Hyperspectral unmixing algorithm via dependent component analysis

This paper introduces a new method to blindly unmix hyperspectral data, termed dependent component analysis (DECA). This method decomposes a hyperspectral images into a collection of reflectance (or radiance) spectra of the materials present in the scene (endmember signatures) and the corresponding...

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Bibliographic Details
Main Author: Nascimento, Jose (author)
Other Authors: Bioucas-Dias, José M. (author)
Format: conferenceObject
Language:eng
Published: 2016
Subjects:
Expectation-maximisation algorithm
Geophysical techniques
Geophysics computing
Dirichlet densities
Abundance fractions
Dependent component analysis
Generalized expectation-maximization algorithm
Hyperspectral unmixing algorithm
Algorithm design and analysis
Hyperspectral imaging
Hyperspectral sensors
Ice
Independent component analysis
Infrared image sensors
Laboratories
Layout
Reflectivity
Telecommunications
Online Access:http://hdl.handle.net/10400.21/6153
Country:Portugal
Oai:oai:repositorio.ipl.pt:10400.21/6153

Internet

http://hdl.handle.net/10400.21/6153

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