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Image Contrast Enhancement Techniques: A Comparative Study of Performance

by Ismail A. Humied, Fatma E.Z. Abou-Chadi
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 137 - Number 13
Year of Publication: 2016
Authors: Ismail A. Humied, Fatma E.Z. Abou-Chadi
10.5120/ijca2016908781

Ismail A. Humied, Fatma E.Z. Abou-Chadi . Image Contrast Enhancement Techniques: A Comparative Study of Performance. International Journal of Computer Applications. 137, 13 ( March 2016), 43-48. DOI=10.5120/ijca2016908781

@article{ 10.5120/ijca2016908781,
author = { Ismail A. Humied, Fatma E.Z. Abou-Chadi },
title = { Image Contrast Enhancement Techniques: A Comparative Study of Performance },
journal = { International Journal of Computer Applications },
issue_date = { March 2016 },
volume = { 137 },
number = { 13 },
month = { March },
year = { 2016 },
issn = { 0975-8887 },
pages = { 43-48 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume137/number13/24444-2016908781/ },
doi = { 10.5120/ijca2016908781 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:38:20.194849+05:30
%A Ismail A. Humied
%A Fatma E.Z. Abou-Chadi
%T Image Contrast Enhancement Techniques: A Comparative Study of Performance
%J International Journal of Computer Applications
%@ 0975-8887
%V 137
%N 13
%P 43-48
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper the performance of four techniques for contrast enhancement of digital images was investigated. The techniques are: histogram equalization (HE), thresholded histogram equalization (WTHE), the low-complexity histogram modification algorithm (LCHM) and a newly developed technique which is a combination of two techniques (HEFGLG): the histogram equalization (HE) and the Fast Gray Level Grouping (FGLG). The performance was compared using different images (gray scale as well as colored) in order to identify which algorithm has the best performance across a variety of images from different sensors and having varying characteristics. Based on the visual quality and the quantitative measures: Absolute Mean Brightness Error (AMBE), the discrete entropy (H), and the measure of enhancement (EME). The experimental results showed that the HEFGLG algorithm outperforms other algorithms. It has the advantage that it has low time complexity since it is a combination of two techniques HE and FGLG, each has low time complexity.

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Index Terms

Computer Science
Information Sciences

Keywords

Histogram Equalization Low-complexity histogram modification Weighted-thresholded histogram equalization Combined algorithm

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