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Due to the selective absorption and scattering of light by diverse aquatic media, underwater images usually suffer from various visual degradations.
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2013
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2015
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2015
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2016
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2016
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2016
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2017
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2017
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2017
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2017
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2018
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2018
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2018
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2019
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D. Akkaynak and T. Treibitz, “Sea-thru: A method for removing water from underwater images,” in Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , 2019, pp. 1682–1691
2019
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K. A. Skinner, J. Zhang, E. A. Olson, and M. Johnson-Roberson, “Uwstereonet: Unsupervised learning for depth estimation and color correction of underwater stereo imagery,” in 2019 International Conference on Robotics and Automation (ICRA) . IEEE, 2019, pp. 7947–7954
2019
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2019
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L. Peng, C. Zhu, and L. Bian, “U-shape transformer for underwater image enhancement,” IEEE Transactions on Image Processing , 2023
2023
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2023
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2023
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2023
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2019
Cited alongside, same era.
T. Porto Marques, A. Branzan Albu, and M. Hoeberechts, “A contrast-guided approach for the enhancement of low-lighting underwater images,” Journal of Imaging , vol. 5, no. 10, p. 79, 2019
2019
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2020
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M. J. Islam, Y. Xia, and J. Sattar, “Fast underwater image enhancement for improved visual perception,” IEEE Robotics and Automation Letters , vol. 5, no. 2, pp. 3227–3234, 2020
2020
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T. P. Marques and A. B. Albu, “L2uwe: A framework for the efficient enhancement of low-light underwater images using local contrast and multi-scale fusion,” in Proceedings of the IEEE/CVF conference on computer vision and pattern recognition workshops , 2020, pp. 538–539
2020
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D. Berman, D. Levy, S. Avidan, and T. Treibitz, “Underwater single image color restoration using haze-lines and a new quantitative dataset,” IEEE transactions on pattern analysis and machine intelligence , vol. 43, no. 8, pp. 2822–2837, 2020
2020
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X. Cao, S. Rong, Y. Liu, T. Li, Q. Wang, and B. He, “Nuicnet: Non-uniform illumination correction for underwater image using fully convolutional network,” IEEE Access , vol. 8, pp. 109 989–110 002, 2020
2020
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R. Ranftl, K. Lasinger, D. Hafner, K. Schindler, and V. Koltun, “Towards robust monocular depth estimation: Mixing datasets for zero-shot cross-dataset transfer,” IEEE transactions on pattern analysis and machine intelligence , vol. 44, no. 3, pp. 1623–1637, 2020
2020
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N. Varghese, A. Kumar, and A. Rajagopalan, “Self-supervised monocular underwater depth recovery, image restoration, and a real-sea video dataset,” in Proceedings of the IEEE/CVF International Conference on Computer Vision , 2023, pp. 12 248–12 258
2023
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G. Hou, N. Li, P. Zhuang, K. Li, H. Sun, and C. Li, “Non-uniform illumination underwater image restoration via illumination channel sparsity prior,” IEEE Transactions on Circuits and Systems for Video Technology , 2023
2023
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W. Zhang, L. Zhou, P. Zhuang, G. Li, X. Pan, W. Zhao, and C. Li, “Underwater image enhancement via weighted wavelet visual perception fusion,” IEEE Transactions on Circuits and Systems for Video Technology , vol. 34, no. 4, pp. 2469–2483, 2023
2023
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2023
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2023
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2023
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M. Li, K. Wang, L. Shen, Y. Lin, Z. Wang, and Q. Zhao, “Uialn: Enhancement for underwater image with artificial light,” IEEE Transactions on Circuits and Systems for Video Technology , 2023
2023
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2023
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2023
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2023
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Z. Cheng, G. Fan, J. Zhou, M. Gan, and C. P. Chen, “Fdce-net: underwater image enhancement with embedding frequency and dual color encoder,” IEEE Transactions on Circuits and Systems for Video Technology , 2024
2024
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J. Zhou, Q. Gai, D. Zhang, K.-M. Lam, W. Zhang, and X. Fu, “Iacc: Cross-illumination awareness and color correction for underwater images under mixed natural and artificial lighting,” IEEE Transactions on Geoscience and Remote Sensing , vol. 62, pp. 1–15, 2024
2024
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L. Yang, B. Kang, Z. Huang, X. Xu, J. Feng, and H. Zhao, “Depth anything: Unleashing the power of large-scale unlabeled data,” in CVPR , 2024
2024
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F. Zhang, S. You, Y. Li, and Y. Fu, “Atlantis: Enabling underwater depth estimation with stable diffusion,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2024, pp. 11 852–11 861
2024
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2024
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T. Cheng, L. Song, Y. Ge, W. Liu, X. Wang, and Y. Shan, “Yolo-world: Real-time open-vocabulary object detection,” in Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR) , 2024
2024
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X. Guo, Y. Dong, X. Chen, W. Chen, Z. Li, F. Zheng, and C.-M. Pun, “Underwater image restoration via polymorphic large kernel cnns,” in ICASSP 2025-2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) . IEEE, 2025, pp. 1–5
2025
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