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基于遥感影像的军事阵地动态监测技术研究
引用本文:许夙晖,慕晓冬,柯冰,王晓日.基于遥感影像的军事阵地动态监测技术研究[J].遥感技术与应用,2014,29(3):511-516.
作者姓名:许夙晖  慕晓冬  柯冰  王晓日
作者单位:(第二炮兵工程大学信息工程系,陕西 西安710025)
基金项目:许夙晖(1989-),女,河南焦作人,博士研究生,主要从事军事阵地遥感图像的研究。Email:xu_suhui@163.com
摘    要:针对部队快速机动作战的军事要求,提出基于高分辨率遥感影像的军用阵地动态监测方法。借助面向对象的多尺度分割技术将阵地影像分割为同质对象,以提取各个对象的特征;针对监督分类和非监督分类的弊端,提出通过一定的先验知识制定分类规则的方法对遥感影像进行地物识别,在此基础上定性和定量地输出变化检测结果。实验结果表明:利用基于对象影像分析方法具有较高的识别精度,能够有效监测军事阵地变化。

关 键 词:军事阵地  面向对象  多尺度  变化检测  
收稿时间:2013-05-02

Dynamic Monitoring of Military Position based on Remote Sensing Image
Xu Suhui,Mu Xiaodong,Ke Bing,Wang Xiaori.Dynamic Monitoring of Military Position based on Remote Sensing Image[J].Remote Sensing Technology and Application,2014,29(3):511-516.
Authors:Xu Suhui  Mu Xiaodong  Ke Bing  Wang Xiaori
Affiliation:(The Department of Information Engineering,The Second Artillery Engineering University,Xi’an 710025,China)
Abstract:According to the demands of rapid maneuvering of military forces,the method of dynamic monitoring of military position based on remote sensing image is proposed.With the help of object\|oriented multi\|scale segmentation,the image of position is segmented into homogeneous objects for extracting their features,which avoids the phenomenon of “the different bodies with the same spectrum” and “content with the different spectrums”.For the trivialness of supervised classification and the blindness of unsupervised classification,through the apriori knowledge the method on making rules for the classification is proposed to identify the objects of the remote sensing images,and on this basis the results of change detection are output qualitatively and quantitatively.The experiments results show that the objected\|oriented method has high identification precision and can effectively monitor the military position.
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Keywords:Military position  Object-oriented  Multi-scale  Change detection
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