Research on Remote Sensing Image Classification Method Based on SVM & Clustering

被引：0
|
作者：
Ma, Yongli [1 ]
Yu, Gangyong [2 ]
Huang, Zhikai [1 ]
机构：
[1] Nanchang Inst Technol, Nanchang 330099, Jiangxi, Peoples R China
[2] Jiangxi Coll Foreign Studies, Nanchang 330099, Jiangxi, Peoples R China
来源：
2015 4TH INTERNATIONAL CONFERENCE ON ENERGY AND ENVIRONMENTAL PROTECTION (ICEEP 2015) | 2015年
关键词：
SVM; remote sensing image; training sample; cluster;
D O I：
暂无
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
Remote sensing image segmentation is important in the analysis of remote sensing images geomorphic features and spatial relationships. However, due to remote sensing image with complex data characteristics, the traditional methods used in remote sensing image segmentation cannot meet the requirements. This paper presents a method of remote sensing image segmentation method based on SVM. & cluster. Remote sensing image is processed mainly by way of human-computer interaction: training samples was selected and trained, then the support vector was obtained, and next each pixel of the image was classified. As for image possible spots/holes after classification, the method of clustering was adopted to remove. To verify the effectiveness of the algorithm, a map on Google Maps was selected, experiment results showed that this method is effective.
引用
收藏
页码：1983 / 1988
页数：6
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