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作者:

Pang, Qingyu (Pang, Qingyu.) | Yu, Jing (Yu, Jing.) | Sun, Weidong (Sun, Weidong.)

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摘要:

With the gradual maturation of imaging spectroscopy, the demand for quantitative analysis of hyperspectral images grows with each passing day. Spectral unmixing has been considered as an efficient way to extract detailed information about land covers. In this paper, by introducing the co-training concept into the spectral unmixing method based on wavelet weighted similarity (WWS-SU), a spectral unmixing method based on co-training (CT-SU) is proposed. Compared with the WWS-SU method on synthetic hyperspectral image, the CT-SU method shows not only more practical but also more accurate in result. © Springer International Publishing AG 2017.

关键词:

Computerized tomography Hyperspectral imaging Remote sensing Spectroscopy

作者机构:

  • [ 1 ] [Pang, Qingyu]State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Electronic Engineering, Tsinghua University, Beijing; 100084, China
  • [ 2 ] [Yu, Jing]College of Computer Science and Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 3 ] [Sun, Weidong]State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Electronic Engineering, Tsinghua University, Beijing; 100084, China

通讯作者信息:

  • [pang, qingyu]state key laboratory of intelligent technology and systems, tsinghua national laboratory for information science and technology, department of electronic engineering, tsinghua university, beijing; 100084, china

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来源 :

ISSN: 0302-9743

年份: 2017

卷: 10667 LNCS

页码: 570-579

语种: 英文

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