Principal curvature for infrared small target detection |
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Institution: | 1. Department of Computer Science, The George Washington University, Washington DC, United States;2. Computer Networks and Security Laboratory (LARCES), State University of Ceará (UECE), Fortaleza, Ceará, Brazil;3. Faculty of Science, Engineering and Computing, Kingston University, United Kingdom |
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Abstract: | Small target detection in infrared image with complex background and low signal–noise ratio is an important and difficult task in the infrared target tracking system. In this paper, a principal curvature-based method is proposed. The principal curvatures of target pixels are negative and their absolute values are larger than that of background pixels and noise pixels in a Gaussian-blurred infrared image. The proposed filter takes a composite function of the curvatures for detection. An approximate model is also built for optimizing the parameters. Experimental results show that the proposed algorithm is effective and adaptable for infrared small target detection in complex background. Compared with several popular methods, the proposed algorithm demonstrates significant improvement on detection performance in terms of the parameters of signal clutter ratio gain, background suppression factor and ROC. |
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Keywords: | Infrared small target detection Hessian matrix Eigenvalue Principal curvature |
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