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Orientador(es)
Resumo(s)
One of the most challenging task underlying many hyperspectral imagery applications is the linear unmixing. The key to linear unmixing is to find the set of reference substances, also called endmembers, that are representative of a given scene.
This paper presents the vertex component analysis (VCA) a new method to unmix linear mixtures of hyperspectral sources. The algorithm is unsupervised and 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 effectiveness of the proposed scheme is illustrated using simulated data.
Descrição
Palavras-chave
Extraction of endmembers spectra Hyperspectral data
Contexto Educativo
Citação
NASCIMENTO, José M. P.; BIOUCAS-DIAS, José M. - Fast unsupervised extraction of endmembers spectra from hyperspectral data. Fourth Conference on Telecommunications - SPIE - The International Society for Optical Engineering. ISSN 0277-788X. 537-540, 2003
Editora
Society of Photo-optical Instrumentation Engineers