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Transmission Estimation in Underwater Single Images
Abstract
This paper proposes a methodology to estimate the transmission in underwater environments which consists on an adaptation of the Dark Channel Prior (DCP), a statistical prior based on properties of images obtained in outdoor natural scenes. Our methodology, called Underwater DCP (UDCP), basically considers that the blue and green color channels are the underwater visual information source, which enables a significant improvement over existing methods based in DCP. This is shown through a comparative study with state of the art techniques, we present a detailed analysis of our technique which shows its applicability and limitations in images acquired from real and simulated scenes.
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Cited by
Color balance and fusion for underwater image enhancement
Ancuti, C. O., Ancuti, C., De Vleeschouwer, C., & Bekaert, P. (2018) · IEEE Transactions on Image Processing · doi:10.1109/tip.2017.2759252 · Cited by 1,357
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 Image Restoration Using Geodesic Color Distance and Complete Image Formation Model
Park, E., & Sim, J.-Y. (2020) · IEEE Access · doi:10.1109/access.2020.3019767 · Cited by 32
Metadata
- Authors
- Drews Jr, P., do Nascimento, E., Moraes, F., Botelho, S., & Campos, M.
- Venue
- 2013 IEEE International Conference on Computer Vision Workshops
- Publisher
- IEEE
- Published
- 2013-12
- Pages
- 825-830
- ISSN
- 2473-9936 (ISSN-L)
- OpenAlex
- W2009071067
- Cited by
- 866
- References
- 0
- FWCI
- 5.12
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Transmission Estimation in Underwater Single Images. https://app.cochat.ai/papers/10.1109/iccvw.2013.113
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- Drews Jr, P., do Nascimento, E., Moraes, F., Botelho, S., & Campos, M. (2013). Transmission Estimation in Underwater Single Images. 2013 IEEE International Conference on Computer Vision Workshops. https://doi.org/10.1109/iccvw.2013.113
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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.