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A PROSAIL-based spectral unmixing algorithm for solving vegetation spectral variability problem
Author(s): Qianqian Li; Wenfei Luo; Fangfang Wang
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Paper Abstract

The spectral signature of vegetation in the image is easily affected by background soil reflectance and spectral variability of vegetation reflectance, spectral variability is one of the major error sources of unmixing. The traditional algorithms do not solve spectral variability problem from the mechanism. In this paper, we take advantage of radiative transfer model, in order to describe the spectral variability of endmember. As a result, the spectral variability can be quantitatively described. The experimental results show that the PROSAIL Model Spectral Unmixing (PMSU) algorithm has higher unmixing precision than the other algorithms.

Paper Details

Date Published: 19 February 2018
PDF: 6 pages
Proc. SPIE 10607, MIPPR 2017: Multispectral Image Acquisition, Processing, and Analysis, 106070L (19 February 2018); doi: 10.1117/12.2283462
Show Author Affiliations
Qianqian Li, South China Normal Univ. (China)
Wenfei Luo, South China Normal Univ. (China)
Fangfang Wang, South China Normal Univ. (China)


Published in SPIE Proceedings Vol. 10607:
MIPPR 2017: Multispectral Image Acquisition, Processing, and Analysis
Xinyu Zhang; Jun Zhang; Hongshi Sang, Editor(s)

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