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)


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.


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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