The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Underwater Image Processing: State of the Art of Restoration and Image Enhancement Methods
Open accessAbstract
The underwater image processing area has received considerable attention within the last decades, showing important achievements. In this paper we review some of the most recent methods that have been specifically developed for the underwater environment. These techniques are capable of extending the range of underwater imaging, improving image contrast and resolution. After considering the basic physics of the light propagation in the water medium, we focus on the different algorithms available in the literature. The conditions for which each of them have been originally developed are highlighted as well as the quality assessment methods used to evaluate their performance.
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Cites
Image quality assessment: from error visibility to structural similarity
Wang, Z., Bovik, A. C., Sheikh, H. R., & Simoncelli, E. P. (2004) · IEEE Transactions on Image Processing · doi:10.1109/tip.2003.819861 · Cited by 57,892
Contrast Limited Adaptive Histogram Equalization
Zuiderveld, K. (1994) · Graphics Gems · doi:10.1016/b978-0-12-336156-1.50061-6 · Cited by 4,192
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
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
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
Lagudi, A., Bianco, G., Muzzupappa, M., & Bruno, F. (2016) · Sensors · doi:10.3390/s16040536 · Cited by 43
Metadata
- Authors
- Schettini, R., & Corchs, S.
- Venue
- EURASIP Journal on Advances in Signal Processing
- Published
- 2010-04-21
- Volume
- 2010
- Issue
- 1
- ISSN
- 1110-8657 (ISSN-L)
- 1687-6180
- OpenAlex
- W2145885328
- Cited by
- 697
- References
- 2
- FWCI
- 14.37
- Type
- journal article
- Language
- en
- Open access
- gold
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- Schettini, R., & Corchs, S. (2010). Underwater Image Processing: State of the Art of Restoration and Image Enhancement Methods. EURASIP Journal on Advances in Signal Processing. https://doi.org/10.1155/2010/746052
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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.
