Paper
7 December 2023 LIGI: low-light image enhancement via gray image
Yue Sun, Qihong Ye, Hongming Chen, Xiaoshuang Wang
Author Affiliations +
Proceedings Volume 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023); 1294144 (2023) https://doi.org/10.1117/12.3011571
Event: Third International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 203), 2023, Yinchuan, China
Abstract
Low-light images are usually affected by problems such as low illumination, noise, and color distortion, resulting in unsatisfactory image enhancement. Low-light image enhancement aims to improve the quality and visibility of low-light images. In this paper, a gray image based low-light image enhancement deep learning method is proposed, which converts the low-light image to gray image and then extracts the important information in the image as branches to assist the main network. To achieve better enhancement performance, we proposed denoising center block (DC block), which focusing on color restoration and information preservation. The experimental results show that the method proposed in this paper outperforms the existing low-light image enhancement methods in both objective and subjective evaluation metrics, and can effectively improve the clarity, contrast, and color reproduction of low-light images.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Yue Sun, Qihong Ye, Hongming Chen, and Xiaoshuang Wang "LIGI: low-light image enhancement via gray image", Proc. SPIE 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023), 1294144 (7 December 2023); https://doi.org/10.1117/12.3011571
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KEYWORDS
Image enhancement

Image processing

Education and training

Denoising

Feature extraction

Video

Video surveillance

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