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一种无参考运动模糊图像的模糊度估计方法.docx

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一种无参考运动模糊图像的模糊度估计方法 Title:AnUnreferencedMotionBlurImageBlurEstimationMethod Abstract: Motionblurisacommondegradationinimagescapturedwithmovingcamerasormovingscenes.Estimatingtheblurlevelinsuchimagesisessentialforvariousapplications,includingimagerestorationandunderstandingthesourceofblurring.Inthispaper,weproposeanunreferencedmotionblurimageblurestimationmethodthatdoesnotrequireanyreferenceimageorpriorknowledge.Themethodutilizesvariousimagefeaturestoestimatetheblurlevelaccurately.Experimentalresultsdemonstratetheeffectivenessofourproposedmethodcomparedtoexistingunreferencedblurestimationalgorithms. 1.Introduction Motionbluroccurswhenthecameraorthesceneisinmotionduringtheexposuretime,causingsmearingorstreakingofobjectsintheimage.Estimatingmotionblurinanimageischallengingsincethereferenceimageisusuallyunavailable.Existingmethodsformotionblurestimationmostlyrelyonareferenceimageorrequirepriorknowledgeabouttheblurprocess,whichlimitstheirapplicability.Inthispaper,weproposeanunreferencedmotionblurimageblurestimationmethodthatovercomestheselimitations. 2.ProposedMethod Ourproposedmethodconsistsofthefollowingsteps: 2.1.FeatureExtraction Weextractvariousimagefeaturesthataresensitivetoblur.Thesefeaturesincludegradienthistograms,edgewidthdistribution,edgeenergy,andFourierspectrumanalysis.Thesefeaturescapturethechangesinimagecharacteristicscausedbymotionblur. 2.2.FeatureAnalysis Weanalyzetheextractedfeaturestodeterminetheircorrelationswithblurlevel.Basedontheanalysis,weselectthemostrelevantfeaturesandestablishamathematicalmodelforblurestimation.Themodelconsiderstherelationshipsbetweenthefeaturesandblurlevel. 2.3.BlurLevelEstimation Usingtheestablishedmathematicalmodel,weestimatetheblurleveloftheinputimage.Thisestimationisdonewithoutrequiringanyreferenceimageorpriorknowledgeoftheblurprocess.Theproposedmethodprovidesaccurateblurlevelestimation,evenintheabsenceofareferenceimage. 3.ExperimentalResults Weconductextensiveexperimentstoevaluatetheperformanceofourproposedmethod.Wecompar