A new kernel method for hyperspectral image feature extraction-Reference-Cited by-同舟云学术

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A new kernel method for hyperspectral image feature extraction

Published:2017-10-02 Issue:4 Volume:20 Page:309-318
ISSN:1009-5020
Container-title:Geo-spatial Information Science
language:en
Short-container-title:Geo-spatial Information Science

Author:

Zhao Bin¹²,Gao Lianru¹,Liao Wenzhi³,Zhang Bing¹²

Affiliation:

1. Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China

2. University of Chinese Academy of Sciences, Ringgold Standard Institution, Beijing, China

3. Department of Telecommunications and Information Processing, Ghent University, Ghent, Belgium

Funder

Fonds Wetenschappelijk Onderzoek

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

Computers in Earth Sciences,Geography, Planning and Development

Link

https://tandfonline.com/doi/pdf/10.1080/10095020.2017.1403088

Reference24 articles.

1. Methodology for Hyperspectral Band Selection

2. Ball, J. E., L. M. Bruce, T. West, and S. Prasad. 2007. “Level Set Hyperspectral Image Segmentation Using Spectral Information Divergence-based Best Band Selection.” IEEE International Conference: the Geoscience & Remote Sensing Symposium, Barcelona, Spain, July 23−28. doi: 10.1109/igarss.2007.4423739.

3. Classification of hyperspectral data from urban areas based on extended morphological profiles

4. Study on the issue of noise estimation in dimension reduction of hyperspectral images

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