Awesome

underwater-test-dataset-U45-

This project contains an effective and pubic underwater test dataset (U45) including the color casts, low contrast and haze-like effects of underwater degradation. Besides, it includes the entire results and scores of Fusion Enhance (FE) [1], Retinex-Based (RB) [2], UDCP [3], UIBLA [4], RED [5], CycleGAN [6], Weakly Supervised Color Transfer (WSCT) [7] and our proposed method.

If you use the enhanced results and dataset, please cite the following papers:

[1] C. Ancuti, C. O. Ancuti, T. Haber, and P. Bekaert, “Enhancing underwater images and videos by fusion,” in 2012 IEEE Conference on Computer Vision and Pattern Recognition. IEEE, 2012, pp. 81–88.
[2] X. Fu, P. Zhuang, Y. Huang, Y. Liao, X.-P. Zhang, and X. Ding, “A retinex-based enhancing approach for single underwater image,” in 2014 IEEE International Conference on Image Processing (ICIP). IEEE, 2014, pp. 4572–4576.
[3] P. L. Drews, E. R. Nascimento, S. S. Botelho, and M. F. M. Campos, “Underwater depth estimation and image restoration based on single images,” IEEE computer graphics and applications, vol. 36, no. 2, pp. 24–35, 2016.
[4] Y.-T. Peng and P. C. Cosman, “Underwater image restoration based on image blurriness and light absorption,” IEEE transactions on image processing, vol. 26, no. 4, pp. 1579–1594, 2017.
[5] Galdran, Adrian, et al. "Automatic red-channel underwater image restoration." Journal of Visual Communication and Image Representation 26 (2015): 132-145.
[6] J.-Y. Zhu, T. Park, P. Isola, and A. A. Efros, “Unpaired image-to-image translation using cycle-consistent adversarial networks,” in Proceedings of the IEEE international conference on computer vision, 2017, pp. 2223–2232.
[7] C. Li, J. Guo, and C. Guo, “Emerging from water: Underwater image color correction based on weakly supervised color transfer,” IEEE Signal Processing Letters, vol. 25, no. 3, pp. 323–327, 2018.