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Recovery of Underwater Visibility and Structure by Polarization Analysis
Abstract
Underwater imaging is important for scientific research and technology as well as for popular activities, yet it is plagued by poor visibility conditions. In this paper, we present a computer vision approach that removes degradation effects in underwater vision. We analyze the physical effects of visibility degradation. It is shown that the main degradation effects can be associated with partial polarization of light. Then, an algorithm is presented, which inverts the image formation process for recovering good visibility in images of scenes. The algorithm is based on a couple of images taken through a polarizer at different orientations. As a by-product, a distance map of the scene is also derived. In addition, this paper analyzes the noise sensitivity of the recovery. We successfully demonstrated our approach in experiments conducted in the sea. Great improvements of scene contrast and color correction were obtained, nearly doubling the underwater visibility range.
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Cites
Morgan, S. P., Khong, M. P., & Somekh, M. G. (1997) · Applied Optics · doi:10.1364/ao.36.001560 · Cited by 136
Cited by
An Underwater Image Enhancement Benchmark Dataset and Beyond
Li, C., Guo, C., Ren, W., Cong, R., Hou, J., Kwong, S., & Tao, D. (2020) · IEEE Transactions on Image Processing · doi:10.1109/tip.2019.2955241 · Cited by 2,373
Automatic Red-Channel underwater image restoration
Galdran, A., Pardo, D., Picón, A., & Alvarez-Gila, A. (2015) · Journal of Visual Communication and Image Representation · doi:10.1016/j.jvcir.2014.11.006 · Cited by 995
Huang, D., Wang, Y., Song, W., Sequeira, J., & Mavromatis, S. (2018) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-73603-7_37 · Cited by 308
Underwater vision enhancement technologies: a comprehensive review, challenges, and recent trends
Zhou, J., Yang, T., & Zhang, W. (2023) · Applied Intelligence · doi:10.1007/s10489-022-03767-y · Cited by 149
Image mining applications for underwater environment management-A review and research agenda
Nair, R. S., Agrawal, R., Domnic, S., & Kumar, A. (2021) · International Journal of Information Management Data Insights · doi:10.1016/j.jjimei.2021.100023 · Cited by 34
Metadata
- Authors
- Schechner, Y. Y., & Karpel, N.
- Venue
- IEEE Journal of Oceanic Engineering
- Published
- 2005-07
- Volume
- 30
- Issue
- 3
- Pages
- 570-587
- ISSN
- 0364-9059 (ISSN-L)
- OpenAlex
- W2135001643
- Cited by
- 688
- References
- 1
- FWCI
- 6.78
- Type
- journal article
- Language
- en
- Open access
- closed
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- Schechner, Y. Y., & Karpel, N. (2005). Recovery of Underwater Visibility and Structure by Polarization Analysis. IEEE Journal of Oceanic Engineering. https://doi.org/10.1109/joe.2005.850871
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
