Application Research of Support Vector Machine in Multi-Spectra Remote Sensing Image Classification

Yujian Wang, Jiazheng Yuan, Lili Fan, Zhiguo Liu
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引用次数: 1

Abstract

In order to improve the accuracy of multi-spectra remote sensing image classification, a terrain classification method based on support vector machine is proposed. A remote sensing image classification method based on SVM algorithm of C-SVC type is introduced and emphasis is put on the study of the improved SMO algorithm. In order to improve efficiency of classification, multiple-spectra remote sensing image classification of terrain is classified using fuzzy clustering based on fuzzy c-means algorithm which adopt semi-supervised improved algorithm. The experimental results show that the approach has an advantage over traditional classification methods.
支持向量机在多光谱遥感图像分类中的应用研究
为了提高多光谱遥感影像分类的精度,提出了一种基于支持向量机的地形分类方法。介绍了一种基于C-SVC型SVM算法的遥感图像分类方法,重点研究了改进的SMO算法。为了提高分类效率,采用基于半监督改进算法的模糊c均值算法对地形多光谱遥感影像进行模糊聚类分类。实验结果表明,该方法优于传统的分类方法。
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