Name
Title | ||
|---|---|---|
Low-Light Image Enhancement Based On Retinex Decomposition And Adaptive Gamma Correction |
Abstract | ||
|---|---|---|
Low-light images suffer from poor visibility and noise. In this paper, a low-light image enhancement method based on Retinex decomposition is proposed. A pyramid network is first utilized to extract multi-scale features to improve the quality of Retinex decomposition. Then the decomposed illumination is refined via an adaptive Gamma correction network to handle non-uniform illumination, while the decomposed reflectance is refined with a lightweight network. Finally, the enhanced image is obtained by element-wise multiplication between the refined illumination and reflectance components. Quantitative and qualitative experiments demonstrate the superiority of our method over state-of-the-art image enhancement methods. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1049/ipr2.12097 | IET IMAGE PROCESSING |
DocType | Volume | Issue |
Journal | 15 | 5 |
ISSN | Citations | PageRank |
1751-9659 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jingyu Yang | 1 | 274 | 31.04 |
| Yuwei Xu | 2 | 0 | 0.34 |
| Huanjing Yue | 3 | 24 | 6.89 |
| Zhongyu Jiang | 4 | 6 | 2.12 |
| Kun Li | 5 | 1 | 1.69 |