Utilisation of contour criteria in micro-segmentation of SAR images

  title={Utilisation of contour criteria in micro-segmentation of SAR images},
  author={Jean-Marie Beaulieu},
  journal={International Journal of Remote Sensing},
  pages={3497 - 3512}
  • Jean-Marie Beaulieu
  • Published 1 September 2004
  • Environmental Science
  • International Journal of Remote Sensing
The segmentation of SAR (Synthetic Aperture Radar) images is greatly complicated by the presence of coherent speckle. To carry out this process a hierarchical segmentation algorithm based on stepwise optimization is used. It starts with each individual pixel as a segment and then sequentially merges the segment pair that minimizes the criterion. In a hypothesis testing approach, we show how the stepwise merging criterion is derived from the probability model of image regions. The Ward criterion… 

Pseudo-convex Contour Criterion for Hierarchical Segmentation of SAR Images

  • Jean-Marie Beaulieu
  • Mathematics
    The 3rd Canadian Conference on Computer and Robot Vision (CRV'06)
  • 2006
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Segmentation of polarimetric SAR image is a difficult problem. We show that image segmentation can be viewed as a likelihood approximation problem. The optimum criterion is derived for a hierarchical

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Segmentation of textured polarimetric SAR scenes by likelihood approximation

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  • Jean-Marie BeaulieuR. Touzi
  • Environmental Science, Mathematics
    IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477)
  • 2003
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The objective of the thesis is to show and illustrate the advantages of the hierarchical segmentation and clustering for the analysis of polarimetric radar images and improve the results of H/A/alpha classification and Wishart clustering.

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  • F. BovoloL. Bruzzone
  • Environmental Science, Mathematics
    IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium
  • 2008
This paper presents a novel adaptive technique for change detection in very high geometrical resolution (VHR) Synthetic Aperture Radar (SAR) images that exploits information theoretical similarity

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Synthetic Aperture Radar (SAR) images have a high geomorphologic information content. Due to the particular operation of this sensor the geomorphologic features of the Earth's surface are enhanced,

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A fully automatic, unsupervised segmentation algorithm, based on the iterative application of the new filter, is described and successfully applied to ERS-1 Synthetic Aperture Radar (SAR) images of sea ice.

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