Parallel algorithm based on improved SSDA in TEM

A new terrain elevation matching (TEM) method using sequential similarity detection algorithm (SSDA), which is an image matching algorithm was presented, while regarding the digital elevation model, height value and real-time profile data in TEM as searching image, hue value and template in SSDA respectively. The dynamic threshold sequence and the method of selecting random points in groups were described. A parallelism algorithm based on improved SSDA was designed and implemented with message passing interface(MPI). The experiment results show that the improved SSDA algorithm can effectively increase the matching speed and the precision, and the corresponding parallel program can also get good speed-up ratio. Therefore the problem of high time complexity and lack of real time feature in traditional TEM was solved to some extent.