Blind Separation of Noisy Multivariate Data Using Second-Order Statistics: Remote-Sensing Applications

Blind Separation of Noisy Multivariate Data Using Second-Order Statistics: Remote-Sensing Applications

In this paper a second-order method for blind source separation of noisy instantaneous linear mixtures is presented for the case where the signal order k is unknown. Its performance advantages are illustrated by simulations and by application to Airborne Visible/Infrared Imaging Spectrometer (AVIRIS...

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Bibliographic Details
Main Authors: Mueller, Amy V., Herring, Keith T., Staelin, David H.
Other Authors: Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Format: Article
Language:en_US
Published: Institute of Electrical and Electronics Engineers 2010
Subjects:
separation
remote sensing
image representation
estimation
Blind signal separation (BSS)
Online Access:http://hdl.handle.net/1721.1/52428
https://orcid.org/0000-0001-8745-9006

Internet

http://hdl.handle.net/1721.1/52428
https://orcid.org/0000-0001-8745-9006

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