BVI-Lowlight: Fully registered datasets for low-light image and video enhancement

Low-light images and video footage often exhibit issues due to the interplay of various parameters such as aperture, shutter speed, and ISO settings. These interactions can lead to distortions, especially in extreme lighting conditions. This distortion is primarily caused by the inverse relationship between decreasing light intensity and increasing photon noise, which gets amplified with higher sensor gain. Additionally, secondary characteristics like white balance and color effects can also be adversely affected and may require post-processing correction. These distortions not only impact the perceived quality of the images but also pose significant challenges for machine learning tasks, including classification and object detection. This is particularly evident when considering the susceptibility of deep learning networks to adversarial examples.

The BVI-Lowlight datasets offer fully registered low-light content alongside their corresponding clean and normal light condition. This dataset includes both images and videos, enabling the use of supervised learning approaches and performance evaluation through objective metrics such as PSNR and SSIM.

Two datasets are available:

BVI-RLV: Fully Registered Low-Light Videos (BVI-Lowlight-videos):

In this video pair dataset, we recorded low-light videos at both 10% and 20% of normal lighting levels (100%), indicated by the Zero 88 FLX S24 light controller. We provide these videos in full HD resolution. There are total 40 scenes, including 6 scenes of static background. More detail at: https://arxiv.org/abs/2407.03535

BVI-Lowlight-Images:

The description can be found on https://github.com/malalejandra/bvi-lowlight

Benchmarks for Low-Light Video Enhancement:

• PCDUNet: https://github.com/lrr-rachel/PCDUNet
• STA-SUNet: https://github.com/lrr-rachel/STA-SUNet
• BVI-CDM: https://github.com/lrr-rachel/BVI-CDM
• BVI-Mamba: https://github.com/russellllaputa/BVI-Mamba

Please cite R. Lin, N. Anantrasirichai, G. Huang, J. Lin, Q. Sun, A. Malyugina, and D.R. Bull. BVI-RLV: A fully registered dataset and benchmarks for low-light video enhancement. arXiv preprint arXiv:2407.03535, 2024.