Utilize este identificador para referenciar este registo:
http://hdl.handle.net/10400.21/6143
Título: | Hyperspectral imagery framework for unmixing and dimensionality estimation |
Autor: | Nascimento, Jose Bioucas-Dias, José M. |
Palavras-chave: | Blind hyperspectral unmixing Minimum volume simplex Minimum description length MDL Variable splitting augmented lagrangian Dimensionality reduction |
Data: | 2013 |
Editora: | Springer-Verlag |
Citação: | NASCIMENTO, José M. P.; BIOUCAS-DIAS, José M. - Hyperspectral imagery framework for unmixing and dimensionality estimation. Pattern Recognition - Applications and Methods. ISBN 978-3-642-36529-4. Vol. 204. 193-204, 2013 |
Relatório da Série N.º: | Advances in Intelligent Systems and Computing; |
Resumo: | In hyperspectral imagery a pixel typically consists mixture of spectral signatures of reference substances, also called endmembers. Linear spectral mixture analysis, or linear unmixing, aims at estimating the number of endmembers, their spectral signatures, and their abundance fractions. This paper proposes a framework for hyperpsectral unmixing. A blind method (SISAL) is used for the estimation of the unknown endmember signature and their abundance fractions. This method solve a non-convex problem by a sequence of augmented Lagrangian optimizations, where the positivity constraints, forcing the spectral vectors to belong to the convex hull of the endmember signatures, are replaced by soft constraints. The proposed framework simultaneously estimates the number of endmembers present in the hyperspectral image by an algorithm based on the minimum description length (MDL) principle. Experimental results on both synthetic and real hyperspectral data demonstrate the effectiveness of the proposed algorithm. |
Peer review: | yes |
URI: | http://hdl.handle.net/10400.21/6143 |
DOI: | 10.1007/978-3-642-36530-0_16 |
ISBN: | 978-3-642-36529-4 978-3-642-36530-0 |
ISSN: | 2194-5357 2194-5365 |
Aparece nas colecções: | ISEL - Eng. Elect. Tel. Comp. - Capítulos ou partes de livros |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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Hyperspectral imagery framework for unmixing and dimensionality estimation.pdf | 548,96 kB | Adobe PDF | Ver/Abrir Acesso Restrito. Solicitar cópia ao autor! |
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