现代电子技术2016，Vol.39Issue(24)：14-17,21,5.DOI:10.16652/j.issn.1004-373x.2016.24.004
基于图像分割和LSSVM的高光谱图像分类
Hyperspectral image classification based on image segmentation and LSSVM
摘要
Abstract
A hyperspectral image classification method based on image segmentation and LSSVM is proposed,which com⁃bines spatial information to realize the hyperspectral imagery classification. Firstly hyperspectral image is segmented with mean⁃shift algorithm,and then dimension reduction of the data in each segmentation region is conducted and LSSVM classification of the data after dimension reduction is carried out. Finally the maximum voting method is used to fuse segmented map and obtain the final classification result. With the proposed method,the similarity matrices of segmented regions are derived and the new training sample set is trained to derive the low rank coefficient matrix,and the eigenvalue equation is built by means of similari⁃ty matrices and low rank coefficient matrix to solve the dimension reduction matrix,and then LSSVM is used to classify the data after dimension reduction. The exp⁃erimental results show that the hyperspectral image classification method based on image seg⁃mentation and LSSVM can effectively improve the classification accuracy of hyperspectral images.关键词
高光谱图像分类/图像分割/LSSVM/数据降维Key words
hyperspectral image classification/image segmentation/LSSVM/dimension reduction of data分类
信息技术与安全科学引用本文复制引用
楚恒,晁拴社..基于图像分割和LSSVM的高光谱图像分类[J].现代电子技术,2016,39(24):14-17,21,5.基金项目
重庆市博士后科研项目高分辨率遥感影像核方法分类在地理国情普查中的应用研究 （）
