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}band.

[1]  Gabriel Vasile,et al.  Coherency Matrix Estimation of Heterogeneous Clutter in High-Resolution Polarimetric SAR Images , 2010, IEEE Transactions on Geoscience and Remote Sensing.

[2]  Philippe Forster,et al.  Covariance Structure Maximum-Likelihood Estimates in Compound Gaussian Noise: Existence and Algorithm Analysis , 2008, IEEE Transactions on Signal Processing.

[3]  A. Doulgeris,et al.  A RELAXED WISHART MODEL FOR POLARIMETRIC SAR DATA , 2009 .

[4]  K. Ranson,et al.  K-distribution for multi-look processed polarimetric SAR imagery , 1994, Proceedings of IGARSS '94 - 1994 IEEE International Geoscience and Remote Sensing Symposium.

[5]  Kung Yao,et al.  A representation theorem and its applications to spherically-invariant random processes , 1973, IEEE Trans. Inf. Theory.

[6]  Jean-Marie Nicolas.  1 - Introduction aux Statistiques de deuxième espèce : applications des Logs-moments et des Logs-cumulants à l'analyse des lois d'images radar , 2002 .

[7]  Xavier Dupuis,et al.  Polarimetric and Interferometric SAR Image Partition Into Statistically Homogeneous Regions Based on the Minimization of the Stochastic Complexity , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[8]  Philippe Forster,et al.  Performance Analysis of Covariance Matrix Estimates in Impulsive Noise , 2008, IEEE Transactions on Signal Processing.

[9]  Lionel Bombrun,et al.  Fisher Distribution for Texture Modeling of Polarimetric SAR Data , 2008, IEEE Geoscience and Remote Sensing Letters.

[10]  Jean-Marie Nicolas,et al.  Unsupervised Synthetic Aperture Radar Image Segmentation Using Fisher Distributions , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[11]  Knut Conradsen,et al.  Polarimetric segmentation using Wishart test statistic , 2002, IEEE International Geoscience and Remote Sensing Symposium.

[12]  Thomas L. Ainsworth,et al.  Unsupervised classification using polarimetric decomposition and the complex Wishart classifier , 1999, IEEE Trans. Geosci. Remote. Sens..

[13]  Deniz Erdoğmuş,et al.  Clustering using Renyi's entropy , 2003, Proceedings of the International Joint Conference on Neural Networks, 2003..

[14]  Gabriel Vasile,et al.  Hierarchical segmentation of Polarimetric SAR images using heterogeneous clutter models , 2009, 2009 IEEE International Geoscience and Remote Sensing Symposium.

[15]  G. J. Hahn,et al.  Statistical models in engineering , 1967 .

[16]  Eric Pottier,et al.  An entropy based classification scheme for land applications of polarimetric SAR , 1997, IEEE Trans. Geosci. Remote. Sens..

[17]  S. Kotz,et al.  Symmetric Multivariate and Related Distributions , 1989 .

[18]  Stephen L. Durden,et al.  A three-component scattering model for polarimetric SAR data , 1998, IEEE Trans. Geosci. Remote. Sens..

[19]  Jean-Marie Nicolas,et al.  Application de la transformée de Mellin : étude des lois statistiques de l'imagerie cohérente , 2006 .

[20]  Ridha Touzi,et al.  Segmentation of textured polarimetric SAR scenes by likelihood approximation , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[21]  Milton Abramowitz,et al.  Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables , 1964 .

[22]  Fulvio Gini,et al.  Covariance matrix estimation for CFAR detection in correlated heavy tailed clutter , 2002, Signal Process..

[23]  S. Quegan,et al.  Statistical models for polarimetric SAR data , 1994, Proceedings of IGARSS '94 - 1994 IEEE International Geoscience and Remote Sensing Symposium.

[24]  Philip Chan,et al.  Determining the number of clusters/segments in hierarchical clustering/segmentation algorithms , 2004, 16th IEEE International Conference on Tools with Artificial Intelligence.

[25]  Steeve Zozor,et al.  Some Results on the Denoising Problem in the Elliptically Distributed Context , 2010, IEEE Transactions on Signal Processing.

[26]  Ridha Touzi,et al.  Target Scattering Decomposition in Terms of Roll-Invariant Target Parameters , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[27]  Alejandro C. Frery,et al.  The polarimetric 𝒢 distribution for SAR data analysis , 2005 .

[28]  Henri Maître,et al.  A new statistical model for Markovian classification of urban areas in high-resolution SAR images , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[29]  L. Ferro-Famil,et al.  Segmentation of polarimetric SAR images , 2001, IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217).

[30]  N. H. C. Yung,et al.  Watershed segmentation with boundary curvature ratio based merging criterion , 2007, SIP.

[31]  Yacine Chitour,et al.  Exact Maximum Likelihood Estimates for SIRV Covariance Matrix: Existence and Algorithm Analysis , 2008, IEEE Transactions on Signal Processing.

[32]  Gabriel Vasile,et al.  Normalized Coherency Matrix Estimation Under the SIRV Model. Alpine Glacier Polsar Data Analysis , 2008, IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium.

[33]  José Carlos Príncipe,et al.  Information Theoretic Clustering , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[34]  R. Garello,et al.  Statistical modelling of ocean SAR images , 1997 .