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Contrastive Learning for Low-light Raw Denoising. (arXiv:2305.03352v1 [cs.CV])
cs.CV updates on arXiv.org arxiv.org
Image/video denoising in low-light scenes is an extremely challenging problem
due to limited photon count and high noise. In this paper, we propose a novel
approach with contrastive learning to address this issue. Inspired by the
success of contrastive learning used in some high-level computer vision tasks,
we bring in this idea to the low-level denoising task. In order to achieve this
goal, we introduce a new denoising contrastive regularization (DCR) to exploit
the information of noisy images and clean …
arxiv computer computer vision count denoising image issue light low noise novel paper photon raw success video video denoising vision