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Proceedings Paper

Wavelet-based approach for the fusion of low-light image pairs
Author(s): Guangxia Wang; Xinbo Song; Meng Chang; Huajun Feng; Zhihai Xu; Qi Li
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Paper Abstract

When taking pictures in low-light scene, due to the insufficient light, we are often posed to the following problem: Using short exposure setting, image tends to be dim and noise, but with a sharp outline. While using longer exposure setting, image captures more color and detail information, but with partly blurred areas. A very common situation, none of those images is good enough. Good brightness and color information are retained in long-exposure images, while sharp outlines are retained in shorter ones. In this paper, we propose a fusion method based on wavelet decomposition for such low-light image pair. In this work, we firstly decompose the original image pair into different frequency subbands. After that, we compute the importance weight maps according to the difference value between corresponding subbands. In order to refuse artifacts and ghost, we compute weight maps in Gauss model. Finally, the coefficients of subbands are blended into a high-quality fusion image. Experimental results show that the proposed method effectively preserves sharp edges of the short-exposure image, and maintains the color, brightness, and details of the long-exposure image.

Paper Details

Date Published: 7 November 2018
PDF: 6 pages
Proc. SPIE 10832, Fifth Conference on Frontiers in Optical Imaging Technology and Applications, 108321A (7 November 2018); doi: 10.1117/12.2511400
Show Author Affiliations
Guangxia Wang, Zhejiang Univ. (China)
Xinbo Song, North Night-Vision Science & Technology Group Co., LTD (China)
Meng Chang, Zhejiang Univ. (China)
Huajun Feng, Zhejiang Univ. (China)
Zhihai Xu, Zhejiang Univ. (China)
Qi Li, Zhejiang Univ. (China)


Published in SPIE Proceedings Vol. 10832:
Fifth Conference on Frontiers in Optical Imaging Technology and Applications
Junhao Chu; Wenqing Liu; Huilin Jiang, Editor(s)

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