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Proceedings Paper

Spectral reflectance measurement and the principal component analysis and correlation analysis of trees in visible and near infrared
Author(s): Zhenhua Du; Junsheng Shi; Feiyan Cheng; Xiaoqiao Huang; Lin Xu
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Paper Abstract

Visible and near-infrared spectral reflectances of surface vegetation are basic data for applications in remote sensing classification, multispectral imaging and color reproduction. Leaves are the objects of this study. Firstly, The 400-700 nm visible light spectral reflectance and 700−1000 nm near infrared spectral reflectance data of 12 kinds of trees such as camphor tree, ginkgo tree and peach tree (etc.) are measured by visible and near-infrared portable hyperspectral cameras. The spectral reflectance data is obtained by denoising the using the Minimum Noise Fraction (MNF). Secondly, the Principal Component Analysis (PCA) is used as a method of processing spectral reflectance in the visible and near infrared bands. At last, the correlation analysis is used for spectral reflectance in the visible and near-infrared bands. The obtained data and results provide a theoretical basis for the subsequent establishment of a spectral reflectance data base of surface vegetation spectroscopy and multispectral imaging.

Paper Details

Date Published: 9 November 2018
PDF: 6 pages
Proc. SPIE 10826, Infrared, Millimeter-Wave, and Terahertz Technologies V, 1082617 (9 November 2018); doi: 10.1117/12.2501165
Show Author Affiliations
Zhenhua Du, Yunnan Normal Univ. (China)
Yunnan Key Lab. of Opto-electronic Information Technology (China)
Junsheng Shi, Yunnan Normal Univ. (China)
Yunnan Key Lab. of Opto-electronic Information Technology (China)
Feiyan Cheng, Yunnan Key Lab. of Opto-electronic Information Technology (China)
Xiaoqiao Huang, Yunnan Normal Univ. (China)
Yunnan Key Lab. of Opto-electronic Information Technology (China)
Lin Xu, Yunnan Normal Univ. (China)
Yunnan Key Lab. of Opto-electronic Information Technology (China)


Published in SPIE Proceedings Vol. 10826:
Infrared, Millimeter-Wave, and Terahertz Technologies V
Cunlin Zhang; Xi-Cheng Zhang; Masahiko Tani, Editor(s)

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