计算机应用研究2017，Vol.34Issue(6)：1913-1916,1920,5.DOI:10.3969/j.issn.1001-3695.2017.06.072
基于联合协同表示与SVM决策融合的高光谱图像分类研究
Research of hyperspectral image classification based on joint collaborative representation and SVM models with decision fusion
李铁 1张新君2
作者信息
- 1. 辽宁工程技术大学电子与信息工程学院,辽宁葫芦岛125105
- 2. 大连理工大学计算机科学与技术学院,辽宁大连116024
- 折叠
摘要
Abstract
In view of the research of hyperspectral image (HSI) classification,this paper proposed a method based on the joint collaborative representation (JCR) and support vector machine(SVM) models with decision fusion.Firstly,it used a JCR model to decompose the samples and dictionaries into multi elements and carried out corresponding cooperative representation respectively,which adaptively learned residuals weights of multi elements and linear weighted.Second,it extracted the statistical features obtained from the gray level co-occurrence matrix to train a multiclass SVM classifier.Finally,it exploitd a multiplicative fusion rule to combine the JCR and SVM models.The experimental results on two standard data sets demonstrate that this method achieves better performance than other competing ones.关键词
协同表示/高光谱图像分类/决策融合/支持向量机Key words
collaborative representation (CR)/hyperspectral image (HSI) classification/decision fusion/support vector machine (SVM)分类
信息技术与安全科学引用本文复制引用
李铁,张新君..基于联合协同表示与SVM决策融合的高光谱图像分类研究[J].计算机应用研究,2017,34(6):1913-1916,1920,5.
