Infrared point target detection with improved template matching |
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| Authors: | Ruiming Liu Yanhong Lu Chenglong Gong Yang Liu |
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| Institution: | 1. School of Electronic Engineering, Huaihai Institute of Technology, No. 59 Cangwu Road, Xinpu District, Lianyungang 222005, China;2. Lianyungang Technical College, No. 2 Chenguang Road, Lianyungang 222006, China;3. School of Foreign Languages, Huaihai Institute of Technology, No. 59 Cangwu Road, Xinpu District, Lianyungang 222005, China;1. College of Information Technology, Harbin Engineering University, Harbin, China;2. Wuhan Digital Engineering Research Institute, Wuhan, China;1. School of Communication and Information Engineering, Shanghai University, China;2. Key Laboratory of Advanced Displays and System Application, Ministry of Education, China;1. Image Processing Center, Beijing University of Aeronautics and Astronautics, Beijing 100191, China;2. State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing 100191, China;3. Beijing Key Laboratory of Digital Media, Beihang University, Beijing 100191, China |
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| Abstract: | Detecting point targets in infrared images is a difficult task. Template matching is simple and easy to implement for completing this task. However, it has some shortcomings. We propose an improved template matching method for detecting targets. Different from the classic template matching, the projection coefficients obtained from principal component analysis are used as templates and the nonlinear correlation is proposed to measure the similarity, the matching degree. The correlation in original space can not capture the higher-order statistical property of images. So its detection performance is not satisfying. We introduce the nonlinear correlation, which computes the correlation coefficients in a higher-dimensional feature space or even in an infinite-dimensional feature space, to capture the higher-order statistics. The detection performance is improved greatly. Results of experiments show that the improved method is competent to detect infrared point targets. |
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