Title
Domain adaptation with hidden Markov random fields Domain adaptation with hidden Markov random fields
Author
Faculty/Department
Faculty of Sciences. Physics
Publication type
conferenceObject
Publication
S.l. , [*]
Subject
Physics
Source (book)
IEEE IGARSS 2013, International Geoscience and Remote Sensing Symposium , Melbourne, Australia, July 21-26
ISSN
2153-6996
ISI
000345638903046
ISBN
978-1-4799-1114-1
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
Affiliation
University of Antwerp
Abstract
In this paper, we propose a method to match multitemporal sequences of hyperspectral images using Hidden Markov Random Fields. Based on the matching of the data manifold, the algorithm matches the reflectance spectra of the classes, thus allowing the reuse of labeled examples acquired on one image to classify the other. This allows valorization of spectra collected in situ to other acquisitions than the one they were acquired for, without user supervision, prior knowledge of the class reflectance in the new domain or global information about atmospheric conditions.
E-info
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