Hierarchical Segmentation of Polarimetric SAR Images using Heterogeneous Clutter Models

In this paper, heterogeneous clutter models are introduced to describe Polarimetric Synthetic Aperture Radar (PolSAR) data. Based on the Spherically Invariant Random Vectors (SIRV) estimation scheme, the scalar texture parameter and the normalized covariance matrix are extracted. If the texture parameter is modeled by a Fisher PDF, the observed target scattering vector follows a KummerU PDF. Then, this PDF is implemented in a hierarchical segmentation algorithm. Segmentation results are shown on high resolution PolSAR data at L and X band.

Keywords

PolSAR data Segmentation KummerU PDF Fisher PDF Spherically Invariant Random Vectors

Domains

Signal and Image Processing Signal and Image processing

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Bombrun09_IGARSS.pdf (609.73 Ko)

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Lionel Bombrun : Connect in order to contact the contributor

https://hal.science/hal-00398923

Submitted on : Thursday, June 25, 2009-11:02:06 AM

Last modification on : Thursday, April 4, 2024-9:38:01 PM

Long-term archiving on: Monday, October 15, 2012-2:42:09 PM

Dates and versions

hal-00398923 , version 1 (25-06-2009)

Identifiers

HAL Id : hal-00398923 , version 1
DOI : 10.1109/IGARSS.2009.5418271

Cite

Lionel Bombrun, Jean-Marie Beaulieu, Gabriel Vasile, Jean-Philippe Ovarlez, Frédéric Pascal, et al.. Hierarchical Segmentation of Polarimetric SAR Images using Heterogeneous Clutter Models. IGARSS 2009 - IEEE International Geoscience and Remote Sensing Symposium, Jul 2009, Le Cap, South Africa. pp.5-8, ⟨10.1109/IGARSS.2009.5418271⟩. ⟨hal-00398923⟩

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