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...

ver descrição completa

Detalhes bibliográficos
Autor principal: Nascimento, Jose (author)
Outros Autores: Bioucas-Dias, José M. (author)
Formato: conferenceObject
Idioma:eng
Publicado em: 2016
Assuntos:
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
Texto completo:http://hdl.handle.net/10400.21/6153
País:Portugal
Oai:oai:repositorio.ipl.pt:10400.21/6153

Texto Completo

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

Registos relacionados