RUDIE: Robust approach for underwater digital image enhancement
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...
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| Format: | Article |
| Language: | English |
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KeAi Communications Co., Ltd.
2024-12-01
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| Series: | Journal of Electronic Science and Technology |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1674862X24000545 |
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| author | V.Sidda Reddy G.Ravi Shankar Reddy K.Sivanagi Reddy |
| author_facet | V.Sidda Reddy G.Ravi Shankar Reddy K.Sivanagi Reddy |
| author_sort | V.Sidda Reddy |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-20ce8ef11d964c73a8b7735cc2ce90ac |
| institution | DOAJ |
| issn | 2666-223X |
| language | English |
| publishDate | 2024-12-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Journal of Electronic Science and Technology |
| spelling | doaj-art-20ce8ef11d964c73a8b7735cc2ce90ac2025-08-20T02:53:13ZengKeAi Communications Co., Ltd.Journal of Electronic Science and Technology2666-223X2024-12-0122410028610.1016/j.jnlest.2024.100286RUDIE: Robust approach for underwater digital image enhancementV.Sidda Reddy0G.Ravi Shankar Reddy1K.Sivanagi Reddy2Department of Information Technology, Stanley College of Engineering and Technology for Women, Hyderabad, 500001, India; Corresponding author.Department of Electronics and Communication Engineering, CVR College of Engineering, Ibrahimpatnam, Hyderabad, 501510, India; Corresponding author.Department of Electronics and Communication Engineering, Sridevi Women's Engineering College, Hyderabad, 5000075, IndiaProcessing 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.http://www.sciencedirect.com/science/article/pii/S1674862X24000545Computer visionDigital imageHistogramImage processingFuzzy logic |
| spellingShingle | V.Sidda Reddy G.Ravi Shankar Reddy K.Sivanagi Reddy RUDIE: Robust approach for underwater digital image enhancement Journal of Electronic Science and Technology Computer vision Digital image Histogram Image processing Fuzzy logic |
| title | RUDIE: Robust approach for underwater digital image enhancement |
| title_full | RUDIE: Robust approach for underwater digital image enhancement |
| title_fullStr | RUDIE: Robust approach for underwater digital image enhancement |
| title_full_unstemmed | RUDIE: Robust approach for underwater digital image enhancement |
| title_short | RUDIE: Robust approach for underwater digital image enhancement |
| title_sort | rudie robust approach for underwater digital image enhancement |
| topic | Computer vision Digital image Histogram Image processing Fuzzy logic |
| url | http://www.sciencedirect.com/science/article/pii/S1674862X24000545 |
| work_keys_str_mv | AT vsiddareddy rudierobustapproachforunderwaterdigitalimageenhancement AT gravishankarreddy rudierobustapproachforunderwaterdigitalimageenhancement AT ksivanagireddy rudierobustapproachforunderwaterdigitalimageenhancement |