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1、NewMethodforImageDenoisingwhileKeepingEdgeInformationEdgeinformationisthemostimportanthigh-frequencyinformationofanimage,soweshouldtrytomaintainmoreedgeinformationwhiledenoising.Inordertopreserveimagedetailsaswellascancelingimagenoise,wepresentanewimagedenoisin
2、gmethod:imagedenoisingbasedonedgedetection.Beforedenoising,image'sedgesarefirstdetected,andthenthenoisedimageisdividedintotwoparts:edgepartandsmoothpart.Wecanthereforesethighdenoisingthresholdtosmoothpartoftheimageandlowdenoisingthresholdtoedgepart.Thetheoretic
3、alanalysesandexperimentalresultspresentedinthispapershowthat,comparedtocommonly-usedwaveletthresholddenoisingmethods,theproposedalgorithmcouldnotonlykeepedgeinformationofanimage,butalsocouldimprovesignal-to-noiseratioofthedenoisedimage.Inthewaveletdomain,theden
4、oisingalgorithmbasedonthethresholdfilteriswidelyused,becauseit’scomparativelyefficientandeasytorealize.Wecanselectathresholdaccordingtothecharacteristicoftheimage,modifyingallofthediscretedetailcoefficientssoastoreducethenoise.However,weareinthedilemmaofdetermi
5、ningthelevelofthethreshold.Thehigherthethresholdis,thebettereffectofdenoisingwillbe,and,atthesametime,theblurriertheedgewillbe.Theedgesofanimagemostlyreflecttheinformationoftheimage,andcontainitsbasiccharacter.Accordingtoresearchonhumaneyes,thecharacteristicoft
6、heedgesisoneofseveralcharacteristicsthatcanstronglyimpressthevisualsystem.Thus,whenweprocessdenoising,thefirstthingthatweshouldcareaboutistryingtoretainedgeinformation.Thispaperpresentsanewmethodforimagedenoisingwhilekeepingedgeinformation.Wefirstapplywavelettr
7、ansformtoanoisedimage,andthenprocessedgedetection.Thewaveletcoefficientsaredividedintotwoparts:edgepartandsmoothpart.Wecanthereforesethighdenoisingthresholdtothesmoothpartandlowdenoisingthresholdtoedgepartinordertoretainmoreedgeinformation.Thetheoreticanalysisa
8、ndexperimentalresultspresentedinthispapershowsthat,comparedwithcommonly-usedwaveletthresholddenoisingmethods,theproposeddenoisingmethodismoreeffective.Theideaofcombiningedge
