Hyperspectral matching method based on absorption features

SHI Junfeng; GUO Baofeng; SHEN Honghai; YANG Mingyu

doi:10.7510/jgjs.issn.1001-3806.2016.06.016

LASER TECHNOLOGY > 2016 > 40(6): 848-852. > DOI: 10.7510/jgjs.issn.1001-3806.2016.06.016

SHI Junfeng, GUO Baofeng, SHEN Honghai, YANG Mingyu. Hyperspectral matching method based on absorption features[J]. LASER TECHNOLOGY, 2016, 40(6): 848-852. DOI: 10.7510/jgjs.issn.1001-3806.2016.06.016

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Hyperspectral matching method based on absorption features

1.
School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China;
2.
Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China

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Received Date: October 28, 2015
Revised Date: December 15, 2015
Published Date: November 24, 2016

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Abstract

When adopting traditional hyperspectral ground objects identification method, the error of spectral matching became big because of the difference of absorption peak number. In order to solve the problem, an optional algorithm based on hyperspectral absorption peak characteristics was brought out, and then spectral matching according to the selected absorption was carried out. At beginning, the continuum removal in spectral curve and the extraction of spectral characteristic parameters matrix were made. And then the matching vertor of absorption peak was searched gradually according to the cosine distance-Euclidian distance of every vertor from the standard characteristic parameter matrix and the to-be-detected characteristic parameter matrix. After theoretical analysis and experimental verification of the selected absorption peak characteristic parameters matrix, the results show that this algorithm can get the best characteristic parameters vector, to realize the selection of absorption peak and make the hyperspectra matching with the selected absorption peak characteristic parameters matrix. The study is helpful for the decrease of the error of spectral matching.
- spectroscopy,
- spectral matching,
- absorption peak selection,
- vector distance

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