简介：AimingtosolvethemisclassificationproblemsofunsupervisedpolarimetricWishartclassificationalgorithmbasedonFreemandecomposition,anunsupervisedPolarimetricSyntheticApertureRadar(SAR)Interferomery(PolInSAR)classificationalgorithmbasedonoptimalcoherencesetparametersisstudiedandproposed.ThisalgorithmusestheresultofFreemandecompositiontodividetheimageintothreebasiccategoriesincludingsurfacescattering,volumescattering,anddouble-bounce.Then,thePolInSARoptimalcoherencesetparametersareusedtofinelydivideeachofthethreebasiccategoriesinto9categories,andthewholeimageisdividedinto27categories.BecauseboththeFreemandecompositionresultandoptimalcoherencesetparametersindicatespecificscatteringcharacteristics,thewholeimageismergedinto16categoriesbasedonphysicalmeaning.Atlast,theWishartclusterisemployedtoobtainthefinalclassificationresult.Topreservethepurityofscatteringcharacteristics,pixelswithsimilarscatteringcharacteristicsarerestrictedtobeclassifiedwithotherpixels.Thefinalclassificationresultseffectivelyresolvethemisclassificationproblem,notonlythebuildingscanbeeffectivelydistinguishedfromvegetationinurbanareas,butalsotheroadiswelldistinguishedfromgrass.Inthispaper,theE-SARPolInSARdataofGermanAerospaceCenter(DLR),areusedtoverifytheeffectivenessofthealgorithm.