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SAR Image Segmentation Based on Level Set Approach and {\cal G}_A^0 Model
Oct. 2012 (vol. 34 no. 10)
pp. 2046-2057
Regis C. Pinheiro Marques, Federal University of Ceara, Fortaleza
Fátima N. Medeiros, Federal University of Ceara, Fortaleza
Juvencio Santos Nobre, Federal University of Ceara, Fortaleza
This paper proposes an image segmentation method for synthetic aperture radar (SAR), exploring statistical properties of SAR data to characterize image regions. We consider {\cal G}_A^0 distribution parameters for SAR image segmentation, combined to the level set framework. The {\cal G}_A^0 distribution belongs to a class of {\cal G} distributions that have been successfully used to model different regions in amplitude SAR images for data modeling purpose. Such statistical data model is fundamental to deriving the energy functional to perform region mapping, which is input into our level set propagation numerical scheme that splits SAR images into homogeneous, heterogeneous, and extremely heterogeneous regions. Moreover, we introduce an assessment procedure based on stochastic distance and the {\cal G}_A^0 model to quantify the robustness and accuracy of our approach. Our results demonstrate the accuracy of the algorithms regarding experiments on synthetic and real SAR data.
Index Terms:
Level set,Image segmentation,Mathematical model,Data models,Equations,Synthetic aperture radar,Speckle,G-amplitude zero distribution.,Speckle,SAR image,segmentation,level sets,energy functional
Citation:
Regis C. Pinheiro Marques, Fátima N. Medeiros, Juvencio Santos Nobre, "SAR Image Segmentation Based on Level Set Approach and {\cal G}_A^0 Model," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 34, no. 10, pp. 2046-2057, Oct. 2012, doi:10.1109/TPAMI.2011.274
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