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Reseach Article

Illumination based Sub Image Histogram Equalization: A Novel Method of Image Contrast Enhancement

by Sangeeta Rani, Ashwini Kumar, Kuldeep Singh
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 119 - Number 20
Year of Publication: 2015
Authors: Sangeeta Rani, Ashwini Kumar, Kuldeep Singh
10.5120/21183-4251

Sangeeta Rani, Ashwini Kumar, Kuldeep Singh . Illumination based Sub Image Histogram Equalization: A Novel Method of Image Contrast Enhancement. International Journal of Computer Applications. 119, 20 ( June 2015), 14-19. DOI=10.5120/21183-4251

@article{ 10.5120/21183-4251,
author = { Sangeeta Rani, Ashwini Kumar, Kuldeep Singh },
title = { Illumination based Sub Image Histogram Equalization: A Novel Method of Image Contrast Enhancement },
journal = { International Journal of Computer Applications },
issue_date = { June 2015 },
volume = { 119 },
number = { 20 },
month = { June },
year = { 2015 },
issn = { 0975-8887 },
pages = { 14-19 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume119/number20/21183-4251/ },
doi = { 10.5120/21183-4251 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:04:34.222286+05:30
%A Sangeeta Rani
%A Ashwini Kumar
%A Kuldeep Singh
%T Illumination based Sub Image Histogram Equalization: A Novel Method of Image Contrast Enhancement
%J International Journal of Computer Applications
%@ 0975-8887
%V 119
%N 20
%P 14-19
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A novel Illumination based Sub-Image Histogram Equalization (ISIHE) method for contrast enhancement for low illumination gray scale images is presented in this paper. As the main crux of paper, illumination thresholds are computed and used to divide the original image into sub-images of different intensity levels. To control the enhancement rate, the histogram is clipped using a threshold value that represents the average number of grey level occurrences in the image. Each individual sub histogram is equalized independently and all sub images are integrated into one complete image for analysis as a final step. The experimental results are compared with other Histogram Equalization (HE) methods and ISIHE has shown promising results.

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Index Terms

Computer Science
Information Sciences

Keywords

Image Contrast Enhancement Image Illumination Threshold Histogram Equalization