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  Fusion of spectral and spatial information by a novel SVM classification technique

Bruzzone, L., Marconcini, M., & Persello, C. (2007). Fusion of spectral and spatial information by a novel SVM classification technique. In IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2007) (pp. 4838-4841). Piscataway, NJ, USA: IEEE.

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Datensatz-Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-CCB9-3 Versions-Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-CCBA-1
Genre: Konferenzbeitrag

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 Urheber:
Bruzzone, L, Autor
Marconcini, M, Autor
Persello, C1, Autor           
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              

Inhalt

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Schlagwörter: -
 Zusammenfassung: A novel context-sensitive semisupervised classification technique based on support vector machines is proposed. This technique aims at exploiting the SVM method for image classification by properly fusing spectral information with spatial- context information. This results in: i) an increased robustness to noisy training sets in the learning phase of the classifier; ii) a higher and more stable classification accuracy with respect to the specific patterns included in the training set; and iii) a regularized classification map. The main property of the proposed context sensitive semisupervised SVM (CS4VM) is to adaptively exploit the contextual information in the training phase of the classifier, without any critical assumption on the expected labels of the pixels included in the same neighborhood system. This is done by defining a novel context-sensitive term in the objective function used in the learning of the classifier. In addition, the proposed CS4VM can be integrated with a Markov random field (MRF) approach for exploiting the contextual information also to regularize the classification map. Experiments carried out on very high geometrical resolution images confirmed the effectiveness of the proposed technique.

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Sprache(n):
 Datum: 2007-07
 Publikationsstatus: Erschienen
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: ISBN: 978-1-4244-1211-2
URI: http://www.grss-ieee.org/event/igarss-2007/
DOI: 10.1109/IGARSS.2007.4423944
BibTex Citekey: BruzzoneMP2007
 Art des Abschluß: -

Veranstaltung

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Titel: IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2007)
Veranstaltungsort: Barcelona, Spain
Start-/Enddatum: -

Entscheidung

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Titel: IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2007)
Genre der Quelle: Konferenzband
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: Piscataway, NJ, USA : IEEE
Seiten: - Band / Heft: - Artikelnummer: - Start- / Endseite: 4838 - 4841 Identifikator: -