A detail-preserved and luminance-consistent multi-exposure image fusion algorithm

Guanquan Wang; Yue Zhou

doi:10.1117/12.2309479

13 April 2018 A detail-preserved and luminance-consistent multi-exposure image fusion algorithm

Guanquan Wang, Yue Zhou

Proceedings Volume 10696, Tenth International Conference on Machine Vision (ICMV 2017); 106961E (2018) https://doi.org/10.1117/12.2309479
Event: Tenth International Conference on Machine Vision, 2017, Vienna, Austria

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.

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Guanquan Wang and Yue Zhou "A detail-preserved and luminance-consistent multi-exposure image fusion algorithm", Proc. SPIE 10696, Tenth International Conference on Machine Vision (ICMV 2017), 106961E (13 April 2018); https://doi.org/10.1117/12.2309479

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KEYWORDS

Image fusion

Image segmentation

Image processing

Image filtering

Image processing algorithms and systems

Image quality

Bismuth

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