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Proceedings Paper

Non-parametric partitioning of SAR images
Author(s): G. Delyon; F. Galland; Ph. Réfrégier
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Paper Abstract

We describe and analyse a generalization of a parametric segmentation technique adapted to Gamma distributed SAR images to a simple non parametric noise model. The partition is obtained by minimizing the stochastic complexity of a quantized version on Q levels of the SAR image and lead to a criterion without parameters to be tuned by the user. We analyse the reliability of the proposed approach on synthetic images. The quality of the obtained partition will be studied for different possible strategies. In particular, one will discuss the reliability of the proposed optimization procedure. Finally, we will precisely study the performance of the proposed approach in comparison with the statistical parametric technique adapted to Gamma noise. These studies will be led by analyzing the number of misclassified pixels, the standard Hausdorff distance and the number of estimated regions.

Paper Details

Date Published: 29 September 2006
PDF: 11 pages
Proc. SPIE 6365, Image and Signal Processing for Remote Sensing XII, 636514 (29 September 2006); doi: 10.1117/12.687579
Show Author Affiliations
G. Delyon, Fresnel Institute, CNRS, Domaine Univ. de Saint-Jérôme (France)
F. Galland, Fresnel Institute, CNRS, Domaine Univ. de Saint-Jérôme (France)
Ph. Réfrégier, Fresnel Institute, CNRS, Domaine Univ. de Saint-Jérôme (France)


Published in SPIE Proceedings Vol. 6365:
Image and Signal Processing for Remote Sensing XII
Lorenzo Bruzzone, Editor(s)

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