement. International Journal of Computer Applications. 1, 15 ( February 2010), 61-65. DOI=10.5120/320-488

@article{ 10.5120/320-488,
author = { P. Shanmugavadivu, K. Balasubramanian },
title = { Image Inversion and Bi Level Histogram Equalization for Contrast Enhancement },
journal = { International Journal of Computer Applications },
issue_date = { February 2010 },
volume = { 1 },
number = { 15 },
month = { February },
year = { 2010 },
issn = { 0975-8887 },
pages = { 61-65 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume1/number15/320-488/ },
doi = { 10.5120/320-488 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:42:29.355202+05:30
%A P. Shanmugavadivu
%A K. Balasubramanian
%T Image Inversion and Bi Level Histogram Equalization for Contrast Enhancement
%J International Journal of Computer Applications
%@ 0975-8887
%V 1
%N 15
%P 61-65
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A novel Image Inversion based Two Level Histogram Equalization (IIBLHE) for contrast enhancement is proposed in this paper. In this method, the first level of equalization is carried out in such a way that the image is inversed first and then histogram equalization is applied; again inversed and the second level of equalization is performed by modifying the probability density function of that resultant image by introducing constraints. This technique of contrast enhancement takes control over the effect of global histogram equalization (GHE / HE) so that it enhances the image without causing any loss of details in it. This approach provides a convenient and effective way to control the enhancement process, while being adaptive to various types of images. Experimental results show that the proposed method gives better results in terms of PSNR values when compared to the existing histogram based equalization methods.

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Index Terms

Computer Science
Information Sciences

Keywords

Contrast Enhancement Histogram Histogram Equalization Probability Density Function (PDF) Cummulative Density Function (CDF)

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