Underwater image sharpening and color correction via dataset based on revised underwater image formation model
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s00371-024-03377-4.pdf
Reference60 articles.
1. Akkaynak, D., Treibitz, T.: A revised underwater image formation model. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2018)
2. Akkaynak, D., Treibitz, T.: Sea-thru: a method for removing water from underwater images. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2019)
3. Akkaynak, D., Treibitz, T., Shlesinger, T., Loya, Y., Tamir, R., Iluz, D.: What is the space of attenuation coefficients in underwater computer vision? In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2017)
4. Ancuti, C.O., Ancuti, C., De Vleeschouwer, C., Bekaert, P.: Color balance and fusion for underwater image enhancement. IEEE Transact. Image Process. 27(1), 379–393 (2018). https://doi.org/10.1109/TIP.2017.2759252
5. Anwar, S., Li, C.: Diving deeper into underwater image enhancement: a survey. Signal Process. Image Commun. 89, 115978 (2020)
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