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LLDiffusion: Learning degradation representations in diffusion models for low-light image enhancement
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“Both PDB and MPB adopt convolution-based architectures to preserve local details and high-frequency components of the moir´ e pattern, following the findings in [47].”
From MoCHA-former: Moiré-Conditioned Hybrid Adaptive Transformer for Video Demoiréing (2026) · cites this paper as [47]
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Metadata
- Authors
- Wang, T., Zhang, K., Zhang, Y., Luo, W., Stenger, B., Lu, T., Kim, T.-K., & Liu, W.
- Affiliations
- Nanjing University (CN)
- Tencent (China) (CN)
- Hong Kong University of Science and Technology (HK)
- Rakuten (Japan) (JP)
- Korea Advanced Institute of Science and Technology (KR)
- Corresponding author
- Luo, Wenhan
- Venue
- Pattern Recognition
- Publisher
- Elsevier BV
- Published
- 2025-10
- Volume
- 166
- Pages
- 111628
- ISSN
- 0031-3203 (ISSN-L)
- OpenAlex
- W4409349224
- Cited by
- 150
- References
- 54
- Citations by year
- 2026: 87 · 2025: 56
- FWCI
- 50.38
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Licence
- Locations
- Pattern Recognition (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- Rare & Special e-Zone (The Hong Kong University of Science and Technology) (submittedVersion)
- arXiv (Cornell University)
- Funders
- National Natural Science Foundation of China (U24A20330, 62372480, 62372223)
- China Computer Federation
- Natural Science Foundation of Shenzhen Municipality (JCYJ20240813110459017)
- Basic and Applied Basic Research Foundation of Guangdong Province (2025A1515011361)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image Enhancement Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Image Processing Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image and Signal Denoising Methods
- Keywords
- low-light image enhancement, diffusion models, noise amplification, color distortion, contrast reduction, image priors
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