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Multi-spectral Texture Characterisation for Remote Sensing Image Segmentation

  • Filiberto Pla
  • Gema Gracia
  • Pedro García-Sevilla
  • Majid Mirmehdi
  • Xianghua Xie
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5524)

Abstract

A multi-spectral texture characterisation model is proposed, the Multi-spectral Local Differences Texem – MLDT, as an affordable approach to be used in multi-spectral images that may contain large number of bands. The MLDT is based on the Texem model. Using an inter-scale post-fusion strategy for image segmentation, framed in a multi-resolution approach, we produce unsupervised multi-spectral image segmentations. Preliminary results on several remote sensing multi-spectral images exhibit a promising performance by the MLDT approach, with further improvements possible to model more complex textures and add some other features, like invariance to spectral intensity.

Keywords

Texture analysis multispectral images Texems 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Filiberto Pla
    • 1
  • Gema Gracia
    • 1
  • Pedro García-Sevilla
    • 1
  • Majid Mirmehdi
    • 2
  • Xianghua Xie
    • 3
  1. 1.Dept. Llenguatges i Sistemes InformàticsUniversity Jaume ICastellónSpain
  2. 2.Dept. of Computer ScienceUniversity of BristolBristolUK
  3. 3.Dept. of Computer ScienceUniversity of SwanseaSwanseaUK

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