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Vol. 159, Issue 11, November 2013, pp. 46-53




The Study of Remote Sensing Image Classification Based on Support Vector Machine
1, 2 ZHANG Jian-Hua

1 Key Research Institute of Yellow River Civilization and Sustainable Development & College of Environment and Planning, Henan University, Kaifeng 475001, China

2 College of Economy and Trade, Henan Institute of Engineering, Zhengzhou 451191, China


Received: 1 September 2013   /Accepted: 25 October 2013   /Published: 30 November 2013

Digital Sensors and Sensor Sysstems


Abstract: This paper proposed a remote sensing image classification method based on Support Vector Machine (SVM). Because it is a convex optimization problem, according to the properties of convex optimization we can know that the values of local optimal solution must be the global optimal solution, which is the other classification methods don't have. In the autonomous learning classification and automatic processing aspects the Support Vector Machine (SVM) shows its effectiveness. In this paper it used the IKNOS remote sensing image and selected crops, residents, water, grass, land transportation and so on five big classes for training. The training results show that Support Vector Machine (SVM) has higher recognition rate in classifying the remote sensing image.


Keywords: Support Vector Machine (SVM), Remote sensing image, Classification.


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