• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>Image and signal processing for remote sensing XVII >Impact of informative band selection on target detection performance
【24h】

Impact of informative band selection on target detection performance

机译：信息带选择对目标检测性能的影响

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

In this paper, the effect of dimensionality reduction of hyperspectral data on 10 subpixel target detectors is investigated. The genetic algorithm (GA) and wavelet feature extraction methods are used for dimensionality reduction as they maintain physically meaningful bands and physical structure of the spectra, respectively. In the former case, the wrapper method is used to improve subpixel target detectors' results in terms of the area under the curve (AUC) of the receiver operating characteristic (ROC) curve. Meanwhile, in the latter case, the AUC is used as a criterion to choose the optimum level of wavelet decomposition. Experimental results obtained from a real-world hyperspectral data and a challenging synthetic dataset approved that band selection with the wrapper method is more efficient than using target detection methods without dimensionality reduction, especially in the presence of difficult targets at subpixel level.
机译：本文研究了高光谱数据降维对10个亚像素目标检测器的影响。遗传算法（GA）和小波特征提取方法分别用于降低维数，因为它们分别保持了物理上有意义的谱带和光谱的物理结构。在前一种情况下，使用包装方法来改善子像素目标检测器的接收器工作特性（ROC）曲线的曲线下面积（AUC）的结果。同时，在后一种情况下，AUC被用作选择小波分解最佳水平的准则。从现实世界的高光谱数据和具有挑战性的合成数据集获得的实验结果证明，使用包裹器方法进行波段选择比使用目标检测方法更有效，而无需降低维数，尤其是在子像素级存在困难目标的情况下。

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