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1、外文文献NewmethodforimagedenoisingwhilekeepingedgeinformationEdgeinformationisthemostimportanthigh-frequencyinformationofanimage,soweshouldtrytomaintainmoreedgeinformationwhiledenoising.Inordertopreserveimagedetailsaswellascancelingimagenoise,wepresentanewimagedenoisingmethod:imagedenoisingbasedon
2、edgedetection.Beforedenoising,image'sedgesarefirstdetected,andthenthenoisedimageisdividedintotwoparts:edgepartandsmoothpart.Wecanthereforesethighdenoisingthresholdtosmoothpartoftheimageandlowdenoisingthresholdtoedgepart.Thetheoreticalanalysesandexperimentalresultspresentedinthispapershowthat,c
3、omparedtocommonly-usedwaveletthresholddenoisingmethods,theproposedalgorithmcouldnotonlykeepedgeinformationofanimage,butalsocouldimprovesignal-to-noiseratioofthedenoisedimage.Inthewaveletdomain,thedenoisingalgorithmbasedonthethresholdfilteriswidelyused,becauseit’scomparativelyefficientandeasyto
4、realize.Wecanselectathresholdaccordingtothecharacteristicoftheimage,modifyingallofthediscretedetailcoefficientssoastoreducethenoise.However,weareinthedilemmaofdeterminingthelevelofthethreshold.Thehigherthethresholdis,thebettereffectofdenoisingwillbe,and,atthesametime,theblurriertheedgewillbe.T
5、heedgesofanimagemostlyreflecttheinformationoftheimage,andcontainitsbasiccharacter.Accordingtoresearchonhumaneyes,thecharacteristicoftheedgesisoneofseveralcharacteristicsthatcanstronglyimpressthevisualsystem.Thus,whenweprocessdenoising,thefirstthingthatweshouldcareaboutistryingtoretainedgeinfor
6、mation.Thispaperpresentsanewmethodforimagedenoisingwhilekeepingedgeinformation.Wefirstapplywavelettransformtoanoisedimage,andthenprocessedgedetection.Thewaveletcoefficientsaredividedintotwoparts:edgepartandsmoothpart.Wecanthereforesethighdenoisingthresholdtothesmoothpartandlowdenoisinghreshold
7、toedgepartinordertoretainmoreedgeinformation.Thetheoreticanalysisandexperimentalresultspresentedinthispapershowsthat,comparedwithcommonly-usedwaveletthresholddenoisingmethods,theproposeddenoisingmethodismoreeffective.Theideaofcombininge