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A band selection approach for small target detection based on CEM

机译:基于CEM的小目标检测波段选择方法

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摘要

Constrained energy minimization (CEM) is one of the most widely used target detection methods due to its simplicity and effectiveness. From a mathematical perspective, the detection result can be regarded as the summation of bands weighted by the corresponding components of the CEM operator. Based on this point of view, we propose a supervised band selection idea for CEM target detection. Three different band selection methods for CEM (namely, BSC1, BSC2 and BSC3) are presented and compared. Some comparative experiments based on real hyperspectral data are conducted to evaluate the performance of these methods (the presented and other two methods). The results show that BSC3 is the most effective band selection method. The CEM detection result is quite acceptable using only a few of the bands selected by BSC3. BSC1 and BSC2 are also more accurate than other compared band selection methods when the number of selected bands is relatively large (>18 in our experiments).
机译:约束能量最小化(CEM)由于其简单性和有效性而成为最广泛使用的目标检测方法之一。从数学角度来看,检测结果可以看作是由CEM运算符的相应分量加权的频带之和。基于此观点,我们提出了一种用于CEM目标检测的监督波段选择思路。提出并比较了三种用于CEM的频带选择方法(即BSC1,BSC2和BSC3)。进行了一些基于实际高光谱数据的比较实验,以评估这些方法(本文介绍的方法和其他两种方法)的性能。结果表明,BSC3是最有效的频带选择方法。仅使用BSC3选择的几个频带,CEM检测结果就可以接受。当所选频段的数量相对较大时(在我们的实验中> 18),BSC1和BSC2也比其他比较的频段选择方法更准确。

著录项

  • 来源
    《International journal of remote sensing》 |2014年第13期|4589-4600|共12页
  • 作者

    Kang Sun; Xiurui Geng; Luyan Ji;

  • 作者单位

    Key Laboratory of Technology in Geospatial Information Processing and Application System, Institute of Electronics, Chinese Academy of Sciences, Beijing, China;

    Key Laboratory of Technology in Geospatial Information Processing and Application System, Institute of Electronics, Chinese Academy of Sciences, Beijing, China;

    Ministry of Education Key Laboratory for Earth System Modelling, Centre for Earth System Science, Tsinghua University, Beijing, China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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