Robust underwater image enhancement with cascaded multi-level sub-networks and triple attention mechanism

Author:

Zhang Dehuan,Wu Chenyu,Zhou JingchunORCID,Zhang Weishi,Lin ZifanORCID,Polat Kemal,Alenezi Fayadh

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Fundamental Research Funds for Central Universities of the Central South University

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience

Reference72 articles.

1. Akkaynak, D., & Treibitz, T. (2019). Sea-thru: A method for removing water from underwater images. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition (pp. 1682–1691).

2. Color balance and fusion for underwater image enhancement;Ancuti;IEEE Transactions on Image Processing,2017

3. Diving deeper into underwater image enhancement: A survey;Anwar;Signal Processing: Image Communication,2020

4. Underwater single image color restoration using haze-lines and a new quantitative dataset;Berman;IEEE Transactions on Pattern Analysis and Machine Intelligence,2020

5. Gcnet: Non-local networks meet squeeze-excitation networks and beyond;Cao,2019

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