摘要
采用基于不同尺度下的面向特征基元的影像分析方法对高分辨率遥感影像进行基于MPI的处理,即在对常规的影像数据划分方法进行总结分析的基础上,提出了基于特定环境下的非均匀数据划分策略;在进行基于影像数据库的MPI并行处理时,提出了一种新的数据流分配方法。处理结果表明,这两种方法均能够在一定环境下取得比常规方法更高的效率。
This paper presents the method which improved the efficiency of information extraction based on feature unit of high-resolution remotely sensed image. To improve the precision of image processing, this paper applied image rough-classification based on large scale and precise-segmentation based on different scales. This paper used parallel computing method to improve the speed of image processing. For the data partition method of parallel computing of remotely sensed image, this paper summarized the general data partition methods and gave the general impelmentaiton method of data symmetrical partition method. After the characteristic analysis of the some special of remotely sensed image, this paper gave the mechanism of improving the efficiency of data partition and presented a new scale data asymmetric partition method, and gave the analysis and implementation of the new method. For the image parallel processing based on remotely sensed image database, this paper presented a new data distributing method. The analysis results show that the new methods can improve the efficiency of parallel computing for some special remotely sensed image in the special condition.
出处
《中国图象图形学报》
CSCD
北大核心
2007年第12期2132-2136,共5页
Journal of Image and Graphics
基金
国家自然科学基金项目(40601057)
中国科学院资源与环境信息系统国家重点实验室开放基金项目(A0615)
天津市科技发展计划重大项目(06YFGZGX17900)
关键词
MPI
并行计算
信息提取
尺度
数据划分
MPI, parallel computing, information extraction, scale, data partition
