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Active contours driven by local Gaussian distribution fitting energy

于 2022-01-28 发布文件大小:1.16 MB

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This paperpresentsanewregion-basedactivecontourmodelinavariationallevelset formulationforimagesegmentation.Inourmodel,thelocalimageintensitiesare describedbyGaussiandistributionswithdifferentmeansandvariances.Wedefinea local Gaussiandistributionfittingenergywithalevelsetfunctionandlocalmeansand variancesasvariables.Theenergyminimizationisachievedbyaninterleavedlevelset evolution andestimationoflocalintensitymeansandvariancesinaniterativeprocess. The meansandvariancesoflocalintensitiesareconsideredasspatiallyvarying functionstohandleintensityinhomogeneitiesandnoiseofspatiallyvaryingstrength (e.g. multiplicativenoise).Inaddition,ourmodelisabletodistinguishregionswith similarintensitymeansbutdifferentvariances.Thisisdemonstratedbyapplyingour methodonnoisyandtextureimagesinwhichthetexturepatternsofdifferentregions can bedistinguishedfromthelocalintensityvariance.Comparativeexperimentsshow the advantagesofth

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