Unsupervised Polarimetric SAR Image Classification

Junyi XU  Jian YANG  Yingning PENG  Chao WANG  

IEICE TRANSACTIONS on Communications   Vol.E87-B   No.4   pp.1048-1052
Publication Date: 2004/04/01
Online ISSN: 
Print ISSN: 0916-8516
Type of Manuscript: LETTER
Category: Sensing
polarimetry,  radar remote sensing,  terrain classification,  cross-entropy,  

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In this letter, the concept of cross-entropy is introduced for unsupervised polarimetric synthetic aperture radar (SAR) image classification. The difference between two scatterers is decomposed into three parts, i.e., the difference of average scattering characteristic, the difference of scattering randomness and the difference of scattering matrix span. All these three parts are expressed in cross-entropy formats. The minimum cross-entropy principle is adopted to make classification decision. It works well in unsupervised terrain classification with a NASA/JPL AIRSAR image.