Parallel algorithm based on improved SSDA in TEM
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摘要: 介绍了一种把图像匹配中的序贯相似性检测算法(SSDA,Sequential Similarity Detection Algorithm)应用到地形匹配中的方法,把地形匹配系统中的数字高程模型、高程数据和实时剖面数据分别视为SSDA算法中的搜索图、灰度值和模板,同时提出了动态门限序列和分组选取随机点的方法,最后将改进的SSDA算法进行并行化并用消息传递接口(MPI, Message Passing Interface)实现.实验结果表明,改进的SSDA算法能有效地提高地形匹配的速度和计算精度,而相应的并行程序也能取得较好的加速比,从而一定程度上解决了传统的地形匹配算法时间复杂度高、实时性差的问题.Abstract: 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.
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