%0 Journal Article
%T Study of Classification by Support Vector Machine on Synthetic Aperture Radar Image<br>基于SVM的SAR图像分类研究
%A TANG Jing-tian
%A HU Dan
%A GONG Zhi-min
%A <br>汤井田
%A 胡丹
%A 龚智敏
%J 遥感技术与应用
%D 2008
%I 
%X Support Vector Machine (SVM) has excellent performance in classification.The Gray Level Co-occurrence Matrix (GLCM) is a promising method for texture analysis.Texture is an important feature in Synthetic Aperture Radar (SAR) image.So the arithmetic of texture classification by SVM was investigated, using GLCM to extract features.Compared to the method using image's gray information directly for SVM classifying, the experimental results show the feasibility and effectiveness of the new method.
%K nullzz<br>支持向量机
%K 灰度共生矩阵
%K 特征提取
%K 纹理分类
%K SAR图像
%K 图像分类
%K 分类研究
%K Radar
%K Image
%K Synthetic
%K Aperture
%K Support
%K Vector
%K Machine
%K Classification
%K 有效性
%K 支持向量机算法
%K 结果
%K 实验
%K 分类法
%K 应用
%K 特征提取
%K 使用
%K 合成孔径雷达
%K 纹理分析方法
%K 灰度共生矩阵
%K 分类方法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=6F56B81324C1B239DA82AE08A4344F0C&aid=80B86F842A5A79AD52B60AB53AE37C73&yid=67289AFF6305E306&vid=EA389574707BDED3&iid=38B194292C032A66&sid=4B168891B5E5FB30&eid=3622B70F9C54A9CC&journal_id=1004-0323&journal_name=遥感技术与应用&referenced_num=3&reference_num=1