![]() Īlthough the existing hyperspectral target recognition algorithms implemented on GPU have a good performance in reducing the operation time, there are few methods to consider synchronizing imaging, data transmission and target recognition for real-time push-broom hyperspectral imagery target search (RT-PBHSI-TS). Benefits from GPU’s ability to support Device Overlap, in this paper, we propose a new RT-PBHSI-TS method, which is implemented on GPU utilizing CUDA streams. The proposed method involves two main phases: (1) real-time hyperspectral target recognition (2) synchronizing imaging, data transmission and target recognition. ![]() Spectral angle mapping (SAM) and Euclidean distance (ED) are used for spectral matching implemented on GPU to realize real-time target recognition, and then, Device Overlap utilizing CUDA streams is applied to synchronize imaging, data transmission and target recognition. the experimental results show that the real-time target recognition algorithm speedups over 20x using GPU architecture by NVIDIA GeForce GTX745 compared to CPU implementation at same recognition accuracy that when the false alarm rate is 10-4, the recognition accuracy can reach 93.46%. Finally, the execution efficiency of the real-time target recognition algorithm is analyzed, and the process of RT-PBHSI-TS method is introduced in detail, which provides a reference for further application of target search in the fields of civilian search and rescue, dangerous substances investigation and so on. ![]() In Section 2, the real-time hyperspectral target recognition algorithm is introduced in detail.
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