Reserch on parallel computing of infrared small target detection

Moving infrared small target detection is widely used in areas such as target surveillance, precise guidance, etc. It has a high demand for the real-time and the probability of detection. Multiband simultaneous detection can get a high detection probability, but it leads to substantial growth in computing time, which cannot meet the real-time requirement in practical applications. To solve this problem, this paper presents a parallel hierarchical approach based on MPI(Message Passing Interface) and OpenMP, which makes full use of the advantages of both message-passing model and shared storage model. It is based on the cluster system of multiprocessor nodes for testing. Experimental results show that, this parallel method can achieve a speedup of 7.8 compared with the serial method in the condition of the same detection probability. And its computational performance is also superior to the methods of pure OpenMP parallel and pure MPI parallel. This method has strong scalability.