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dc.contributor.authorLuppino, Luigi Tommaso
dc.contributor.authorAnfinsen, Stian Normann
dc.contributor.authorMoser, Gabriele
dc.contributor.authorJenssen, Robert
dc.contributor.authorBianchi, Filippo Maria
dc.contributor.authorSerpico, Sebastian Bruno
dc.contributor.authorMercier, Gregoire
dc.date.accessioned2022-11-07T10:07:22Z
dc.date.available2022-11-07T10:07:22Z
dc.date.issued2017-05-19
dc.description.abstractChange detection in heterogeneous multitemporal satellite images is a challenging and still not much studied topic in remote sensing and earth observation. This paper focuses on comparison of image pairs covering the same geographical area and acquired by two different sensors, one optical radiometer and one synthetic aperture radar, at two different times. We propose a clustering-based technique to detect changes, identified as clusters that split or merge in the different images. To evaluate potentials and limitations of our method, we perform experiments on real data. Preliminary results confirm the relationship between splits and merges of clusters and the occurrence of changes. However, it becomes evident that it is necessary to incorporate prior, ancillary, or application-specific information to improve the interpretation of clustering results and to identify unambiguously the areas of change.en_US
dc.identifier.citationLuppino LT, Anfinsen SN, Moser G, Jenssen R, Bianchi FM, Serpico SB, Mercier: A clustering approach to heterogeneous change detection. In: Sharma P, Bianchi FM. Image Analysis 20th Scandinavian Conference, SCIA 2017 Tromsø, Norway, June 12–14, 2017 Proceedings, Part II, 2017. Springer p. 181-192en_US
dc.identifier.cristinIDFRIDAID 1501131
dc.identifier.doi10.1007/978-3-319-59129-2_16
dc.identifier.isbn978-3-319-59128-5
dc.identifier.issn0302-9743
dc.identifier.issn1611-3349
dc.identifier.urihttps://hdl.handle.net/10037/27274
dc.language.isoengen_US
dc.publisherSpringeren_US
dc.relation.projectIDNorges forskningsråd: 251327en_US
dc.relation.urihttps://link.springer.com/chapter/10.1007/978-3-319-59129-2_16
dc.rights.accessRightsopenAccessen_US
dc.titleA clustering approach to heterogeneous change detectionen_US
dc.type.versionsubmittedVersionen_US
dc.typeChapteren_US
dc.typeBokkapittelen_US


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