Method of Remote Sensing Image Fine Classification Based on Geometric Features and SVM

被引:2
作者
Zhou Xiao-Dong [1 ]
Yang Chun-Cheng [1 ]
Meng Ni-Na [2 ]
机构
[1] Xian Inst Surveying & Mapping, Cartog & GIS Lab, Xian, Peoples R China
[2] Changan Univ, Coll Geol Engn & Geomat, Xian, Peoples R China
来源
ADVANCED MATERIALS IN MICROWAVES AND OPTICS | 2012年 / 500卷
关键词
Image classification; SVM; geometric features; fine classification; classification rules;
D O I
10.4028/www.scientific.net/KEM.500.562
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In order to overcome the phenomenon of foreign bodies in the same spectrum in remote sensing images, as needs of land-use surveys, traditional methods often can't get good results. In this paper, an efficient method for dividing the classifying results of traditional methods into further items is proposed and studied. Our approach to remote sensing image fine classification is based on both geometric features and SVM. By making full use of geometric features in the structure of property characteristics, we produce rules of the morphological characteristics and distribution. With deductive reasoning, we further classify the classifying results of SVM classifier. Tests showed that the method can be better broken down into the waters of rivers, lakes, reservoirs and ponds.
引用
收藏
页码:562 / +
页数:2
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