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A lattice matrix method for hyperspectral image unmixing
GONZALO JORGE URCID SERRANO
Acceso Abierto
Atribución-NoComercial-SinDerivadas
Neural networks: Associative memories
Lattice associative memories
Lattice algebra: affine independence
Lattice independence
Lattice matrices
Hyperspectral image analysis: endmember
In this manuscript we propose a method for the autonomous determination of endmembers in hyperspectral imagery based on recent theoretical advancements on lattice autoassociative memories. Given a hyperspectral image, the lattice algebra approach finds in a single-pass all possible candidate endmembers from which various affinely independent sets of final endmembers may be derived. In contrast to other endmember detection methods, the endmembers found using two dual canonical lattice matrices are geometrically linked to the data set spectra. The mathematical foundation of the proposed method is first described in some detail followed by application examples that illustrate the key steps of the proposed lattice based method.
Information Sciences
2011
Artículo
Inglés
Estudiantes
Investigadores
Público en general
Ritter, Gerhard X. and Urcid Serrano, G. (2011). A lattice matrix method for hyperspectral image unmixing, Information Sciences. Vol. 181(10):1787–1803
ÓPTICA
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