matlab大学外文资料翻译 学位论文.docx

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matlab大学外文资料翻译学位论文

ComplexRidgeletsforImageDenoising

1Introduction

Wavelettransformshavebeensuccessfullyusedinmanyscientificfieldssuchasimagecompression,imagedenoising,signalprocessing,computergraphics,andpatternrecognition,tonameonlyafew.Donohoandhiscoworkerspioneeredawaveletdenoisingschemebyusingsoftthresholdingandhardthresholding.Thisapproachappearstobeagoodchoiceforanumberofapplications.Thisisbecauseawavelettransformcancompacttheenergyoftheimagetoonlyasmallnumberoflargecoefficientsandthemajorityofthewaveletcoeficientsareverysmallsothattheycanbesettozero.Thethresholdingofthewaveletcoeficientscanbedoneatonlythedetailwaveletdecompositionsubbands.Wekeepafewlowfrequencywaveletsubbandsuntouchedsothattheyarenotthresholded.ItiswellknownthatDonoho'smethodofferstheadvantagesofsmoothnessandadaptation.However,asCoifman

andDonohopointedout,thisalgorithmexhibitsvisualartifacts:

Gibbsphenomenaintheneighbourhoodofdiscontinuities.Therefore,theyproposeinatranslationinvariant(TI)denoisingschemetosuppresssuchartifactsbyaveragingoverthedenoisedsignalsofallcircularshifts.TheexperimentalresultsinconfirmthatsingleTIwaveletdenoisingperformsbetterthanthenon-TIcase.BuiandChenextendedthisTIschemetothemultiwaveletcaseandtheyfoundthatTImultiwaveletdenoisinggavebetterresultsthanTIsinglewaveletdenoising.CaiandSilvermanproposedathresholdingschemebytakingtheneighbourcoeficientsintoaccountTheirexperimentalresultsshowedapparentadvantagesoverthetraditionalterm-by-termwaveletdenoising.ChenandBuiextendedthisneighbouringwaveletthresholdingideatothemultiwaveletcase.Theyclaimedthatneighbourmultiwaveletdenoisingoutperformsneighboursinglewaveletdenoisingforsomestandardtestsignalsandreal-lifeimages.Chenetal.proposedanimagedenoisingschemebyconsideringasquareneighbourhoodinthewaveletdomain.Chenetal.alsotriedtocustomizethewavelet_lterandthethresholdforimagedenoising.Experimentalresultsshowthatthesetwomethodsproducebetterdenoisingresults.Theridgelettransformwasdevelopedoverseveralyearstobreakthelimitationsofthewavelettransform.The2Dwavelettransformofimagesproduceslargewaveletcoeficientsateveryscaleofthedecomposition.Withsomanylargecoe_cients,thedenoisingofnoisyimagesfacesalotofdiffculties.Weknowthattheridgelettransformhasbeensuccessfullyusedtoanalyzedigitalimages.Unlikewavelettransforms,theridgelettransformprocessesdatabyfirstcomputingintegralsoverdifferentorientationsandlocations.Aridgeletisconstant

alongthelinesx1cos_+x2sin_=constant.Inthedirectionorthogonaltotheseridgesitisawavelet.Ridgeletshavebeensuccessfullyappliedinimagedenoisingrecently.Inthispaper,wecombinethedual-treecomplexwaveletintheridgelettransformandapplyittoimagedenoising.Theapproximateshiftinvariancepropertyofthedual-treecomplexwaveletandthegoodpropertyoftheridgeletmakeourmethodaverygoodmethodforimagedenoising.Experimentalresultsshowthatbyusingdual-treecomplexridgelets,ouralgorithmsobtainhigherPeakSignaltoNoiseRatio(PSNR)forallthedenoisedimageswithdi_erentnoiselevels.Theorganizationofthispaperisasfollows.InSection2,weexplainhowtoincorporatethedual-tree

complexwaveletsintotheridgelettransformforimagedenoising.ExperimentalresultsareconductedinSection3.Finallywegivetheconclusionandfutureworktobedoneinsection4.

2ImageDenoisingbyusingComplex

RidgeletsDiscreteridgelettransformprovidesnear-idealsparsityofrepresentationofbothsmoothobjectsandofobjectswithedges.Itisanear-optimalmethodofdenoisingforGaussiannoise.Theridgelettransformcancompresstheenergyoftheimageintoasmallernumberofridgeletcoe_cients.Ontheotherhand,thewavelettransformproducesmanylargewaveletcoe_cientsontheedgesoneveryscaleofthe2Dwaveletdecomposition.Thismeansthatmanywaveletcoe_cientsareneededinordertoreconstructtheedgesintheimage.WeknowthatapproximateRadontransformsfordigitaldatacanbebasedondiscretefastFouriertransform.Theordinaryridgelettransformcanbeachievedasfollows:

1.Computethe2DFFToftheimage.

2.SubstitutethesampledvaluesoftheFouriertransformobtainedonthesquarelatticewithsampledvaluesonapolarlattice.

3.Computethe1DinverseFFToneachangularline.

4.Performthe1Dscalarwavelettransformontheresultingangularlinesinordertoobtaintheridgeletcoe_cients.

Itiswellknownthattheordinarydiscretewavelettransformisnotshiftinvariantbecauseofthedecimationoperationduringthetransform.Asmallshiftinthein

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