英文资料快速的基于相位的多式联运图像数据配准Word文件下载.docx

英文资料快速的基于相位的多式联运图像数据配准Word文件下载.docx

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Received19July2008;

revised14October2008;

accepted18October2008. 

Availableonline5November2008.

Abstract

Aninterestingprobleminpatternrecognitionisthatofimageregistration,whichplaysanimportantroleinmanyvision-basedrecognitionandmotionanalysisapplications.Ofparticularinterestamongregistrationproblemsaremultimodalregistrationproblems,wheretheimagesexistindifferentfeaturespaces.State-of-the-artphased-basedapproachestomultimodalimageregistrationmethodshaveprovidedgoodaccuracybuthavehighcomputationalcost.Thispaperpresentsafastphase-basedapproachtoregisteringmultimodalimagesforthepurposeofinitialcoarse-grainedregistration.Thisisaccomplishedbysimultaneouslyperformingbothgloballyexhaustivedynamicphasesub-cloudmatchingandpolynomialfeaturespacetransformationestimationinthefrequencydomainusingthefastFouriertransform（FFT）.Amultiscalephase-basedfeatureextractionmethodisproposedthatdeterminesboththelocationandsizeofthedynamicsub-cloudsbeingextracted.Asimpleoutlierpruningbasedonresamplingisusedtoremovefalsekeypointmatches.Theproposedphase-basedapproachtoregistrationcanbeperformedveryefficientlywithouttheneedforinitialestimatesorequivalentkeypointsfrombothimages.Experimentalresultsshowthattheproposedmethodcanprovideaccuraciescomparabletothestate-of-the-artphase-basedimageregistrationmethodsforthepurposeofinitialcoarse-grainedregistrationwhilebeingmuchfastertocompute.

Keywords:

Imageregistration;

Phase;

FastFouriertransform;

Multimodal;

Keypoints;

Dynamicsub-clouds

ArticleOutline

1.Introduction

2.Multimodalregistrationproblem

3.Previouswork

4.Proposedregistrationalgorithm

4.1.Keypointdetectionandsub-cloudsizeestimation

4.2.Phasesub-cloudextraction

4.3.Simultaneoussub-cloudmatchingandfeaturespacetransformationestimation

4.4.Solvingthesimultaneousmatchingandfeaturespacetransformationestimationprobleminthefrequencydomain

4.5.Outlierpruningthroughresampling

4.6.Algorithmoutline

5.Computationalcomplexityanalysis

6.Experimentalresults

7.Conclusionsandfuturework

Acknowledgements

References

1.Introduction

Imageregistrationistheprocessofmatchingpointsinoneimagetotheircorrespondingpointsinanotherimage.Theproblemofimageregistrationplaysaveryimportantroleinmanyvisualandobjectrecognitionandmotionanalysisapplications.Someoftheseapplicationsincludevisualmotionestimation[1]and[2],vision-basedcontent-basedretrieval[3]and[4],imageregistration[5],[6],[7]and[9],andbiometricauthentication[10].Inthebestcasescenario,theimagesexistatthesamescale,inthesameorientation,aswellasrepresentedinthesamefeaturespace.However,thisisnotthecaseinmostreal-worldapplications.Therearemanysituationswheretheimagesexistindifferentfeaturespaces.Thisparticularproblemwillbereferredtoasthemultimodalregistrationproblemandisaparticularlydifficultproblemtosolve.Examplesofthisprobleminreal-worldsituationsincludemedicalimageregistrationandtrackingofMRI/CT/PETdata[11]andbuildingmodelingandvisualizationusingLIDARandopticaldata[12]and[13].

Thereareseveralimportantissuesthatmakemultimodalregistrationadifficultproblemtosolve.First,manyregistrationalgorithmsrequirethatequivalentkeypointsbeidentifiedwithineachimage.However,giventhedifferencesbetweenfeaturespacesinwhichtheimagesexist,itisoftenaverydifficulttask.Thesignificantdifferencesbetweenfeaturespacesalsomakeitimpracticaltoperformdirectintensitymatchingbetweenthetwoimages.Inrecentyears,aneffectiveapproachtomultimodalregistrationhasbeenproposedthatutilizeslocalphase[14]and[15].Thisstate-of-the-artapproachevaluatesthemutualinformationbetweenthelocalphaseoftwoimagestodeterminetheoptimalalignmentandhasbeenshowntobeveryeffectiveatmatchingmultimodalmedicalimagedata,outperformingexistingmultimodalregistrationmethods[14]and[15].However,thisapproachiscomputationallyexpensive（O（N6）forthemutualinformationevaluationprocess）.Assuch,aregistrationmethodthatisabletotakeadvantageoflocalphaseinformationtodeterminepointcorrespondencesbetweenimageswhilebeingcomputationallyefficientishighlydesiredforthepurposeofinitialcoarse-grainedregistration.

Themaincontributionofthispaperisfastphase-basedregistrationalgorithmforaligningmultimodalimages.Theproposedmethodisdesignedtoprovideafastalternativeto