yang and parvin high-resolution reconstruction of sparse data from dense low-resolution spa

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1、YANGANDPARVIN:HIGH-RESOLUTIONRECONSTRUCTIONOFSPARSEDATAFROMDENSELOW-RESOLUTIONSPATIO-TEMPORALDATA1High-ResolutionReconstructionofSparseDatafromDenseLow-ResolutionSpatio-TemporalDataQingYangandBahramParvin,SeniorMember,IEEEAbstract—Anovelapproachforreconstructionofsparsehigh-2)Compu

2、tingfeaturevelocitiesofdensespatio-temporalresolutiondatafromlower-resolutiondensespatio-temporaldataimagesfromlow-resolution18kmdata.isintroduced.Thebasicideaistocomputethedensefeature3)Projectingcomputedfeaturevelocitiesonto4kmdatavelocitiesfromlower-resolutiondataandprojectthemt

3、otheandsolvingtheflowequationforintensityasopposedcorrespondinghigh-resolutiondataforcomputingthemissingdata.Inthiscontext,thebasicflowequationissolvedforintensity,tovelocities.asopposedtofeaturevelocitiesathighresolution.AlthoughtheCurrentmethodsforinterpolatingSSTdataarebasedonprop

4、osedtechniqueisgeneric,wehaveappliedourapproachobjectiveanalysis(OA)[1]andoptimalinterpolation(OI)toseasurfacetemperature(SST)dataat18km(low-resolutiondensedata)forcomputingthefeaturevelocitiesandat4km[2]asaspecialcase.Thesetechniquesoperateonrandomly(high-resolutionsparsedata)fori

5、nterpolatingthemissingdata.distributedspatio-temporaldata,andtheyhavebeenshownAtlowresolution,computationoftheflowfieldisregularizedandtobereliableupto18kmresolution,e.g.,agridsizeofusestheincompressibilityconstraintsfortrackingfluidmotion.ÆAthighresolution,computationoftheintensityis

6、regularized0:25withanimagesizeof7201440.However,duetotheextremelyhighcomputationalcomplexityofthesemethods,forcontinuityacrossmultipleframes.interpolatingSSTdataathighresolution,e.g.,agridsizeofIndexTerms—Highresolution,interpolation,motion,duality,Æmultigridmethods(0:04395withani

7、magesizeof40968192,remainsanopenproblem.Weproposetosolvethisproblembyintegratingtwodifferentsourcesofinformation:motionandtemperature.InI.INTRODUCTIONtheproposedmodel,wecanincorporateflow,temperature,Thispaperpresentsanovelapproachforreconstructionincompressibilityandsmoothnesstoge

8、ther.Asweshallsee,ofhigh-r