Visible and infrared images fusion target tracking based on deep learning, progress, and prospects

Due to the complementarity of visible and infrared images in target tracking, the target tracking of the fusion of the two has more advantages than traditional target tracking methods in performance and robustness. Recently, the development of artificial intelligence has promoted the progress of visible and infrared images fusion target tracking technology. This paper summarizes the infrared and visible images fusion algorithms in target tracking, introduces the research progress of image fusion technology in detail, and shows the research results of fusion algorithms. Based on the development history of this field, this paper summarizes the classic methods and emerging technologies in recent years. What’s more, a network is designed based on the transformer network structure combined with the feature fusion module. The experimental results show that the comprehensive performance of the transformer-based network is improved by nearly 1%. It proves that the transformer-based network has great application potential in the target tracking network of visible and infrared images fusion.