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A detail-preserved and luminance-consistent multi-exposure image fusion algorithm
Author(s): Guanquan Wang; Yue Zhou
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Paper Abstract

When irradiance across a scene varies greatly, we can hardly get an image of the scene without over- or underexposure area, because of the constraints of cameras. Multi-exposure image fusion (MEF) is an effective method to deal with this problem by fusing multi-exposure images of a static scene. A novel MEF method is described in this paper. In the proposed algorithm, coarser-scale luminance consistency is preserved by contribution adjustment using the luminance information between blocks; detail-preserved smoothing filter can stitch blocks smoothly without losing details. Experiment results show that the proposed method performs well in preserving luminance consistency and details.

Paper Details

Date Published: 13 April 2018
PDF: 6 pages
Proc. SPIE 10696, Tenth International Conference on Machine Vision (ICMV 2017), 106961E (13 April 2018); doi: 10.1117/12.2309479
Show Author Affiliations
Guanquan Wang, Shanghai Jiao Tong Univ. (China)
Yue Zhou, Shanghai Jiao Tong Univ. (China)


Published in SPIE Proceedings Vol. 10696:
Tenth International Conference on Machine Vision (ICMV 2017)
Antanas Verikas; Petia Radeva; Dmitry Nikolaev; Jianhong Zhou, Editor(s)

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