Infrared and visible image fusion method based on saliency detection in sparse domain |
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| Affiliation: | 1. Institute of Unmanned System, Beihang University, Xueyuan Road, Haidian District, 100191 Beijing, China;2. State Key Laboratory of Virtual Reality Technology and System, Beihang University, NO. 37 Xueyuan Road, Haidian District, 100191 Beijing, China;1. Computer Vision and Systems Laboratory, Laval University, Quebec City, Quebec, G1K 7P4, Canada;2. Las.E.R. Laboratory, Dept. of Industrial and Information Engineering and Economics (DIIIE), University of L''Aquila, Monteluco di Roio - L''Aquila (AQ), 67100, Italy;3. Visiooimage Inc, Infrared Vision Systems, 2604 Lapointe, Quebec City, Quebec, G1W 1A8, Canada;1. Department of Electronic & Computer Engineering, Ngee Ann Polytechnic, 535 Clementi Rd, S599489, Singapore;2. Department of Biomedical Engineering, Faculty of Engineering, University of Malaya, Malaysia;3. Department of Biomedical Engineering, School of Science and Technology, SIM University, 599491, Singapore;1. Department of Physics, Xiamen University, Xiamen 361005, Fujian, People''s Republic of China;2. Department of Electrical and Computer Engineering, National University of Singapore, Singapore 119260, Singapore;3. Key Laboratory of Semiconductor Materials Science, Institute of Semiconductors, Chinese Academy of Sciences, Beijing 100083, People''s Republic of China;1. Life and Health Sciences Research Institute (ICVS), School of Health Sciences, University of Minho, Campus de Gualtar, 4710-057 Braga, Portugal;2. ICVS/3B’s PT Government Associate Laboratory, Braga/Guimarães, Portugal;3. Department of Obstetrics and Gynecology, Hospital de Braga, 4710-243 Braga, Portugal;4. Polytechnic Institute of Cavado and Ave, Campus do IPCA, 4750-810 Barcelos, Portugal;5. Institute for Polymers and Composites IPC/I3N, University of Minho, Campus de Azurm, 4800-058 Guimarães, Portugal |
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| Abstract: | 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. |
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| Keywords: | Image fusion Joint sparse representation Saliency detection Infrared image Visible image |
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