Separable convolution template (SCT) background prediction accelerated by CUDA for infrared small target detection |
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| Institution: | 1. Food Technology Department, Research Institute of Meat and Meat Product (IproCar), University of Extremadura, Av/Universidad S/N, ES-10003 Cáceres, Spain;2. Computer Science Department, Research Institute of Meat and Meat Product (IproCar), University of Extremadura, Av/Universidad S/N, ES-10003 Cáceres, Spain;3. Department of Food Science, Quality and Technology, Faculty of Life Science, University of Copenhagen, Rolighedsvej 30, DK-1958 Frediksberg C, Denmark.;4. Department of Applied Mathematics and Computer Science, Technical University of Denmark, Richard Petersen Plads, Building 324, DK-2800 Kongens Lyngby, Denmark;5. Department of Informatics and Mathematical Modeling, Technical University of Denmark, Richard Petersen Plads, Building 324, DK-2800 Kongens Lyngby, Denmark |
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| Abstract: | This paper presents a novel background prediction method for infrared small target detection (ISTD). Using a separable convolution template (SCT) to accelerate the traditional background prediction by graphic processing unit (GPU), the new method provides a significant improvement in the prediction speed, which enables the prediction process in real time. And experimental results show its high efficiency and practical application over previous work. The mathematical approach proposed here could be extended to accelerate the applications referred to image convolutions not only to the infrared field. |
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| Keywords: | Infrared images Separate template CUDA Background prediction |
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