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Orientador(es)
Resumo(s)
Linear unmixing decomposes an hyperspectral image into a collection of re
ectance spectra, called endmember
signatures, and a set corresponding abundance fractions from the respective spatial coverage. This paper introduces
vertex component analysis, an unsupervised algorithm to unmix linear mixtures of hyperpsectral data.
VCA exploits the fact that endmembers occupy vertices of a simplex, and assumes the presence of pure pixels
in data. VCA performance is illustrated using simulated and real data. VCA competes with state-of-the-art
methods with much lower computational complexity.
Descrição
Palavras-chave
Hyperspectral imagery Unsupervised endmember extraction Vertex component analysis Spectral mixture model Linear unmixing
Contexto Educativo
Citação
NASCIMENTO, José M. P.; BIOUCAS-DIAS, José M. - Fast unsupervised extraction of endmembers spectra from hyperspectral data. Proceedings of SPIE - Remote Sensing for Environmental Monitoring, GIS Applications, and Geology III. ISSN 0277-786X. Vol. 5239. 314-321, 2004
Editora
SPIE