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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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  2/2018 - 14

 HIGH-IMPACT PAPER 

Underwater Image Enhancement by Adaptive Gray World and Differential Gray-Levels Histogram Equalization

WONG, S.-L. See more information about WONG, S.-L. on SCOPUS See more information about WONG, S.-L. on IEEExplore See more information about WONG, S.-L. on Web of Science, PARAMESRAN, R. See more information about  PARAMESRAN, R. on SCOPUS See more information about  PARAMESRAN, R. on SCOPUS See more information about PARAMESRAN, R. on Web of Science, TAGUCHI, A. See more information about TAGUCHI, A. on SCOPUS See more information about TAGUCHI, A. on SCOPUS See more information about TAGUCHI, A. on Web of Science
 
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Download PDF pdficon (1,881 KB) | Citation | Downloads: 1,325 | Views: 3,379

Author keywords
digital images, image processing, image enhancement, image color analysis, image fusion

References keywords
image(23), water(16), enhancement(11), processing(10), quality(6), information(5), signal(4), restoration(4), method(4), images(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2018-05-31
Volume 18, Issue 2, Year 2018, On page(s): 109 - 116
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2018.02014
Web of Science Accession Number: 000434245000014
SCOPUS ID: 85047857925

Abstract
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Most underwater images tend to be dominated by a single color cast. This paper presents a solution to remove the color cast and improve the contrast in underwater images. However, after the removal of the color cast using Gray World (GW) method, the resultant image is not visually pleasing. Hence, we propose an integrated approach using Adaptive GW (AGW) and Differential Gray-Levels Histogram Equalization (DHE) that operate in parallel. The AGW is applied to remove the color cast while DHE is used to improve the contrast of the underwater image. The outputs of both chromaticity components of AGW and intensity components of DHE are combined to form the enhanced image. The results of the proposed method are compared with three existing methods using qualitative and quantitative measures. The proposed method increased the visibility of underwater images and in most cases produces better quantitative scores when compared to the three existing methods.


References | Cited By

Cited-By Clarivate Web of Science

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Cited-By SCOPUS

SCOPUS® Times Cited: 18
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Cited-By CrossRef

[1] Single underwater image enhancement using integrated variational model, Li, Nan, Hou, Guojia, Liu, Yuhai, Pan, Zhenkuan, Tan, Lu, Digital Signal Processing, ISSN 1051-2004, Issue , 2022.
Digital Object Identifier: 10.1016/j.dsp.2022.103660
[CrossRef]

[2] Underwater image restoration using oblique gradient operator and light attenuation prior, Li, Jingyi, Hou, Guojia, Wang, Guodong, Multimedia Tools and Applications, ISSN 1380-7501, 2022.
Digital Object Identifier: 10.1007/s11042-022-13605-5
[CrossRef]

[3] WITHDRAWN: Feature extraction of underwater images using principle component analysis with image registration, Islabudeen, M., Vigneshwaran, P., Sindhu Madhuri, G., Muthu Kumar, B., Ragaventhiran, J., Sharmila, G., Materials Today: Proceedings, ISSN 2214-7853, 2021.
Digital Object Identifier: 10.1016/j.matpr.2021.03.341
[CrossRef]

[4] An improved image enhancement framework based on multiple attention mechanism, Chen, Qili, Fan, Junfang, Chen, Wenbai, Displays, ISSN 0141-9382, Issue , 2021.
Digital Object Identifier: 10.1016/j.displa.2021.102091
[CrossRef]

[5] An Integrated Method to Remove Color Cast and Contrast Enhancement for Underwater Image, WONG, Siaw-Lang, PARAMESRAN, Raveendran, YOSHIDA, Ibuki, TAGUCHI, Akira, IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, ISSN 0916-8508, Issue 11, Volume E102.A, 2019.
Digital Object Identifier: 10.1587/transfun.E102.A.1524
[CrossRef]

[6] Underwater image enhancement: a comprehensive review, recent trends, challenges and applications, Raveendran, Smitha, Patil, Mukesh D., Birajdar, Gajanan K., Artificial Intelligence Review, ISSN 0269-2821, Issue 7, Volume 54, 2021.
Digital Object Identifier: 10.1007/s10462-021-10025-z
[CrossRef]

[7] Underwater images quality improvement techniques for feature extraction based on comparative analysis for species classification, Kaur, Maninder, Vijay, Sandip, Multimedia Tools and Applications, ISSN 1380-7501, Issue 14, Volume 81, 2022.
Digital Object Identifier: 10.1007/s11042-022-12535-6
[CrossRef]

[8] Underwater image enhancement and restoration based on local fusion, Gao, Yakun, Wang, Jing, Li, Haibin, Feng, Lei, Journal of Electronic Imaging, ISSN 1017-9909, Issue 04, Volume 28, 2019.
Digital Object Identifier: 10.1117/1.JEI.28.4.043014
[CrossRef]

[9] Enhancing underwater image via adaptive color and contrast enhancement, and denoising, Li, Xinjie, Hou, Guojia, Li, Kunqian, Pan, Zhenkuan, Engineering Applications of Artificial Intelligence, ISSN 0952-1976, Issue , 2022.
Digital Object Identifier: 10.1016/j.engappai.2022.104759
[CrossRef]

[10] Review of underwater image restoration algorithms, Raihan A, Jarina, Abas, Pg Emeroylariffion, C. De Silva, Liyanage, IET Image Processing, ISSN 1751-9659, Issue 10, Volume 13, 2019.
Digital Object Identifier: 10.1049/iet-ipr.2019.0117
[CrossRef]

[11] Color correction and restoration based on multi-scale recursive network for underwater optical image, Huang, Yifan, Liu, Manyu, Yuan, Fei, Signal Processing: Image Communication, ISSN 0923-5965, Issue , 2021.
Digital Object Identifier: 10.1016/j.image.2021.116174
[CrossRef]

[12] Underwater images contrast enhancement and its challenges: a survey, Almutiry, Omar, Iqbal, Khalid, Hussain, Shariq, Mahmood, Awais, Dhahri, Habib, Multimedia Tools and Applications, ISSN 1380-7501, 2021.
Digital Object Identifier: 10.1007/s11042-021-10626-4
[CrossRef]

[13] An automated solid waste detection using the optimized YOLO model for riverine management, Zailan, Nur Athirah, Azizan, Muhammad Mokhzaini, Hasikin, Khairunnisa, Mohd Khairuddin, Anis Salwa, Khairuddin, Uswah, Frontiers in Public Health, ISSN 2296-2565, Issue , 2022.
Digital Object Identifier: 10.3389/fpubh.2022.907280
[CrossRef]

[14] Processing and compression of underwater image based on deep learning, Zhang, Jianrong, Optik, ISSN 0030-4026, Issue , 2022.
Digital Object Identifier: 10.1016/j.ijleo.2022.170168
[CrossRef]

[15] A Survey on Underwater Images Enhancement Techniques, Soni, Om Kumari, Kumare, Jamvant Singh, 2020 IEEE 9th International Conference on Communication Systems and Network Technologies (CSNT), ISBN 978-1-7281-4976-9, 2020.
Digital Object Identifier: 10.1109/CSNT48778.2020.9115732
[CrossRef]

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