Title :
Hierarchical segmentation of Polarimetric SAR images using heterogeneous clutter models
Author :
Bombrun, L. ; Beaulieu, J.-M. ; Vasile, G. ; Ovarlez, J.P. ; Pascal, F. ; Gay, M.
Author_Institution :
Grenoble-Image-sPeach-Signal-Automatics Lab., CNRS, Grenoble, France
Abstract :
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 :
geophysical image processing; geophysical techniques; image segmentation; image texture; radar clutter; radar polarimetry; remote sensing by radar; synthetic aperture radar; Fisher PDF; L band high resolution PolSAR data; X band high resolution PolSAR data; heterogeneous clutter models; hierarchical image segmentation; hierarchical segmentation algorithm; normalized covariance matrix; polarimetric SAR images; polarimetric synthetic aperture radar data; scalar texture parameter; spherically invariant random vectors estimation scheme; target scattering vector; Backscatter; Clutter; Covariance matrix; Data mining; Image segmentation; L-band; Maximum likelihood estimation; Parameter estimation; Radar scattering; Testing; Fisher PDF; KummerU PDF; PolSAR data; Segmentation; Spherically Invariant Random Vectors;
Conference_Titel :
Geoscience and Remote Sensing Symposium,2009 IEEE International,IGARSS 2009
Conference_Location :
Cape Town
Print_ISBN :
978-1-4244-3394-0
Electronic_ISBN :
978-1-4244-3395-7
DOI :
10.1109/IGARSS.2009.5418271
