A New Algorithm for Bilinear Spectral Unmixing of Hyperspectral Images Using Particle Swarm Optimization

Spectral unmixing is an important technique for exploiting hyperspectral data. The presence of nonlinear mixing effects poses an important problem when attempting to provide accurate estimates of the abundance fractions of pure spectral components (endmembers) in a scene. This problem complicates th...

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Vydané v:	IEEE journal of selected topics in applied earth observations and remote sensing Ročník 9; číslo 12; s. 5776 - 5790
Hlavní autori:	Luo, Wenfei, Gao, Lianru, Plaza, Antonio, Marinoni, Andrea, Yang, Bin, Zhong, Liang, Gamba, Paolo, Zhang, Bing
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 01.12.2016 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Algorithm design and analysis Algorithms Computational modeling Hyperspectral imaging Linear programming Mixtures Motivation multiobjective optimization (MO) Multiple objective analysis Nonlinearity Optimization Optimization techniques Particle swarm optimization particle swarm optimization (PSO) simplex volume minimization spectral unmixing
ISSN:	1939-1404, 2151-1535
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