DMCA
Vertex component analysis: A fast algorithm to unmix hyperspectral data (2005)
| Venue: | IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING |
| Citations: | 191 - 16 self |
BibTeX
@ARTICLE{Nascimento05vertexcomponent,
author = {José M. P. Nascimento and José M. Bioucas Dias},
title = {Vertex component analysis: A fast algorithm to unmix hyperspectral data},
journal = {IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING},
year = {2005},
pages = {898--910}
}
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Abstract
Given a set of mixed spectral (multispectral or hyperspectral) vectors, linear spectral mixture analysis, or linear unmixing, aims at estimating the number of reference substances, also called endmembers, their spectral signatures, and their abundance fractions. This paper presents a new method for unsupervised endmember extraction from hyperspectral data, termed vertex component analysis (VCA). The algorithm exploits two facts: 1) the endmembers are the vertices of a simplex and 2) the affine transformation of a simplex is also a simplex. In a series of experiments using simulated and real data, the VCA algorithm competes with state-of-the-art methods, with a computational complexity between one and two orders of magnitude lower than the best available method.
Keyphrases
vertex component analysis hyperspectral data fast algorithm unsupervised endmember extraction algorithm exploit reference substance new method real data affine transformation spectral mixture model abundance fraction linear spectral mixture analysis index term component analysis vca algorithm competes abstract given state-of-the-art method spectral signature available method computational complexity unmixing hypespectral data linear unmixing
