A review: underwater image enhancement based on deep learning

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.

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Publication Details

Published
2024-09-10
DOI
https://doi.org/10.1117/12.3040459
Citations
2
Primary Topic
Image Enhancement Techniques
Type
article
Field-Weighted Citation Impact
0.50
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article

A review: underwater image enhancement based on deep learning

Yifan Liu, Yongxiang Chen, Yinyi Lai, Yibei Wu
2 citations
Image Enhancement Techniques
0.50
article

A review: underwater image enhancement based on deep learning

Yifan Liu, Yongxiang Chen, Yinyi Lai, Yibei Wu
article en
2 citations

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.

Hohai University (CN), Henan University of Technology (CN)
Openalex Percentile: Top 35%
Image Enhancement Techniques
0.50
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