Volume 36 Issue 9
Sep.  2011
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ZHANG Bin, MA Guorui, LIU Guoying, QIN Qianqing. MRF-Based Segmentation Algorithm Combined with Freeman Decomposition and Scattering Entropy for Polarimetric SAR Images[J]. Geomatics and Information Science of Wuhan University, 2011, 36(9): 1064-1067.
Citation: ZHANG Bin, MA Guorui, LIU Guoying, QIN Qianqing. MRF-Based Segmentation Algorithm Combined with Freeman Decomposition and Scattering Entropy for Polarimetric SAR Images[J]. Geomatics and Information Science of Wuhan University, 2011, 36(9): 1064-1067.
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MRF-Based Segmentation Algorithm Combined with Freeman Decomposition and Scattering Entropy for Polarimetric SAR Images

  • 1School of Electronic Information,Wuhan University,129 Luoyu Road,Wuhan 430079,China;2 State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing,Wuhan University,129 Luoyu Road,Wuhan 430079,China;3School of Computer and Information Engineering,Anyang Normal University,Xian'ge Road,Anyang 455002,China

Funds: 国家自然科学基金资助项目(61001187,60602013,41001251,40971219)
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  • Received Date: July 12, 2011
  • Published Date: September 04, 2011
    Graphical Abstract
    • Abstract
  • A new segmentation algorithm is proposed for polarimetric SAR images based on Markov random field combined with Freeman decomposition and scattering entropy.Firstly,Freeman decomposition theory is adopted to obtain four kinds of scattering characteristics,which are surface scattering,double scattering,volume scattering and mixed scattering,and scattering entropy is exacted by H/Alpha decomposition.Then,the terrain can be divided into 12 initial clusters.Secondly,an agglomerative hierarchical clustering algorithm is introduced to reduce the number of clusters.Finally,by adopting Wishart distribution to model the character field,simulated annealing model method(SA) based on maximum a posteriori criterion is used to acquire the segmentation results.Using fully polarimetric SAR images acquired by the NASA/ JPL and E-SAR,the experimental results show the effectiveness and superiority of this algorithm.
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