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Conference Papers Year : 1998

Model-Based Segmentation of Cloud Structures In Satellite Image Sequences

Abstract

Meteorological image sequences acquired with remote sensing devices contain huge amounts of available data featuring the temporal evolution of highly deformable and complex structures. In this study is presented a robust and effective model-based segmentation procedure for approximating highly deformable cloud structures. The whole image sequence may be viewed as a 3D data set, but the classical techniques for performing 3D segmentation are not meaningful here, because cloud structures are not shapes in the classical sense. The model-based segmentation presented here uses level-sets controlled by particle systems. A specific energy formulation is introduced, permitting the use of robust conjugate gradient techniques. The model is validated on a real meteorological image sequence. We outline the generalizations of the this particle system to perform image analysis tasks on truly 3D images.
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Dates and versions

inria-00423792 , version 1 (12-10-2009)

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  • HAL Id : inria-00423792 , version 1

Cite

Hussein M. Yahia, Jean-Paul Berroir, Gilles Mazars. Model-Based Segmentation of Cloud Structures In Satellite Image Sequences. ICCV - Proceedings of the IEEE International Conference on Computer Vision, Jan 1998, Mumbai, India. pp.77-85. ⟨inria-00423792⟩

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