FAN Pengcheng, ZHANG Weiguo, LIU Wangang, ZHANG Wei, HUANG Weidong, LIU Guodong, XU Xiaofeng. Infrared weak small target detection algorithm based on embedded GPU[J]. Journal of Applied Optics, 2020, 41(5): 1089-1095. DOI: 10.5768/JAO202041.0506004
Citation: FAN Pengcheng, ZHANG Weiguo, LIU Wangang, ZHANG Wei, HUANG Weidong, LIU Guodong, XU Xiaofeng. Infrared weak small target detection algorithm based on embedded GPU[J]. Journal of Applied Optics, 2020, 41(5): 1089-1095. DOI: 10.5768/JAO202041.0506004

Infrared weak small target detection algorithm based on embedded GPU

  • The infrared weak small targets have few target pixels, low target contrast, high imaging frame rate, large amount of image data, and strong real-time detection. Aiming at the characteristic that the infrared weak small targets detection algorithm was suitable for the GPU parallel computing, the parallel optimization was implemented on the Jetson TX2 of the embedded GPU platform, and the optimized design was mainly reflected in the following three aspects: detection algorithm design, memory access, and debugging optimization. The experimental results show that for the infrared videos with a resolution of 640×480 pixels, the target detection algorithm after parallel optimization can complete the calculation in 10 ms, which meets the requirements of real-time processing.
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