@inproceedings{041f93cd63a24e9b8167e363ef9a8d2d,
title = "Model-Driven Deep Unfolding Approach to Underwater Image Enhancement",
abstract = "We propose a model-driven deep learning approach to underwater image enhancement that can take advantage of both model- and learning-based approaches. We first formulate a joint optimization problem with physical priors to estimate the transmission map and latent clear image. Then, we solve the optimization problem iteratively. At each iteration, the optimization variables and image priors are updated by closed-form solutions and learned deep neural networks, respectively. Experimental results show that the proposed algorithm outperforms state-of-the-art underwater image enhancement algorithms.",
keywords = "deep unfolding, Image restoration, underwater images",
author = "Pham, {Thuy Thi} and {Nhat Mai}, {Truong Thanh} and Chul Lee",
note = "Publisher Copyright: {\textcopyright} 2023 SPIE.; 2023 International Workshop on Advanced Imaging Technology, IWAIT 2023 ; Conference date: 09-01-2023 Through 11-01-2023",
year = "2023",
doi = "10.1117/12.2666202",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Masayuki Nakajima and Jae-Gon Kim and Kwang-deok Seo and Toshihiko Yamasaki and Jing-Ming Guo and Lau, {Phooi Yee} and Qian Kemao",
booktitle = "International Workshop on Advanced Imaging Technology, IWAIT 2023",
address = "United States",
}