%0 Journal Article
%A SHEN Sheng-yu
%A LIU Zhe
%A ZHANG Ping-cang
%A ZHANG Tong
%A WU Hua-yi
%A CHEN Xiao-ping
%T Extraction of High-resolution Remote-sensing Image Feature Based on MapReduce
%D 2014
%R 10.3969/j.issn.1001-5485.2014.02.019
%J Journal of Yangtze River Scientific Research Institute
%P 91-96
%V 31
%N 2
%X 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. 
%U http://ckyyb.crsri.cn/EN/10.3969/j.issn.1001-5485.2014.02.019