1 |
Zhang, T., Li, Y., & Takahashi, S. (2021). Underwater Image Enhancement Using Improved Generative Adversarial Network. Concurrency and Computation: Practice and Experience, 33(22), e5841. https://doi.org/10.1002/cpe.5841
DOI
|
2 |
Zhu, J.Y., Park, T., Isola, P., & Efros, A.A. (2017). Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks. In Proceedings of the IEEE International Conference on Computer Vision, 2223-2232.
|
3 |
Panetta, K., Gao, C., & Agaian, S. (2015). Human-Visual-System- Inspired Underwater Image Quality Measures. IEEE Journal of Oceanic Engineering, 41(3), 541-551. https://doi.org/10.1109/JOE.2015.2469915
DOI
|
4 |
Ancuti, C.O., Ancuti, C., De Vleeschouwer, C., & Bekaert, P. (2017). Color Balance and Fusion for Underwater Image Enhancement. IEEE Transactions on Image Processing, 27(1), 379-393. https://doi.org/10.1109/TIP.2017.2759252
DOI
|
5 |
Arjovsky, M., Chintala, S., & Bottou, L. (2017). Wasserstein Generative Adversarial Networks. Proceedings of the 34th International Conference on Machine Learning, PMLR, 70, 214-223.
|
6 |
Chen, X., Yu, J., Kong, S., Wu, Z., Fang, X., & Wen, L. (2019). Towards Real-Time Advancement of Underwater Visual Quality with GAN. In IEEE Transactions on Industrial Electronics, 66(12), 9350-9359. https://doi.org/10.1109/TIE.2019.2893840
DOI
|
7 |
Deng, J., Dong, W., Socher, R., Li, L.J., Li, K., & Fei-Fei, L. (2009, June). Imagenet: A Large-Scale Hierarchical Image Database. In 2009 IEEE Conference on Computer Vision and Pattern Recognition, 248-255. https://doi.org/10.1109/CVPR.2009.5206848
DOI
|
8 |
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., WardNe-Farley, D., Ozair, S., Courville, A., & Bengio, Y. (2014). Generative Adversarial Nets. Advances in Neural Information Processing Systems, 27.
|
9 |
Islam, M.J., Xia, Y., & Sattar, J. (2020). Fast Underwater Image Enhancement for Improved Visual Perception. IEEE Robotics and Automation Letters, 5(2), 3227-3234. https://doi.org/10.1109/LRA.2020.2974710
DOI
|
10 |
Han, M., Lyu, Z., Qiu, T., & Xu, M. (2018). A Review on Intelligence Dehazing and Color Restoration for Underwater Images. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 50(5), 1820-1832. https://doi.org/10.1109/TSMC.2017.2788902
DOI
|
11 |
Li, C.Y., & Cavallaro, A. (2020, October). Cast-Gan: Learning to Retmove Colour Cast From Underwater Images. In 2020 IEEE International Conference on Image Processing (ICIP), 1083-1087. https://doi.org/10.1109/ICIP40778.2020.9191157
|
12 |
He, K., Sun, J., & Tang, X. (2010). Single Image Haze Removal Using Dark Channel Prior. IEEE Transactions on Pattern Analysis and Machine Intelligence, 33(12), 2341-2353. https://doi.org/10.1109/TPAMI.2010.168
DOI
|
13 |
He, K., Zhang, X., Ren, S., & Sun, J. (2016). Deep Residual Learning for Image Recognition. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 770-778.
|
14 |
Li, W.J., Gu, B., Huang, J.T., Wang, S.Y., & Wang, M.H. (2012). Single Image Visibility Enhancement in Gradient Domain. IET Image Processing, 6(5), 589-595.
DOI
|
15 |
Ronneberger, O., Fischer, P., & Brox, T. (2015). U-Net: Convolutional Networks for Biomedical Image Segmentation. In International Conference on Medical Image Computing and Computer-Assisted Intervention, Springer, Cham, 234-241. https://doi.org/10.1007/978-3-319-24574-4_28
DOI
|
16 |
Uplavikar, P. M., Wu, Z., & Wang, Z. (2019, May). All-in-One Underwater Image Enhancement Using Domain-Adversarial Learning. In CVPR Workshops, 1-8.
|
17 |
Wang, J., Li, P., Deng, J., Du, Y., Zhuang, J., Liang, P., & Liu, P. (2020). CA-GAN: Class-Condition Attention GAN for A Underwater Image Enhancement. IEEE Access, 8, 130719-130728. https://doi.org/10.1109/ACCESS.2020.3003351
DOI
|
18 |
Bharal, S. (2015). Review of Underwater Image Enhancement Techniques. International Research Journal of Engineering and Technology, 2(3), 340-344.
|
19 |
Fabbri, C., Islam, M.J., & Sattar, J. (2018, May). Enhancing Underwater Imagery Using Generative Adversarial Networks. In 2018 IEEE International Conference on Robotics and Automation (ICRA), 7159-7165. https://doi.org/10.1109/ICRA.2018.8460552
|
20 |
Kim, D.G., & Kim, S. M. (2020). Single Image-based Enhancement Techniques for Underwater Optical Imaging. Journal of Ocean Engineering and Technology, 34(6), 442-453. https://doi.org/10.26748/KSOE.2020.030
DOI
|
21 |
Mobley, C.D., & Mobley, C.D. (1994). Light and Water: Radiative Transfer in Natural Waters. Academic Press.
|
22 |
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, 2010, 1-14. https://doi.org/10.1155/2010/746052
DOI
|
23 |
Yang, M., & Sowmya, A. (2015). An Underwater Color Image Quality Evaluation Metric. IEEE Transactions on Image Processing, 24(12), 6062-6071. https://doi.org/10.1109/TIP.2015.2491020.
DOI
|