|
The existing hyperspectral target recognition algorithms implemented on graphics processing units (GPU) have an outstanding performance in reducing the operation time. However, for push-broom hyperspectral imagery, real-time target search not only requires high computing performance for real-time response and rapid decisions but also requires synchronizing imaging, data transmission and target recognition. In terms of this problem, this paper proposes a new realtime target search method for push-broom hyperspectral imagery. This method takes the advantage of cross-execution and concurrent execution of compute unified device architecture (CUDA) streams in graphics processing units (GPU). The execution efficiency and process of this method are analyzed using GPU architecture by NVIDIA GeForce GTX745, which provides a reference for further application of real-time target search in the fields of civilian search and rescue, dangerous substances investigation and so on.
|
