A review: underwater image enhancement based on deep learning

Yifan Liu; Yinyi Lai; Yibei Wu; Yongxiang Chen

doi:10.1117/12.3040459

10 September 2024 A review: underwater image enhancement based on deep learning

Yifan Liu, Yinyi Lai, Yibei Wu, Yongxiang Chen

Author Affiliations +

Proceedings Volume 13257, International Conference on Advanced Image Processing Technology (AIPT 2024); 1325704 (2024) https://doi.org/10.1117/12.3040459
Event: International Conference on Advanced Image Processing Technology (AIPT 2024), 2024, Chongqing, China

Abstract

The continuous advancement in the field of deep learning has increasingly drawn attention to underwater image enhancement as a pivotal area of research in underwater robotics. Deep learning techniques have demonstrated significant progress in this domain, furnishing robust tools to tackle image quality challenges in underwater environments. This review presents a comprehensive overview of various deep learning applications in underwater image enhancement, elucidating the scope of each model's utilization while also delineating current challenges and proposing future research directions within the field. The primary objective of this review is to consolidate the latest research advancements in underwater image enhancement through deep learning methodologies, providing researchers with an up-to-date understanding and reference framework to stimulate further progress in this domain.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yifan Liu, Yinyi Lai, Yibei Wu, and Yongxiang Chen "A review: underwater image enhancement based on deep learning", Proc. SPIE 13257, International Conference on Advanced Image Processing Technology (AIPT 2024), 1325704 (10 September 2024); https://doi.org/10.1117/12.3040459

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