mlsanityData to 7 Oct 2026

A Comprehensive Survey on Underwater Image Enhancement Based on Deep Learning

arXiv 2405.19684 ↗First posted 30 May 2024cs.CVcited by 9

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Abstract (arXiv)

Underwater image enhancement (UIE) presents a significant challenge within computer vision research. Despite the development of numerous UIE algorithms, a thorough and systematic review is still absent. To foster future advancements, we provide a detailed overview of the UIE task from several perspectives. Firstly, we introduce the physical models, data construction processes, evaluation metrics, and loss functions. Secondly, we categorize and discuss recent algorithms based on their contributions, considering six aspects: network architecture, learning strategy, learning stage, auxiliary tasks, domain perspective, and disentanglement fusion. Thirdly, due to the varying experimental setups in the existing literature, a comprehensive and unbiased comparison is currently unavailable. To address this, we perform both quantitative and qualitative evaluations of state-of-the-art algorithms across multiple benchmark datasets. Lastly, we identify key areas for future research in UIE. A collection of resources for UIE can be found at {https://github.com/YuZhao1999/UIE}.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 66 of its 193 references that are in the map. First posted on arXiv 30 May 2024.

Builds on

66 of 193 references.

References · 66

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38 more
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50 most cited of 66 All 66 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 6; 2026: 2.

9 papers.

  1. 2025WWE-UIE: A Wavelet & White Balance Efficient Network for Underwater Image Enhancementcited by 3
  2. 2025FUSION: Frequency-guided Underwater Spatial Image recOnstructioNcited by 1
  3. 2025Underwater Diffusion Attention Network with Contrastive Language-Image Joint Learning for Underwater Image Enhancementcited by 1
  4. 2025DISC-GAN: Disentangling Style and Content for Cluster-Specific Synthetic Underwater Image Generationcited by 1
  5. 2025MuS-Polar3D: A Benchmark Dataset for Computational Polarimetric 3D Imaging under Multi-Scattering Conditionscited by 1
  6. 2024Underwater Organism Color Enhancement via Color Code Decomposition, Adaptation and Interpolationcited by 0
  7. 2025TIDE: Two-Stage Inverse Degradation Estimation with Guided Prior Disentanglement for Underwater Image Restorationcited by 0
  8. 2026Real-Time Underwater Image Enhancement via Frequency-Guided Dual-Path Attentioncited by 0
  9. 2026π-SUB: A Physics-Informed Synthetic Underwater Benchmark Dataset for Underwater Image Enhancementcited by 0