摘要
遥感影像的快速匹配是3维信息实时获取的关键,而采用并行处理技术能够有效地解决匹配的速度问题。在对基于概率松弛的匹配算法进行分析的基础上,结合集群并行计算平台的特点,从负载平衡和数据通信两个方面出发,对并行匹配算法中的数据划分关键问题进行了深入讨论,提出一种负载平衡的并行匹配算法。实验结果证明,该算法能够达到计算节点的负载平衡,通信开销更小,适合在集群计算平台进行高性能影像匹配处理。
Rapid image matching is the key to real-time 3D information acquisition,and parallel processing technology is an important way for solving the problem of computing speed.Image matching algorithm based on probability relaxation was firstly analyzed.Then,combined with the characteristics of cluster computer and considering the load balancing and data communication,the key technology of parallel matching-data partitioning was discussed and a load balancing parallel image matching algorithm was put forward.It is proved by experiments that,by using the load balancing algorithm,it is more likely to achieve load balance and the cost of data communication is smaller.
出处
《测绘科学技术学报》
北大核心
2010年第3期205-208,共4页
Journal of Geomatics Science and Technology
基金
江西省数字国土重点实验室开放基金资助项目(DLLG201001)
矿山空间信息技术国家测绘局重点实验室开放基金资助项目(KLM200904)
关键词
集群并行计算
概率松弛法
负载平衡
影像匹配
数据划分
cluster computing
probabilistic relaxation
load balancing
image matching
data partitioning
