图像处理中值滤波器中英文对照外文翻译文献

中英文资料对照外文翻译英文原文ANEWCONTENTBASEDMEDIANFILTERABSTRACTInthispaperthehardwareimplementationofacontentbasedmedianfiltersuitableforreal-timeimpulsenoisesuppressionispresented.Thefunctionoftheproposedcircuitryisadaptive;itdetectstheexistenceofimpulsenoiseinanimageneighborhoodandappliesthemedianfilteroperatoronlywhennecessary.Inthisway,theblurringoftheimageinprocessisavoidedandtheintegrityofedgeanddetailinformationispreserved.Theproposeddigitalhardwarestructureiscapableofprocessinggray-scaleimagesof8-bitresolutionandisfullypipelined,whereasparallelprocessingisusedtominimizecomputationaltime.ThearchitecturepresentedwasimplementedinFPGAanditcanbeusedinindustrialimagingapplications,wherefastprocessingisoftheutmostimportance.Thetypicalsystemclockfrequencyis55MHz.1.INTRODUCTIONTwoapplicationsofgreatimportanceintheareaofimageprocessingarenoisefilteringandimageenhancement[1].Thesetasksareanessentialpartofanyimageprocessor,whetherthefinalimageisutilizedforvisualinterpretationorforautomaticanalysis.Theaimofnoisefilteringistoeliminatenoiseanditseffectsontheoriginalimage,whilecorruptingtheimageaslittleaspossible.Tothisend,nonlineartechniques(likethemedianand,ingeneral,orderstatisticsfilters)havebeenfoundtoprovidemoresatisfactoryresultsincomparisontolinearmethods.Impulsenoiseexistsinmanypracticalapplicationsandcanbegeneratedbyvarioussources,includinganumberofmanmadephenomena,suchasunprotectedswitches,industrialmachinesandcarignitionsystems.Imagesareoftencorruptedbyimpulsenoiseduetoanoisysensororchanneltransmissionerrors.Themostcommonmethodusedforimpulsenoisesuppressionnforgray-scaleandcolorimagesisthemedianfilter(MF)[2].ThebasicdrawbackoftheapplicationoftheMFistheblurringoftheimageinprocess.Inthegeneralcase,thefilterisapplieduniformlyacrossanimage,modifyingpixelsthatarenotcontaminatedbynoise.Inthisway,theeffectiveeliminationofimpulsenoiseisoftenattheexpenseofanoveralldegradationoftheimageandblurredordistortedfeatures[3].Inthispaperanintelligenthardwarestructureofacontentbasedmedianfilter(CBMF)suitableforimpulsenoisesuppressionispresented.ThefunctionoftheproposedcircuitistodetecttheexistenceofnoiseintheimagewindowandapplythecorrespondingMFonlywhennecessary.Thenoisedetectionprocedureisbasedonthecontentoftheimageandcomputesthedifferencesbetweenthecentralpixelandthesurroundingpixelsofaneighborhood.Themainadvantageofthisadaptiveapproachisthatimageblurringisavoidedandtheintegrityofedgeanddetailinformationarepreserved[4,5].Theproposeddigitalhardwarestructureiscapableofprocessinggray-scaleimagesof8-bitresolutionandperformsbothpositiveandnegativeimpulsenoiseremoval.Thearchitectturechosenisbasedonasequenceoffourbasicfunctionalpipelinedstages,andparallelprocessingisusedwithineachstage.Amovingwindowofa3×3and5×5-pixelimageneighborhoodcanbeselected.However,thesystemcanbeeasilyexpandedtoaccommodatewindowsoflargersizes.Theproposedstructurewasimplementedusingfieldprogrammablegatearrays(FPGA).Thedigitalcircuitwasdesigned,compiledandsuccessfullysimulatedusingtheMAX+PLUSIIProgrammableLogicDevelopmentSystembyAlteraCorporation.TheEPF10K200SFC484-1FPGAdeviceoftheFLEX10KEdevicefamilywasutilizedfortherealizationofthesystem.Thetypicalclockfrequencyis55MHzandthesystemcanbeusedforreal-timeimagingapplicationswherefastprocessingisrequired[6].Asanexample,thetimerequiredtoperformfilteringofagray-scaleimageof260×244pixelsisapproximately10.6msec.2.ADAPTIVEFILTERINGPROCEDURETheoutputofamedianfilteratapointxofanimagefdependsonthevaluesoftheimagepointsintheneighborhoodofx.ThisneighborhoodisdeterminedbyawindowWthatislocatedatpointxoffincludingnpointsx1,x2,…,xnoff,withn=2k+1.Theproposedadaptivecontentbasedmedianfiltercanbeutilizedforimpulsenoisesuppressioningray-scaleimages.AblockdiagramoftheadaptivefilteringprocedureisdepictedinFig.1.Thenoisedetectionprocedureforbothpositiveandnegativenoiseisasfollows:(i)WeconsideraneighborhoodwindowWthatislocatedatpointxoftheimagef.Thedifferencesbetweenthecentralpixelatpointxandthepixelvaluesofthen-1surroundingpointsoftheneighborhood(excludingthevalueofthecentralpixel)arecomputed.(ii)Thesumoftheabsolutevaluesofthesedifferencesiscomputed,denotedasfabs(x).Thisvalueprovidesameasureofclosenessbetweenthecentralpixelanditssurroundingpixels.(iii)Thevaluefabs(x)iscomparedtofthreshold(x),whichisanappropriatelyselectedpositiveintegerthresholdvalueandcanbemodified.Thecentralpixelisconsideredtobenoisewhenthevaluefabs(x)isgreaterthanthethresholdvaluefthreshod(x).(iv)Whenthecentralpixelisconsideredtobenoiseitissubstitutedbythemedianvalueoftheimageneighborhood,denotedasfk+1,whichisthenormaloperationofthemedianfilter.Intheoppositecase,thevalueofthecentralpixelisnotalteredandtheprocedureisrepeatedforthenextneighborhoodwindow.Fromthenoisedetectionschemedescribed,itshouldbementionedthatthenoisedetectionlevelprocedurecanbecontrolledandarangeofpixelvalues(andnotonlythefixedvaluesof0and255,saltandpeppernoise)isconsideredasimpulsenoise.InFig.2theresultsoftheapplicationofthemedianfilterandtheCBMFinthegray-scaleimage“Peppers”aredepicted.Morespecifically,inFig.2(a)theoriginal,uncorruptedimage“Peppers”isdepicted.InFig.2(b)theoriginalimagedegradedby5%bothpositiveandnegativeimpulsenoiseisillustrated.InFigs2(c)and2(d)theresultantimagesoftheapplicationofmedianfilterandCBMFfora3×3-pixelwindowareshown,respectively.Finally,theresultantimagesoftheapplicationofmedianfilterandCBMFfora5×5-pixelwindowarepresentedinFigs2(e)and2(f).ItcanbenoticedthattheapplicationoftheCBMFpreservesmuchbetteredgesanddetailsoftheimages,incomparisontothemedianfilter.Anumberofdifferentobjectivemeasurescanbeutilizedfortheevaluationoftheseresults.ThemostwidelyusedmeasuresaretheMeanSquareError(MSE)andtheNormalizedMeanSquareError(NMSE)[1].TheresultsoftheestimationofthesemeasuresforthetwofiltersaredepictedinTableI.Fortheestimationofthesemeasures,theresultantimagesofthefiltersarecomparedtotheoriginal,uncorruptedimage.FromTableIitcanbenoticedthattheMSEandNMSEestimatedfortheapplicationoftheCBMFareconsiderablysmallerthanthoseestimatedforthemedianfilter,inallthecases.TableI.Similaritymeasures.FilterImpulsenoise5%mseNmse(×10-2)3×35×53×35×5MedianCBMF57.55435.287130.49684.7880.3170.1940.7180.4673.HARDWAREARCHITECTUREThestructureoftheadaptivefiltercomprisesfourbasicfunctionalunits,themovingwindowunit,themediancomputationunit,thearithmeticoperationsunit,andtheoutputselectionunit.Theinputdataofthesystemarethegray-scalevaluesofthepixelsoftheimageneighborhoodandthenoisethresholdvalue.Forthecomputationofthefilteroutputa3×3or5×5-pixelimageneighborhoodcanbeselected