Low-light image enhancement: A comparative review and prospects

W Kim - IEEE Access, 2022‏ - ieeexplore.ieee.org
Low-light image enhancement is a key prerequisite for diverse applications in the field of
image processing and computer vision. Various approaches for this task have been …

Retinexformer: One-stage retinex-based transformer for low-light image enhancement

Y Cai, H Bian, J Lin, H Wang… - Proceedings of the …, 2023‏ - openaccess.thecvf.com
When enhancing low-light images, many deep learning algorithms are based on the Retinex
theory. However, the Retinex model does not consider the corruptions hidden in the dark or …

Snr-aware low-light image enhancement

X Xu, R Wang, CW Fu, J Jia - Proceedings of the IEEE/CVF …, 2022‏ - openaccess.thecvf.com
This paper presents a new solution for low-light image enhancement by collectively
exploiting Signal-to-Noise-Ratio-aware transformers and convolutional models to …

Learning semantic-aware knowledge guidance for low-light image enhancement

Y Wu, C Pan, G Wang, Y Yang, J Wei… - Proceedings of the …, 2023‏ - openaccess.thecvf.com
Low-light image enhancement (LLIE) investigates how to improve illumination and produce
normal-light images. The majority of existing methods improve low-light images via a global …

Low-light image enhancement via structure modeling and guidance

X Xu, R Wang, J Lu - … of the IEEE/CVF Conference on …, 2023‏ - openaccess.thecvf.com
This paper proposes a new framework for low-light image enhancement by simultaneously
conducting the appearance as well as structure modeling. It employs the structural feature to …

Global structure-aware diffusion process for low-light image enhancement

J Hou, Z Zhu, J Hou, H Liu, H Zeng… - Advances in Neural …, 2023‏ - proceedings.neurips.cc
This paper studies a diffusion-based framework to address the low-light image
enhancement problem. To harness the capabilities of diffusion models, we delve into this …

Deep fourier-based exposure correction network with spatial-frequency interaction

J Huang, Y Liu, F Zhao, K Yan, J Zhang… - … on Computer Vision, 2022‏ - Springer
Images captured under incorrect exposures unavoidably suffer from mixed degradations of
lightness and structures. Most existing deep learning-based exposure correction methods …

LightingNet: An integrated learning method for low-light image enhancement

S Yang, D Zhou, J Cao, Y Guo - IEEE Transactions on …, 2023‏ - ieeexplore.ieee.org
Images captured in low-light environments suffer from serious degradation due to insufficient
light, leading to the performance decline of industrial and civilian devices. To address the …

You only need 90k parameters to adapt light: a light weight transformer for image enhancement and exposure correction

Z Cui, K Li, L Gu, S Su, P Gao, Z Jiang, Y Qiao… - arxiv preprint arxiv …, 2022‏ - arxiv.org
Challenging illumination conditions (low-light, under-exposure and over-exposure) in the
real world not only cast an unpleasant visual appearance but also taint the computer vision …

Low-light image and video enhancement: A comprehensive survey and beyond

S Zheng, Y Ma, J Pan, C Lu, G Gupta - arxiv preprint arxiv:2212.10772, 2022‏ - arxiv.org
This paper presents a comprehensive survey of low-light image and video enhancement,
addressing two primary challenges in the field. The first challenge is the prevalence of mixed …