Low-Light Image and Video Enhancement Using Deep Learning: A Survey.

@article{Li2021LowLightIA,
  title={Low-Light Image and Video Enhancement Using Deep Learning: A Survey.},
  author={Chongyi Li and Chunle Guo and Linghao Han and Jun Jiang and Mingg-Ming Cheng and Jinwei Gu and Chen Change Loy},
  journal={IEEE transactions on pattern analysis and machine intelligence},
  year={2021},
  volume={PP}
}
Low-light image enhancement (LLIE) aims at improving the perception or interpretability of an image captured in an environment with poor illumination. Recent advances in this area are dominated by deep learning-based solutions, where many learning strategies, network structures, loss functions, training data, etc. have been employed. In this paper, we provide a comprehensive survey to cover various aspects ranging from algorithm taxonomy to unsolved open issues. To examine the generalization of… 
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