%0 Journal Article
%T Automated remote sensing image classification method based on Kmeans and SVM<br>基于Kmeans与SVM结合的遥感图像全自动分类方法*
%A JU Hong-yun
%A ZHANG Jun-ben
%A LI Chao-feng
%A WANG Zheng-you
%A <br>居红云
%A 张俊本
%A 李朝峰
%A 王正友
%J 计算机应用研究
%D 2007
%I 
%X The supervised learning algorithm was usually used for remote sensing image classification, but its training samples need to be chosen by manual, which was boring and sometimes even difficult. However, in unsupervised learning algorithm classification result was often not satisfactory. According to these limitations, an automated remote sensing image classification method of combining K-means algorithm with SVM. In new method, at first K-means algorithm was used to cluster original data points, and then according to the number and sparse degree of points in each class, some points as labeled samples were chosen to train SVM, at last SVM was utilized to reclassify original data points. Experimental results for Iris data and remote sensing data verify the validity of the proposed method.
%K Kmeans
%K SVM
%K remote sensing image classification<br>K-means
%K 支持向量机
%K 遥感图像分类
%K 结合
%K 遥感图像
%K 全自动
%K 分类方法
%K based
%K classification
%K method
%K remote
%K sensing
%K image
%K 有效性
%K 验证
%K 结果
%K 实验
%K 遥感数据
%K Iris
%K 重新分类
%K 分类器
%K 样本训练
%K 非监督学习算法
%K 程度
%K 样本数
%K 聚类算法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=C793235A4E87B8F684F5223B313F6CFC&yid=A732AF04DDA03BB3&vid=B91E8C6D6FE990DB&iid=708DD6B15D2464E8&sid=3C6F5C97A07587AE&eid=CA9ED1AB4D9E3E04&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=5