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Proceedings Paper

Endmember extraction using the physics-based multi-mixture pixel model
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Paper Abstract

A method of incorporating the multi-mixture pixel model into hyperspectral endmember extraction is presented and discussed. A vast majority of hyperspectral endmember extraction methods rely on the linear mixture model to describe pixel spectra resulting from mixtures of endmembers. Methods exist to unmix hyperspectral pixels using nonlinear models, but rely on severely limiting assumptions or estimations of the nonlinearity. This paper will present a hyperspectral pixel endmember extraction method that utilizes the bidirectional reflectance distribution function to model microscopic mixtures. Using this model, along with the linear mixture model to incorporate macroscopic mixtures, this method is able to accurately unmix hyperspectral images composed of both macroscopic and microscopic mixtures. The mixtures are estimated directly from the hyperspectral data without the need for a priori knowledge of the mixture types. Results are presented using synthetic datasets, of multi-mixture pixels, to demonstrate the increased accuracy in unmixing using this new physics-based method over linear methods. In addition, results are presented using a well-known laboratory dataset.

Paper Details

Date Published: 15 October 2012
PDF: 14 pages
Proc. SPIE 8515, Imaging Spectrometry XVII, 85150L (15 October 2012); doi: 10.1117/12.930288
Show Author Affiliations
Ryan Close, U.S. Army RDECOM CERDEC NVESD (United States)
Paul Gader, Univ. of Florida (United States)
Alina Zare, Univ. of Missouri (United States)
Joseph Wilson, Univ. of Florida (United States)
Dmitri Dranishnikov, Univ. of Florida (United States)

Published in SPIE Proceedings Vol. 8515:
Imaging Spectrometry XVII
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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