• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XII pt.1 >Change Detection in Hyperspectral Imagery using Temporal Principal Components
【24h】

Change Detection in Hyperspectral Imagery using Temporal Principal Components

机译：使用时间主成分的高光谱图像中的变化检测

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

Change detection is the process of automatically identifying and analyzing regions that have undergone spatial or spectral changes from multi temporal images. Detecting and representing change provides valuable information of the possible transformations a given scene has suffered over time. Change detection in sequences of hyperspectral images is complicated by the fact that change can occur in the temporal and/or spectral domains. This work studies the use of Temporal Principal Component Analysis (TPCA) for change detection in multi/hyperspectral images. Two additional methods were implemented in order to compare its results with TPCA. These were: Image Differencing and Conventional Principal Component Analysis. Experimental results using phantom hyperspectral imagery taken with Surface Optics SOC-700 hyperspectral camera are presented. The algorithms were implemented using Matlab, and their performance is compared in terms of false alarms, missed changes and overall error. Results show that the performance of TPCA was the best, obtaining the smallest percentages of error, missed changes, and false alarms using global or local threshold. TPCA with local threshold gave the best performance.
机译：变化检测是从多个时间图像自动识别和分析经历了空间或光谱变化的区域的过程。检测和表示变化可提供给定场景随时间推移可能发生的转换的有价值的信息。高光谱图像序列中的变化检测由于时间和/或光谱域中可能发生变化这一事实而变得复杂。这项工作研究了时间主成分分析（TPCA）在多/高光谱图像中检测变化的用途。为了将其结果与TPCA进行比较，还采用了两种其他方法。它们是：图像差异和常规主成分分析。提出了使用Surface Optics SOC-700高光谱相机拍摄的幻像高光谱图像进行实验的结果。这些算法是使用Matlab实施的，并根据错误警报，更改遗漏和整体错误对它们的性能进行了比较。结果表明，TPCA的性能最佳，使用全局或局部阈值可获得的错误，遗漏更改和错误警报的百分比最小。具有本地阈值的TPCA提供了最佳性能。

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