一种基于多尺度时频分析的快速非局部均值InSAR相位滤波算法.docx

一种基于多尺度时频分析的快速非局部均值InSAR相位滤波算法
Title:AFastNon-localMeansInSARPhaseFilteringAlgorithmBasedonMultiscaleTime-FrequencyAnalysis
Abstract:
Inrecentyears,InterferometricSyntheticApertureRadar(InSAR)hasemergedasapowerfultechniqueformeasuringgrounddeformationswithhighprecision.However,theinterferometricphaseimagesobtainedfromInSARareoftencontaminatedbyvariousformsofnoiseanderrors.ToenhancethequalityoftheInSARphaseimages,phasefilteringisacriticalstepintheprocessingchain.Inthispaper,weproposeafastnon-localmeansInSARphasefilteringalgorithmbasedonmultiscaletime-frequencyanalysis.Thealgorithmaimstopreservetheunderlyingphasestructurewhileeffectivelyremovingnoiseanderrors.
1.Introduction
1.1Background
1.2Motivation
1.3Objectives
2.InSARPhaseFiltering
2.1PrinciplesofInSAR
2.2ChallengesinInSARPhaseFiltering
2.3Non-localMeans(NLM)Filtering
2.4MultiscaleTime-FrequencyAnalysis
3.ProposedAlgorithm
3.1OverviewoftheAlgorithm
3.2MultiscaleTime-FrequencyAnalysis
3.3Non-localMeansFilteringforPhaseCorrection
3.4FastImplementationStrategy
4.ExperimentalResults
4.1DataCollection
4.2EvaluationMetrics
4.3PerformanceComparisonwithExistingMethods
4.4AnalysisofExperimentalResults
5.Discussion
5.1AdvantagesandLimitationsoftheProposedAlgorithm
5.2PotentialApplications
5.3FutureWork
6.Conclusion
Inthispaper,weproposedafastnon-localmeansInSARphasefilteringalgorithmbasedonmultiscaletime-frequencyanalysis.ThealgorithmaimstoenhancethequalityofInSARphaseimagesbyeffectivelyremovingnoiseanderrorswhilepreservingtheunderlyingphasestructure.Theexperimentalresultsdemonstratethesuperiorperformanceoftheproposedalgorithmcomparedtoexistingmethods.Thealgorithmhasthepotentialforvariousapplications,suchasgrounddeformationmonitoringandnaturaldisasterassessment.Futureworkwillfocusonfurtherimprovingthealgorithm'sefficiencyandexploringitsapplicabilityinotherremotesensingdomains.
Keywords:InSAR,phasefiltering,non-localmeans,multiscaletime-frequencyanalysis,grounddeformationmonitoring
Introduction:
InterferometricSyntheticApe