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Title
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Domain adaptation with hidden Markov random fields
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Author
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Abstract
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| 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. |
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Language
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English
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Source (journal)
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IEEE International Geoscience and Remote Sensing Symposium proceedings. - [New York]
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Source (book)
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IEEE IGARSS 2013, International Geoscience and Remote Sensing Symposium , Melbourne, Australia, July 21-26
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Publication
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S.l.
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Institute of Electrical and Electronics Engineers
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2013
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ISSN
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2153-6996
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ISBN
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978-1-4799-1114-1
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DOI
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10.1109/IGARSS.2013.6723485
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Volume/pages
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p. 3112-3115
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ISI
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000345638903046
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Full text (Publisher's DOI)
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