Abstract
With the development of multi-source detectors, the fusion of infrared and visible light images has received close attention from researchers. Infrared images have the advantages of all-day time, and can clearly image temperature-sensitive targets under low or no light conditions. Visible light images have strong imaging capabilities for target details under good lighting conditions. After the two are fused, the advantages of the two imaging methods can be integrated. In this paper, to obtain more valuable scene information in the fused image, an infrared and visible image fusion method based on multi-scale Gaussian rolling guidance filter (MLRGF) decomposition is proposed. First of all, the MLRGF is utilized to decompose infrared images and visible light images into three different scale layers, which are called detail preservation layer, edge preservation layer and energy base layer, respectively. Then, the three different scale layers are respectively fused based on the properties of different scale layers through spatial frequency-based, gradient-based and energy-based fusion strategies. Finally, the final fusion result is obtained by adding the fusion results of the three different scale layers. Experimental results show that the proposed method has achieved excellent results in both subjective evaluation and objective evaluation.
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Zhang, J., **ang, P., Teng, X., Zhang, X., Zhou, H. (2022). Infrared and Visible Image Fusion Based on Multi-scale Gaussian Rolling Guidance Filter Decomposition. In: Berretti, S., Su, GM. (eds) Smart Multimedia. ICSM 2022. Lecture Notes in Computer Science, vol 13497. Springer, Cham. https://doi.org/10.1007/978-3-031-22061-6_6
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