Low-Light Enhancement Using a Plug-and-Play Retinex Model With Shrinkage Mapping for Illumination Estimation

Author:

Lin Yi-Hsien1ORCID,Lu Yi-Chang1ORCID

Affiliation:

1. Graduate Institute of Electronics Engineering, National Taiwan University, Taipei, Taiwan

Funder

Ministry of Science and Technology, Taiwan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Graphics and Computer-Aided Design,Software

Cited by 24 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Low-light image enhancement based on cell vibration energy model and lightness difference;Computer Vision and Image Understanding;2024-10

2. A Deep Retinex-Based Low-Light Enhancement Network Fusing Rich Intrinsic Prior Information;ACM Transactions on Multimedia Computing, Communications, and Applications;2024-08-23

3. A low-light image enhancement model based on anisotropic weighted exponential local derivatives;Digital Signal Processing;2024-08

4. Low-Light Image Enhancement via Weighted Low-Rank Tensor Regularized Retinex Model;Proceedings of the 2024 International Conference on Multimedia Retrieval;2024-05-30

5. Joint Self-Supervised Enhancement and Denoising of Low-Light Images;IEEE Transactions on Emerging Topics in Computational Intelligence;2024-04

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