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1、FromProceedingsofImagingUnderstandingWorkshop,pp.121-130(1981).AnIterativeImageRegistrationTechniquewithanApplicationtoStereoVisionBruceD.LucasTakeoKanadeComputerScienceDepartmentCarnegie-MellonUniversityPittsburgh,Pennsylvania15213Abstract2.TheregistrationproblemImageregistrationfi
2、ndsavarietyofapplicationsinThetranslationalimageregistrationproblemcanbecomputervision.Unfortunately,traditionalimageregistrationcharacterizedasfollows:WearegivenfunctionsF(x)andtechniquestendtobecostly.WepresentanewimageG(x)whichgivetherespectivepixelvaluesateachlocationregistratio
3、ntechniquethatmakesuseofthespatialintensityxintwoimages,wherexisavector.WewishtofindthegradientoftheimagestofindagoodmatchusingatypeofdisparityvectorhwhichminimizessomemeasureoftheNewton-Raphsoniteration.OurtechniqueisfasterbecausedifferencebetweenF(x+h)andG(x),forxinsomeregionofite
4、xaminesfarfewerpotentialmatchesbetweentheimagesinterestR.(Seefigure1).thanexistingtechniques.Furthermore,thisregistrationtechniquecanbegeneralizedtohandlerotation,scalingandshearing.Weshowshowourtechniquecanbeadaptedforuseinastereovisionsystem.1.IntroductionImageregistrationfindsava
5、rietyofapplicationsincomputervision,suchasimagematchingforstereovision,patternrecognition,andmotionanalysis.Untortunately,Figure1:Theimageregistrationproblemexistingtechniquesforimageregistrationtendtobecostly.Moreover,theygenerallyfailtodealwithrotationorotherTypicalmeasuresofthedi
6、fferencebetweenF(x+h)anddistortionsoftheimages.G(x)are:Inthispaperwepresentanewimageregistration?L1norm=?e
7、(FxhGx+-)()
8、techniquethatusesspatialintensitygradientinformationtoxRdirectthesearchforthepositionthatyieldsthebestmatch.12/Bytakingmoreinformationabouttheimagesintoaccount,?Lno
9、rm=()[]FxhGx()(+-)22?xRethistechniqueisabletofindthebestmatchbetweentwoimageswithfarfewercomparisonsofimagesthan?negativeofnormalizedcorrelationtechniqueswhichexaminethepossiblepositionsofregistrationinsomefixedorder.Ourtechniquetakesadvantageofthefactthatinmanyapplicationsthetwo=-+
10、?xReFxhGx()()images
