RUDIE: Robust approach for underwater digital image enhancement

V.Sidda Reddy; G.Ravi Shankar Reddy; K.Sivanagi Reddy

doi:10.1016/j.jnlest.2024.100286

Journal of Electronic Science and Technology ›› 2024, Vol. 22 ›› Issue (4) : 100286 DOI: 10.1016/j.jnlest.2024.100286

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RUDIE: Robust approach for underwater digital image enhancement

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^a Department of Information Technology, Stanley College of Engineering and Technology for Women, Hyderabad, 500001, India

^b Department of Electronics and Communication Engineering, CVR College of Engineering, Ibrahimpatnam, Hyderabad, 501510, India

^c Department of Electronics and Communication Engineering, Sridevi Women's Engineering College, Hyderabad, 5000075, India

^** E-mail addresses: ravishankar.reddy@cvr.ac.in (G.RaviS. Reddy).

^* E-mail addresses: siddareddy@stanley.edu.in (V.Sidda Reddy),

ksivanagireddy@swec.ac.in (K.Sivanagi Reddy).

V. Sidda Reddy received the B.E. degree in computer science and engineering (CSE) from Bangalore University, Bangalore, India. He graduated from Jawaharlal Nehru Technological University (JNTU), Hyderabad, India, with the M. Tech. degree in information technology (IT) and the Ph.D. degree in data mining in CSE. He is currently a professor with the IT Department at Stanley College of Engineering and Technology for Women, Hyderabad, India. His research has covered topics including data mining, machine learning, and image processing. For the past several years, his research interest has been in data stream mining, data science, and big data analytics. He has published 15 research articles, presented 4 conferences papers, and served as a reviewer for various leading journals.

G. Ravi Shankar Reddy has an extensive academic background in Electronics and Communication Engineering. He completed his B. Tech. degree from JNTU in 2001, followed by the M. Tech. from Osmania University, Hyderabad, India in 2004. He achieved his Ph.D. degree from JNTU in 2018. Dr. Reddy is currently a professor with the Department of Electronics and Communication Engineering, CVR College of Engineering, Hyderabad, India. His research expertise includes signal processing, image processing, and video processing. He has published 20 research papers that are indexed in SCI and Scopus.

K. Sivanagi Reddy obtained his B.E degree from Bharathidasan University, Trichy, India, his M. Tech. degree from JNTU, Kakinada, India, and his Ph.D. degree from JNTU. He is currently designated as a professor with the Department of Electronics and Communication Engineering, Sridevi Women's Engineering College at Hyderabad affiliated with JNTU Hyderabad. He has 20 years of experience in the field of education, research & administration at various levels. He has obtained grant for two UK patents, one Australian patent and published 5 Indian patents. He has published more than 50 articles in IEEE/SCI/Scopus/WoS journals, and presented 15 conferences papers, as well as served as viewer for in various leading journals. Apart from academics, he is an active participant in professional societies as a Life Member of IEEE.

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Abstract

Processing underwater digital images is critical in ocean engineering, biology, and environmental studies, focusing on challenges such as poor lighting, image de-scattering, and color restoration. Due to environmental conditions on the sea floor, improving image contrast and clarity is essential for underwater navigation and obstacle avoidance. Particularly in turbid, low-visibility waters, we require robust computer vision techniques and algorithms. Over the past decade, various models for underwater image enrichment have been proposed to address quality and visibility issues under dynamic and natural lighting conditions. This research article aims to evaluate various image improvement methods and propose a robust model that improves image quality, addresses turbidity, and enhances color, ultimately improving obstacle avoidance in autonomous systems. The proposed model demonstrates high accuracy compared to traditional models. The result analysis indicates the proposed model produces images with greatly improved visibility and exceptional color accuracy. Furthermore, research can unlock new possibilities for underwater exploration, monitoring, and intervention by advancing the state-of-the-art models in this domain.

Keywords

Computer vision / Digital image / Histogram / Image processing / Fuzzy logic

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V.Sidda Reddy, G.Ravi Shankar Reddy, K.Sivanagi Reddy. RUDIE: Robust approach for underwater digital image enhancement. Journal of Electronic Science and Technology, 2024, 22(4): 100286 DOI:10.1016/j.jnlest.2024.100286

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Declaration of competing interest

The authors declare no conflicts of interest.

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