• DocumentCode
    2206478
  • Title

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

  • Author

    Kurtz, Camille ; Puissant, Anne ; Passat, Nicolas ; Gançarski, Pierre

  • Author_Institution
    LSIIT, Univ. of Strasbourg, Strasbourg, France
  • fYear
    2012
  • fDate
    22-27 July 2012
  • Firstpage
    1773
  • Lastpage
    1776
  • 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 segmentation 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
    geophysical image processing; geophysical techniques; image classification; image segmentation; remote sensing; VHSR images; complex urban pattern extraction; data complexity; domain adaptation; large dataset processing; multiresolution satellite images; object classification; object segmentation; urban images; very high spatial resolution images; Data mining; Image segmentation; Indexes; Remote sensing; Satellites; Spatial resolution; Clustering; Domain adaptation; Hierarchical segmentation; Multiresolution satellite images; Urban analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
  • Conference_Location
    Munich
  • ISSN
    2153-6996
  • Print_ISBN
    978-1-4673-1160-1
  • Electronic_ISBN
    2153-6996
  • Type

    conf

  • DOI
    10.1109/IGARSS.2012.6351172
  • Filename
    6351172