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CodeEnhance: A Codebook-Driven Approach for Low-Light Image Enhancement
April 9, 2024, 4:47 a.m. | Xu Wu, XianXu Hou, Zhihui Lai, Jie Zhou, Ya-nan Zhang, Witold Pedrycz, Linlin Shen
cs.CV updates on arXiv.org arxiv.org
Abstract: Low-light image enhancement (LLIE) aims to improve low-illumination images. However, existing methods face two challenges: (1) uncertainty in restoration from diverse brightness degradations; (2) loss of texture and color information caused by noise suppression and light enhancement. In this paper, we propose a novel enhancement approach, CodeEnhance, by leveraging quantized priors and image refinement to address these challenges. In particular, we reframe LLIE as learning an image-to-code mapping from low-light images to discrete codebook, which …
abstract arxiv challenges color cs.cv diverse face however image images information light loss low noise novel paper texture type uncertainty
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