Journal
INFRARED PHYSICS & TECHNOLOGY
Volume 83, Issue -, Pages 94-102Publisher
ELSEVIER
DOI: 10.1016/j.infrared.2017.04.018
Keywords
Image fusion; Joint sparse representation; Saliency detection; Infrared image; Visible image
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Funding
- National Natural Science Foundation of China [61272348, 61572054]
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Infrared and visible image fusion is a key problem in the field of multi-sensor image fusion. To better preserve the significant information of the infrared and visible images in the final fused image, the saliency maps of the source images is introduced into the fusion procedure. Firstly, under the framework of the joint sparse representation (JSR) model, the global and local saliency maps of the source images are obtained based on sparse coefficients. Then, a saliency detection model is proposed, which combines the global and local saliency maps to generate an integrated saliency map. Finally, a weighted fusion algorithm based on the integrated saliency map is developed to achieve the fusion progress. The experimental results show that our method is superior to the state-of-the-art methods in terms of several universal quality evaluation indexes, as well as in the visual quality. (C) 2017 Elsevier B.V. All rights reserved.
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