首页 | 本学科首页   官方微博 | 高级检索  
     

基于MapReduce的高分辨率遥感影像特征提取方法
引用本文:沈盛彧,刘哲,张平仓,张彤,吴华意,陈小平.基于MapReduce的高分辨率遥感影像特征提取方法[J].长江科学院院报,2014,31(2):91-96.
作者姓名:沈盛彧  刘哲  张平仓  张彤  吴华意  陈小平
作者单位:(1.长江科学院 水土保持研究所,武汉 430010;2. 长江水利委员会 网络与信息中心,武汉 430010;3.武汉大学 测绘遥感信息工程国家重点实验室,武汉 430079)
基金项目:国家自然科学基金资助项目(41271400);国家973计划资助项目(2012CB719906);中央级公益性科研院所基本科研业务费(CKSF2012044TB,CKSF2012055TB)
摘    要: 遥感影像的数量和数据量正在呈几何级数增长,传统遥感影像处理方法已经无法应对这一海量问题。利用新兴的高性能计算集群的超强计算、存储及吞吐能力处理海量高分辨率遥感影像是一种新的思路。在基于云计算的高分辨率遥感影像处理的研究框架下,介绍一种MapReduce遥感影像特征提取方法,实现海量高分辨率遥感影像的海量底层视觉特征的提取。通过在16个节点的Hadoop集群上进行数据量扩展和处理能力扩展实验,证明了基于MapReduce的高分辨率遥感影像底层视觉特征的高效检测与描述方法的高效率及可扩展性。

关 键 词:云计算  高分辨率遥感影像  底层视觉特征  MapReduce

Extraction of High-resolution Remote-sensing Image Feature Based on MapReduce
SHEN Sheng-yu,LIU Zhe,ZHANG Ping-cang,ZHANG Tong,WU Hua-yi,CHEN Xiao-ping.Extraction of High-resolution Remote-sensing Image Feature Based on MapReduce[J].Journal of Yangtze River Scientific Research Institute,2014,31(2):91-96.
Authors:SHEN Sheng-yu  LIU Zhe  ZHANG Ping-cang  ZHANG Tong  WU Hua-yi  CHEN Xiao-ping
Affiliation:(1.Soil and Water Conservation Department, Yangtze River Scientific Research Institute,Wuhan 430010, China; 2. Network and Information Center, Changjiang Water Resources Commission,Wuhan 430010, China; 3. State Key Laboratory of Information Engineering in Surveying, Mapping,and Remote Sensing, Wuhan University, Wuhan 430079, China)
Abstract:Since the number and amount of remote sensing images is growing exponentially, traditional sensing image processing methods have been unable to deal with this massive growth. The supercomputing, massive storage and handling capacity of the high-performance computing cluster is a new solution to deal with the massive high-resolution remote sensing images. A method of extracting the basic visual features of high-resolution remote sensing images based on MapReduce is proposed. By experiments on the expansion of data amount and processing capacity on a 16-node Hadoop cluster, the MapReduce-based method is proved to be effective and scalable.
Keywords:cloud computing  high-resolution remote sensing image  basic visual features  MapReduce
本文献已被 CNKI 等数据库收录!
点击此处可从《长江科学院院报》浏览原始摘要信息
点击此处可从《长江科学院院报》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号