Automatic System for Improving Underwater Image Contrast and Color Through Recursive Adaptive Histogram Modification

Contrast and color are important attributes to extract and acquire much information from underwater images. However, normal underwater images contain bright foreground and dark background areas. Previous enhancement methods enhance the foreground areas but retain darkness and blue-green illumination...

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Main Authors:	Ahmad Shahrizan, Abdul Ghani, Mat Isa, Nor Ashidi
Format:	Article
Language:	English
Published:	Elsevier B.V. 2017
Subjects:	S Agriculture (General) SH Aquaculture. Fisheries. Angling TK Electrical engineering. Electronics Nuclear engineering TR Photography
Online Access:	http://umpir.ump.edu.my/id/eprint/18464/ http://umpir.ump.edu.my/id/eprint/18464/ http://umpir.ump.edu.my/id/eprint/18464/ http://umpir.ump.edu.my/id/eprint/18464/1/fkp-2017-shahrizan-Automatic%20system%20for%20improving%20underwater1.pdf

id	ump-18464
recordtype	eprints
spelling	ump-184642017-11-07T04:01:33Z http://umpir.ump.edu.my/id/eprint/18464/ Automatic System for Improving Underwater Image Contrast and Color Through Recursive Adaptive Histogram Modification Ahmad Shahrizan, Abdul Ghani Mat Isa, Nor Ashidi S Agriculture (General) SH Aquaculture. Fisheries. Angling TK Electrical engineering. Electronics Nuclear engineering TR Photography Contrast and color are important attributes to extract and acquire much information from underwater images. However, normal underwater images contain bright foreground and dark background areas. Previous enhancement methods enhance the foreground areas but retain darkness and blue-green illumination of background areas. This study proposes a new method of enhancing underwater image, which is called recursive adaptive histogram modification (RAHIM), to modify image histograms column wisely in accordance with Rayleigh distribution. Modifying image saturation and brightness in the hue–saturation–value color model increases the natural impression of image color through the human visual system. Qualitative and quantitative evaluations prove the effectiveness of the proposed method. Comparison with state-of-the-art methods shows that the proposed method produces the highest average entropy, measure of enhancement (EME), and EME by entropy with the values of 7.618, 28.193, and 6.829, respectively. Elsevier B.V. 2017-07-27 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/18464/1/fkp-2017-shahrizan-Automatic%20system%20for%20improving%20underwater1.pdf Ahmad Shahrizan, Abdul Ghani and Mat Isa, Nor Ashidi (2017) Automatic System for Improving Underwater Image Contrast and Color Through Recursive Adaptive Histogram Modification. Computers and Electronics in Agriculture, 141. pp. 181-195. ISSN 0168-1699 http://dx.doi.org/10.1016/j.compag.2017.07.021 DOI: 10.1016/j.compag.2017.07.021
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	S Agriculture (General) SH Aquaculture. Fisheries. Angling TK Electrical engineering. Electronics Nuclear engineering TR Photography
spellingShingle	S Agriculture (General) SH Aquaculture. Fisheries. Angling TK Electrical engineering. Electronics Nuclear engineering TR Photography Ahmad Shahrizan, Abdul Ghani Mat Isa, Nor Ashidi Automatic System for Improving Underwater Image Contrast and Color Through Recursive Adaptive Histogram Modification
description	Contrast and color are important attributes to extract and acquire much information from underwater images. However, normal underwater images contain bright foreground and dark background areas. Previous enhancement methods enhance the foreground areas but retain darkness and blue-green illumination of background areas. This study proposes a new method of enhancing underwater image, which is called recursive adaptive histogram modification (RAHIM), to modify image histograms column wisely in accordance with Rayleigh distribution. Modifying image saturation and brightness in the hue–saturation–value color model increases the natural impression of image color through the human visual system. Qualitative and quantitative evaluations prove the effectiveness of the proposed method. Comparison with state-of-the-art methods shows that the proposed method produces the highest average entropy, measure of enhancement (EME), and EME by entropy with the values of 7.618, 28.193, and 6.829, respectively.
format	Article
author	Ahmad Shahrizan, Abdul Ghani Mat Isa, Nor Ashidi
author_facet	Ahmad Shahrizan, Abdul Ghani Mat Isa, Nor Ashidi
author_sort	Ahmad Shahrizan, Abdul Ghani
title	Automatic System for Improving Underwater Image Contrast and Color Through Recursive Adaptive Histogram Modification
title_short	Automatic System for Improving Underwater Image Contrast and Color Through Recursive Adaptive Histogram Modification
title_full	Automatic System for Improving Underwater Image Contrast and Color Through Recursive Adaptive Histogram Modification
title_fullStr	Automatic System for Improving Underwater Image Contrast and Color Through Recursive Adaptive Histogram Modification
title_full_unstemmed	Automatic System for Improving Underwater Image Contrast and Color Through Recursive Adaptive Histogram Modification
title_sort	automatic system for improving underwater image contrast and color through recursive adaptive histogram modification
publisher	Elsevier B.V.
publishDate	2017
url	http://umpir.ump.edu.my/id/eprint/18464/ http://umpir.ump.edu.my/id/eprint/18464/ http://umpir.ump.edu.my/id/eprint/18464/ http://umpir.ump.edu.my/id/eprint/18464/1/fkp-2017-shahrizan-Automatic%20system%20for%20improving%20underwater1.pdf
first_indexed	2023-09-18T22:26:11Z
last_indexed	2023-09-18T22:26:11Z
_version_	1777415981693403136

Automatic System for Improving Underwater Image Contrast and Color Through Recursive Adaptive Histogram Modification

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