Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (34): 7-9.DOI: 10.3778/j.issn.1002-8331.2009.34.003

• 博士论坛 • Previous Articles     Next Articles

Implementation of multi-scales segmentation for high resolution RS images based on cluster

WU Wei1,2,SHEN Zhan-feng1,LUO Jian-cheng1,CHEN Qiu-xiao3,HU Xiao-dong1,2   

  1. 1.Institute of Remote Sensing Application,Chinese Academy of Sciences,Beijing 100101,China
    2.Graduate University of Chinese Academy of Sciences,Beijing 100049,China
    3.Department of City Planning,Zhejiang University,Hangzhou 310058,China
  • Received:2009-09-03 Revised:2009-10-12 Online:2009-12-01 Published:2009-12-01
  • Contact: WU Wei

均值漂移高分辨率遥感影像多尺度分割的集群实现

吴 炜1,2,沈占锋1,骆剑承1,陈秋晓3,胡晓东1,2   

  1. 1.中国科学院 遥感应用研究所,北京 100101
    2.中国科学院 研究生院,北京 100049
    3.浙江大学 城市规划系,杭州 310058
  • 通讯作者: 吴 炜

Abstract: Multi_scales segmentation is important basis for high resolution RS information computation and key technologies for graphics information extraction.The existed multi_scales segmentation algorithms are usually memory cost,computation-intensive.What’s more,these problems will become serious as the data accumulating and algorithms improving.To solve these problems,a parallel algorithm for mean shift multi_scales segmentation based on cluster is proposed and implemented,statistics the processing time,then analyzes and proves the effectiveness of the algorithm.

Key words: multi_scales segmentation, high resolution RS image, efficiency analysis, mean shift, cluster

摘要: 多尺度分割是高分辨率遥感信息计算的重要基础,是高分辨率遥感影像图谱认知中“图”提取的关键技术。当前提出的多尺度分割方法普遍存在着占用内存大,耗费计算资源、计算时间长的缺点,并且这些问题随着遥感数据量的增大、算法的改进等进一步加剧。针对这种情况,根据当前集群计算技术的发展,以均值漂移的多尺度分割方法为例,实现了一种基于集群计算环境的多尺度分割算法,集中解决任务分配和结果回收以及数据并行的方式,统计了算法所消耗的时间,对其的效率进行了分析,通过实验说明了集群化对提高多尺度分割效率的有效性。

关键词: 多尺度分割, 高分辨率影像, 效率分析, 均值漂移, 集群

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