Channel and Spatial Transformer for Underwater Image Enhancement

Jiayi Li, Xiaoyue Jiang, Mengyi Yan, Yuanbo Ren, Zhaoqiang Xia, Xiaoyi Feng

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Underwater images always suffered from significant degradation, such as color deviation, low contrast and blurred details. Underwater image enhancement is an essential step to improve the image quality. However, the existing underwater image enhancement results always have the problem of colour bias, and do not consider the non-uniform attenuation in different color channels. In this paper, a channel and spatial (CS) transformer module is proposed for the underwater image enhancement, where multi-dimensional attention is extracted from the deep features. The channel-level multiscale feature fusion (CMFT) module focuses on the channel with severe color attenuation. The spatial-level attention module(SAT) focuses on the degraded regions in spatial domain. Furthermore, a new loss function that combines perceptual losses in RGB, LAB and LCH colour spaces is proposed to correct color distoration and improve image details. A large number of experiments on existing datasets have verified the excellent performance of the proposed networks.

源语言英语
主期刊名Proceedings - 2023 2nd International Conference on Image Processing and Media Computing, ICIPMC 2023
出版商Institute of Electrical and Electronics Engineers Inc.
15-20
页数6
ISBN(电子版)9798350326611
DOI
出版状态已出版 - 2023
活动2nd International Conference on Image Processing and Media Computing, ICIPMC 2023 - Xi�an, 中国
期限: 26 5月 202328 5月 2023

出版系列

姓名Proceedings - 2023 2nd International Conference on Image Processing and Media Computing, ICIPMC 2023

会议

会议2nd International Conference on Image Processing and Media Computing, ICIPMC 2023
国家/地区中国
Xi�an
时期26/05/2328/05/23

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