Domain adaptation for the extraction of complex urban patterns from multiresolution satellite images

Camille Kurtz 1 Anne Puissant 2 Nicolas Passat 1 Pierre Gançarski 1
1 LSIIT - Laboratoire des Sciences de l'Image, de l'Informatique et de la Télédétection
2 LIVE - Laboratoire Image, Ville, Environnement
Abstract : The extraction of complex urban patterns from Very High Spatial Resolution (VHSR) images presents several challenges related to the complexity of the data. Based on the availability of images of a same scene at various resolutions (Medium to Very High Spatial resolutions), a hierarchical approach has been recently proposed to segment/classify objects of interest in a top-down fashion in order to determine patterns from VHSR images. To perform, this method requires the interactive definition of segmentation examples for each considered resolution image. In the context of large dataset processing, such interactive task becomes time consuming. To deal with this issue, we propose in this article, an extension of the domain adaptation paradigm enabling the transfer of the segmenta tion examples defined on a source dataset to automatically process a target one. Experiments performed on urban images provide satisfactory results which may be further used for operational needs.
Keywords : hierarchical segmentation Clustering Domain adaptation Multiresolution satellite images Urban analysis
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Camille Kurtz, Anne Puissant, Nicolas Passat, Pierre Gançarski. Domain adaptation for the extraction of complex urban patterns from multiresolution satellite images. International Geoscience and Remote Sensing Symposium (IGARSS), 2012, Munich, France. pp.1773-1776, ⟨10.1109/IGARSS.2012.6351172⟩. ⟨hal-01695057⟩

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