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基于自适应滤波的快速广义模糊C均值聚类图像分割 Title:FastGeneralizedFuzzyC-meansImageSegmentationbasedonAdaptiveFiltering Abstract: Imagesegmentationplaysacrucialroleincomputervisionandimageprocessing.Itaimstopartitionanimageintodistinctregionsbasedonsimilaritiesintheirvisualattributes.GeneralizedFuzzyC-means(GFCM)isaneffectiveclusteringalgorithmwidelyusedforimagesegmentation.However,theconventionalGFCMsuffersfromhighcomputationalcomplexityandtheinabilitytohandlenoisyimages.Inthispaper,weproposeafastGFCMimagesegmentationapproachbasedonadaptivefiltering,whichaddressestheseissues. 1.Introduction Imagesegmentationisessentialforawiderangeofapplications,includingobjectrecognition,tracking,andsceneunderstanding.Amongvarioussegmentationtechniques,theGFCMalgorithmhasshownpromisingresultsinhandlingcomplexsegmentationtasks.However,itstillfaceschallengesintermsofcomputationtimeandnoiserobustness.ThispaperaimstoovercometheselimitationsbyintegratingadaptivefilteringintotheGFCMalgorithm. 2.RelatedWork PriorresearchhasexploreddifferentapproachestoimprovetheperformanceofGFCMimagesegmentation.Manystudiesfocusonreducingthecomputationalcomplexityandenhancingnoiserobustness.Techniquessuchasgraph-basedalgorithms,advancedclusteringtechniques,andfeatureextractionmethodshavebeenproposed.However,noneofthesemethodsofferacomprehensivesolution. 3.Methodology 3.1GFCMAlgorithmOverview TheGFCMalgorithmisbasedontheFuzzyC-means(FCM)clusteringalgorithm.Thegoalistominimizeanobjectivefunctionthatcombinesfuzzymembershipvaluesandspatialhomogeneityconstraints.However,theoriginalGFCMalgorithmsuffersfromhighcomputationalcomplexityduetothelargenumberofclustersandrequirediterations. 3.2AdaptiveFiltering Toaddressthenoiserobustnessissue,weintroduceanadaptivefilteringtechnique.Theadaptivefilterenhancestheimagebysuppressingnoisypixelswhilepreservingimportantdetails.Weemployanon-linearfilterbasedonthebilateralfilter,whichconsidersbothspatialandintensityinformation. 3.3FastGFCMwithAdaptiveFiltering WeproposeamodifiedGFCMalgorithmthatin