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| 高光谱影像的改进K-均值监督式聚类分析方法 | |
| 引用本文： | 苏红军,盛业华,DU Qian,YANG He.高光谱影像的改进K-均值监督式聚类分析方法[J].武汉大学学报(信息科学版),2012,37(6):640-643,687. |
| 作者姓名： | 苏红军 盛业华 DU Qian YANG He |
| 作者单位： | 1. 河海大学地球科学与工程学院,南京市西康路1号210098／南京师范大学虚拟地理环境教育部重点实验室,南京市文苑路1号210046 2. 南京师范大学虚拟地理环境教育部重点实验室,南京市文苑路1号,210046 3. 美国密西西比州立大学电子与计算机工程系,美国密西西比斯塔克维尔市39762 |
| 基金项目： | 国家自然科学基金资助项目，河海大学中央高校基本科研业务费专项资金资助项目 |
| 摘 要： | 针对K-均值聚类存在的初始聚类中心不稳定、聚类数目难以确定的问题,提出利用正交投影散度(OPD)优化K-均值算法的初始聚类中心,设计了RD指标函数用于估计聚类数目k。将所提出的算法应用于高光谱影像特征提取与端元提取分析,实验结果表明,所提出算法的性能高于已有的类似算法。 |
| 关 键 词： | 高光谱影像 监督K-均值 端元提取 |
Supervised K-means Clustering Analysis for Hyperspectral Imagery |
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| SU Hongjun,SHENG Yehua.Supervised K-means Clustering Analysis for Hyperspectral Imagery[J].Geomatics and Information Science of Wuhan University,2012,37(6):640-643,687. | |
| Authors: | SU Hongjun SHENG Yehua |
| Institution: | 2 DU Qian3 YANG He3(1 School of Earth Sciences and Engineering,Hohai University,1 Xikang Road,Nanjing 210098,China)(2 Key Laboratory of Virtual Geographic Environment,Ministry of Education,Nanjing Normal University, 1 Wenyuan Road,Nanjing 210046,China)(3 Department of Electrical and Computer Engineering,Mississippi State University,Starkville,MS 39762,USA) |
| Abstract: | We explore widely used K-means algorithm and propose two methods to improve its performance for hyperspectral clustering and analysis.A novel initialization method based on orthogonal subspace projection(OSP) is presented,which can get the suitable initial seeds for K-means clustering.In addition,we address a new cardinality estimation index which maximizes the distance ratio between intra-cluster distance and inter-cluster distance.It is used as a tool to estimate the numbers of clusters in K-means for hyperspectral data.The experimental results show that the proposed method can performs better than other traditional methods. |
| Keywords: | hyperspectral imagery supervised K-means endmember extraction |
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