A Novel Spatial Analysis Method for Remote Sensing Image Classification

被引:16
|
作者
Gao, Jianqiang [1 ]
Xu, Lizhong [1 ]
机构
[1] Hohai Univ, Coll Comp & Informat Engn, Nanjing 210098, Jiangsu, Peoples R China
关键词
Remote sensing image; Projection matrix; Support vector machine; Image classification; Kernel method; KERNEL SPARSE REPRESENTATION; CONTEXTUAL INFORMATION; GIS DATA; SYSTEM; REDUCTION;
D O I
10.1007/s11063-015-9447-0
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A new and efficient classification model is introduced in this paper. The proposed model enjoys the information of null space of within-class and range space of within-class. And the proposed model aims at defining a reliable spatial analysis criterion for the remote sensing image, taking advantage of the differences in different areas. Finally, by incorporating fisher linear discriminant analysis and support vector machine (or K-nearest neighbor) classifier among image pixels, the model obtained more accurate classification results.
引用
收藏
页码:805 / 821
页数:17
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