Abstract
Cameras usually produce low-quality images under low-light conditions. Though many methods have been proposed to enhance the visibility of low-light images, they are mainly designed for illumination correction and less capable of sup-pressing the artifacts. In this paper, we propose to enhance the visibility and suppress artifacts by purifying low-light images under the guidance of the NIR enlightened image captured by using the near-infrared light as compensation. Specifically, we introduce a disentanglement framework to disentangle the structure and color components from the NIR enlightened and RGB images, respectively. Correspondingly, we introduce a new dataset with the RGB and NIR enlightened images for training and evaluation purposes. The experimental results show that our proposed method achieves promising results.
Original language | English |
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Article number | 9999306 |
Pages (from-to) | 1-13 |
Number of pages | 13 |
Journal | IEEE Transactions on Multimedia |
DOIs | |
Publication status | E-pub ahead of print - 26 Dec 2022 |
Scopus Subject Areas
- Signal Processing
- Electrical and Electronic Engineering
- Media Technology
- Computer Science Applications
User-Defined Keywords
- Cameras
- Image color analysis
- Image enhancement
- Image restoration
- Lighting
- Surveillance
- Training