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Vertex Component Analysis: A fast algorithm to extract endmembers spectra from Hyperspectral data

Nascimento, J. ; Bioucas-Dias, J.

Vertex Component Analysis: A fast algorithm to extract endmembers spectra from Hyperspectral data, Proc Iberian Conf. on Pattern Recognition and Image Analysis, Puerto de Andratx, Spain, Vol. LNCS - 2652, pp. 626 - 635, June, 2003.

Digital Object Identifier: 10.1007/978-3-540-44871-6_73

Abstract
Linear spectral mixture analysis, or linear unmixing, has
proven to be a useful tool in hyperspectral remote sensing applications. It aims at estimating the number of reference substances, also called endmembers,
their spectral signature and abundance fractions, using only the observed data (mixed pixels).
This paper presents new method that performs unsupervised endmember extraction from hyperspectral data. The algorithm exploits a simple geometric fact: endmembers are vertices of a simplex. The algorithm
complexity, measured in floating points operations, is O(n), where n is the sample size. The e ectiveness of the proposed scheme is illustrated using simulated data.