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An infrared and visible image fusion algorithm based on MAP
Author(s): Kai Kang; Tingting Liu; Tianyun Wang; Fuchun Nian; Xianchun Xu
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Paper Abstract

This paper deals with infrared and visible image fusion problems by maximum a posteriori probability (MAP) estimation. We use imaging mode to construct the conditional probability distribution, assume the fusion image approximate the visible image, and treat sparse property of image gradient as fusion image prior probability distribution. According Bayesian theorem, the fusion image’s posterior probability distribution is deduced. The fusion results are obtained by maxim the posterior probability distribution. In experiments, we conduct subjective and objective evaluation. The comparisons show that the MAP-based image fusion method has better performance in both subjective and objective evaluations. The MAP-based image fusion method can be applied to image interpretation, detection and recognition tasks.

Paper Details

Date Published: 14 February 2019
PDF: 5 pages
Proc. SPIE 11048, 17th International Conference on Optical Communications and Networks (ICOCN2018), 1104810 (14 February 2019); doi: 10.1117/12.2519624
Show Author Affiliations
Kai Kang, China Satellite Maritime Tracking and Control Dept. (China)
Tingting Liu, China Satellite Maritime Tracking and Control Dept. (China)
Tianyun Wang, China Satellite Maritime Tracking and Control Dept. (China)
Fuchun Nian, China Satellite Maritime Tracking and Control Dept. (China)
Xianchun Xu, China Satellite Maritime Tracking and Control Dept. (China)


Published in SPIE Proceedings Vol. 11048:
17th International Conference on Optical Communications and Networks (ICOCN2018)
Zhaohui Li, Editor(s)

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