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1、IEEETRANSACTIONSONPATTERNANALYSISANDMACHINEINTELLIGENCE,VOL.33,NO.4,APRIL2011807RobustStereoMatchingUsingAdaptiveNormalizedCross-CorrelationYongSeokHeo,StudentMember,IEEE,KyoungMuLee,Member,IEEE,andSangUkLee,Fellow,IEEEAbstract—Amajorityoftheexistingstereomatchingalgorithmsassumethatthecorr
2、espondingcolorvaluesaresimilartoeachother.However,itisnotsoinpracticeasimagecolorvaluesareoftenaffectedbyvariousradiometricfactorssuchasilluminationdirection,illuminantcolor,andimagingdevicechanges.Forthisreason,therawcolorrecordedbyacamerashouldnotbereliedoncompletely,andtheassumptionofcol
3、orconsistencydoesnotholdgoodbetweenstereoimagesinrealscenes.Therefore,theperformanceofmostconventionalstereomatchingalgorithmscanbeseverelydegradedundertheradiometricvariations.Inthispaper,wepresentanewstereomatchingmeasurethatisinsensitivetoradiometricvariationsbetweenleftandrightimages.Un
4、likemoststereomatchingmeasures,weusethecolorformationmodelexplicitlyinourframeworkandproposeanewmeasure,calledtheAdaptiveNormalizedCross-Correlation(ANCC),forarobustandaccuratecorrespondencemeasure.Theadvantageofourmethodisthatitisrobusttolightinggeometry,illuminantcolor,andcameraparameterc
5、hangesbetweenleftandrightimages,anddoesnotsufferfromthefatteningeffectunlikeconventionalNormalizedCross-Correlation(NCC).Experimentalresultsshowthatourmethodoutperformsotherstate-of-the-artstereomethodsunderseverelydifferentradiometricconditionsbetweenstereoimages.IndexTerms—Stereomatching,
6、color,radiometricvariation,illumination,cameraexposure,gammacorrection.Ç1INTRODUCTION1.1MotivationInarealscenario,variousfactorspreventtwocorre-TEREOmatchingaimstoobtain3Dinformationbyfindingspondingpixelsfromhavingthesamecolorvalue.OneSthecorrectcorrespondencebetweenimagescapturedmajorprev
7、entingfactorisaradiometricchange,whichfromdifferentpointofviewsoratdifferenttimes.However,includeslightinggeometry,illuminantcolor,andcameradevicefindingtheaccuratecorrespondenceisnotaneasytask;changesbetweenstereoimages.Differentcolorvaluesarethereexist
