• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>IEEE Transactions on Geoscience and Remote Sensing >Dual-Clustering-Based Hyperspectral Band Selection by Contextual Analysis
【24h】

Dual-Clustering-Based Hyperspectral Band Selection by Contextual Analysis

机译：基于上下文分析的基于双聚类的高光谱波段选择

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Hyperspectral image (HSI) involves vast quantities of information that can help with the image analysis. However, this information has sometimes been proved to be redundant, considering specific applications such as HSI classification and anomaly detection. To address this problem, hyperspectral band selection is viewed as an effective dimensionality reduction method that can remove the redundant components of HSI. Various HSI band selection methods have been proposed recently, and the clustering-based method is a traditional one. This agglomerative method has been considered simple and straightforward, while the performance is generally inferior to the state of the art. To tackle the inherent drawbacks of the clustering-based band selection method, a new framework concerning on dual clustering is proposed in this paper. The main contribution can be concluded as follows: 1) a novel descriptor that reveals the context of HSI efficiently; 2) a dual clustering method that includes the contextual information in the clustering process; 3) a new strategy that selects the cluster representatives jointly considering the mutual effects of each cluster. Experimental results on three real-world HSIs verify the noticeable accuracy of the proposed method, with regard to the HSI classification application. The main comparison has been conducted among several recent clustering-based band selection methods and constraint-based band selection methods, demonstrating the superiority of the technique that we present.
机译：高光谱图像（HSI）涉及大量信息，可帮助进行图像分析。但是，考虑到诸如HSI分类和异常检测之类的特定应用，有时已证明此信息是多余的。为了解决这个问题，高光谱波段的选择被认为是一种有效的降维方法，可以消除HSI的冗余成分。最近已经提出了各种HSI频带选择方法，并且基于聚类的方法是传统的方法。这种聚集方法被认为是简单明了的，而性能通常不如现有技术水平。为了解决基于聚类的频带选择方法的固有弊端，提出了一种关于双聚类的新框架。主要的贡献可以归纳如下：1）一种新颖的描述符，可以有效地揭示HSI的背景； 2）在聚类过程中包括上下文信息的双重聚类方法； 3）一种新策略，该策略共同考虑每个集群的相互影响来选择集群代表。关于HSI分类应用，在三个真实世界的HSI上的实验结果证明了该方法的显着准确性。主要的比较是在最近几种基于聚类的频带选择方法和基于约束的频带选择方法之间进行的，证明了我们提出的技术的优越性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号