Abstract
This paper analyses the characteristics of infrared detection imaging, with the specific application of multi-scale analysis theory for SAR and infrared image fusion. After learning and discussing the research results in image fusion area at home and abroad, it proposes an adaptive weighted image fusion method which combines the idea of fuzzy theory based on Curvelet transform, i.e., defines the membership function with fuzzy logic variables, makes different weights to transform coefficients of different levels, and designs a kind of adaptive weighted image fusion strategy. Experimental results validate the reliability and credibility of this method in term of visual quality and objective evaluation, and it can effectively improve the fusion quality.
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Acknowledgments
The authors would like to thank the anonymous reviewers for their helpful comments and advices which contributed much to the improvement of this paper. The work was jointly supported by the National Science Foundation of China under grant No. 61471191, the Natural Science Foundation of Jiangsu colleges and universities under grant No. 14KJD510004, 15KJB590001.
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Ji, X., Zhang, G. Image fusion method of SAR and infrared image based on Curvelet transform with adaptive weighting. Multimed Tools Appl 76, 17633–17649 (2017). https://doi.org/10.1007/s11042-015-2879-8
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DOI: https://doi.org/10.1007/s11042-015-2879-8