Dynamic Hierarchical Segmentation of Remote Sensing Images

  • Giuseppe Scarpa
  • Giuseppe Masi
  • Raffaele Gaetano
  • Luisa Verdoliva
  • Giovanni Poggi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8156)


Recursive tree-structured segmentation is a powerful tool to deal with the non-stationary nature of images. By fitting model parameters to each region/class under analysis one can adapt the segmentation algorithm to the local image statistics, thus improving accuracy. However, a single model/segmenter cannot fit regions with wildly different nature, and one should be allowed to select in a suitable library the tool most suited to the local statistics. In this paper, we implement this dynamic segmentation/classification paradigm, using two segmenters, based on spectral and textural properties, respectively, and defining suitable rules for switching model locally. Experiments on remote-sensing mosaics show that the multiple-model dynamic algorithm largely outperforms comparable single-model segmenters.


Image segmentation image model hierarchical segmentation 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Giuseppe Scarpa
    • 1
  • Giuseppe Masi
    • 1
  • Raffaele Gaetano
    • 2
  • Luisa Verdoliva
    • 1
  • Giovanni Poggi
    • 1
  1. 1.DIETIUniversity Federico II of NaplesItaly
  2. 2.TELECOM-ParisTechFrance

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