A New Method in Change Detection of Remote Sensing Image

被引:0
|
作者
Di Fengping [1 ]
Li Xiaowen [1 ]
Zhu Chongguang [2 ]
机构
[1] Beijing Normal Univ, Sch Geog, Beijing 100875, Peoples R China
[2] Chinese Acad Sci, Inst Remote Sensing Applicat, Beijing, Peoples R China
关键词
Change detection; SVM; Image analysis; COVER CHANGE DETECTION; MEAN SHIFT;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Change detection based on oriented-object employs objects to show real world. It can reflect visually change of real objects. Result of the method is easier to be understood and re-used. Meanwhile, applying support vector machine (SVM) to change detection can avoid requiring for samples distributing like traditional methods and the questions resulted from over learning like other machine learning methods. And the application can receive higher accuracy. So applying support vector machine along with oriented-object to change detection provides new idea for change detection. By proving, applying support vector machine and oriented-object to change detection supplies facility for result's re-use. And compared to result's readability and precision of other traditional methods, which of this method are higher
引用
收藏
页码:1308 / +
页数:3
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