A Comprehensive Survey on Image Dehazing Based on Deep Learning

Gui, Jie; Cong, Xiaofeng; Cao, Yuan; Ren, Wenqi; Zhang, Jun; Zhang, Jing; Tao, Dacheng

doi:10.24963/ijcai.2021/604

A Comprehensive Survey on Image Dehazing Based on Deep Learning

Jie Gui, Xiaofeng Cong, Yuan Cao, Wenqi Ren, Jun Zhang, Jing Zhang, Dacheng Tao

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Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence. Survey Track. Pages 4426-4433.

https://doi.org/10.24963/ijcai.2021/604

Keywords

Machine learning: General
Computer vision: General

Abstract

The presence of haze significantly reduces the quality of images. Researchers have designed a variety of algorithms for image dehazing (ID) to restore the quality of hazy images. However, there are few studies that summarize the deep learning (DL) based dehazing technologies. In this paper, we conduct a comprehensive survey on the recent proposed dehazing methods. Firstly, we conclude the commonly used datasets, loss functions and evaluation metrics. Secondly, we group the existing researches of ID into two major categories: supervised ID and unsupervised ID. The core ideas of various influential dehazing models are introduced. Finally, the open issues for future research on ID are pointed out.

Jie Gui, Xiaofeng Cong, Yuan Cao, Wenqi Ren, Jun Zhang, Jing Zhang, and Dacheng Tao. 2021. A Comprehensive Survey on Image Dehazing Based on Deep Learning. In Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21. IJCAI, 4426–4433. https://doi.org/10.24963/ijcai.2021/604

@inproceedings{ijcai2021p604,
  title     = {A Comprehensive Survey on Image Dehazing Based on Deep Learning},
  author    = {Gui, Jie and Cong, Xiaofeng and Cao, Yuan and Ren, Wenqi and Zhang, Jun and Zhang, Jing and Tao, Dacheng},
  booktitle = {Proceedings of the Thirtieth International Joint Conference on
               Artificial Intelligence, {IJCAI-21}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Prof. Zhi-Hua Zhou},
  pages     = {4426--4433},
  year      = {2021},
  month     = {8},
  note      = {Survey Track},
  doi       = {10.24963/ijcai.2021/604},
  url       = {https://doi.org/10.24963/ijcai.2021/604},
}

TY  - CPAPER
TI  - A Comprehensive Survey on Image Dehazing Based on Deep Learning
AU  - Gui, Jie
AU  - Cong, Xiaofeng
AU  - Cao, Yuan
AU  - Ren, Wenqi
AU  - Zhang, Jun
AU  - Zhang, Jing
AU  - Tao, Dacheng
T2  - Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21
PB  - International Joint Conferences on Artificial Intelligence Organization
PY  - 2021
SP  - 4426
EP  - 4433
DO  - 10.24963/ijcai.2021/604
UR  - https://doi.org/10.24963/ijcai.2021/604
ER  -