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Structural high-resolution satellite image indexing

  • Gui Song Xia
  • , Wen Yang
  • , Julie Delon
  • , Yann Gousseau
  • , Hong Sun
  • , Henri Maître
  • CNRS
  • Wuhan University

Résultats de recherche: Contribution à un journalArticle de conférenceRevue par des pairs

Résumé

Satellite images with high spatial resolution raise many challenging issues in image understanding and pattern recognition. First, they allow measurement of small objects maybe up to 0.5 m, and both texture and geometrical structures emerge simultaneously. Second, objects in the same type of scenes might appear at different scales and orientations. Consequently, image indexing methods should combine the structure and texture information of images and comply with some invariant properties. This paper contributes to the indexing of high-resolution satellite images. We suggest a satellite image indexing method relying on topographic maps and a shape-based image indexing scheme. The proposed approach contains both the textural and structural information of satellite images and is also robust to changes in scale, orientation and contrast. Experimental analysis on a real satellite image database confirms the efficiency of the approach.

langue originaleAnglais
Pages (de - à)298-303
Nombre de pages6
journalInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
Volume38
étatPublié - 1 janv. 2010
EvénementISPRS Technical Commission VII Symposium on Advancing Remote Sensing Science - Vienna, Autriche
Durée: 5 juil. 20107 juil. 2010

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