.Imageinputdataisseriallyimportedintothefirststage.Inthisway,thetotalnumberoftheinputpinsare24(21inputsfortheinputdataand3inputsfortheclockandthecontrolsignalsrequired).Theoutputdataofthesystemaretheresultantgray-scalevaluescomputedfortheoperationselected(8pins).Themovingwindowunitistheinternalmemoryofthesystem,usedforstoringtheinputvaluesofthepixelsandforrealizingthemovingwindowoperation.Thepixelvaluesoftheinputimage,denotedas“IMAGE_INPUT[7..0]”,areimportedintothisunitinserial.Fortherepresentationofthethresholdvalueusedforthedetectionofanoisepixel13bitsarerequired.Forthemovingwindowoperationa3×3(5×5)-pixelsepentinetypememoryisused,consistingof9(25)registers.Inthisway,whenthewindowismovedintothenextimageneighborhoodonly3or5pixelvaluesstoredinthememoryarealtered.The“en5×5”controlsignalisusedfortheselectionofthesizeoftheimagewindow,when“en5×5”isequalto“0”(“1”)a3×3(5×5)-pixelneighborhoodisselected.Itshouldbementionedthatthemodulesofthecircuitusedforthe3×3-pixelwindowareutilizedforthe5×5-pixelwindowaswell.Forthesemodules,2-to-1multiplexersareutilizedtoselecttheappropriatepixelvalues,wherenecessary.Themodulesthatareutilizedonlyinthecaseofthe5×5-pixelneighborhoodareenabledbythe“en5×5”controlsignal.Theoutputsofthisunitarerowsofpixelvalues(3or5,respectively),whicharetheinputstothemediancomputationunit.Thetaskofthemediancomputationunitistocomputethemedianvalueoftheimageneighborhoodinordertosubstitutethecentralpixelvalue,ifnecessary.Forthispurposea25-inputsorterisutilizeed.ThestructureofthesorterhasbeenproposedbyBatcherandisbasedontheuseofCSblocks.ACSblockisamax/minmodule;itsfirstoutputisthemaximumoftheinputsanditssecondoutputtheminimum.TheimplementationofaCSblockincludesacomparatorandtwo2-to-1multiplexers.Theoutputsvaluesofthesorter,denotedas“OUT_0[7..0]”….“OUT_24[7..0]”,producea“sortedlist”ofthe25initialpixelvalues.A2-to-1multiplexerisusedfortheselectionofthemedianvaluefora3×3or5×5-pixelneighborhood.Thefunctionofthearithmeticoperationsunitistocomputethevaluefabs(x),whichiscomparedtothenoisethresholdvalueinthefinalstageoftheadaptivefilter.Theinputsofthisunitarethesurroundingpixelvaluesandthecentralpixeloftheneighborhood.Fortheimplementationofthemathematicalexpressionoffabs(x),thecircuitofthisunitcontainsanumberofaddermodules.Notethatregistershavebeenusedtoachieveapipelinedoperation.Anadditional2-to-1multiplexerisutilizedfortheselectionoftheappropriateoutputvalue,dependingonthe“en5×5”controlsignal.Fromtheimplementationpointofview,theuseofarithmeticblocksmakesthisstagehardwaredemanding.Theoutputselectionunitisusedfortheselectionoftheappropriateoutputvalueoftheperformednoisesuppressionoperation.Forthisselection,thecorrespondingnoisethresholdvaluecalculatedfortheimageneighborhood,“NOISE_THRESHOLD[12..0]”,isemployed.Thisvalueiscomparedtofabs(x)andtheresultofthecomparisonClassifiesthecentralpixeleitherasimpulsenoiseornot.Ifthevaluefabs(x)isgreaterthanthethresholdvaluefthreshold(x)thecentralpixelispositiveornegativeimpulsenoiseandhastobeeliminated.Forthisreason,theoutputofthecomparisonisusedastheselectionsignalofa2-to-1multiplexerwhoseinputsarethecentralpixelandthecorrespondingmedianvaluefortheimageneighborhood.Theoutputofthemultiplexeristheoutputofthisstageandthefinaloutputofthecircuitoftheadaptivefilter.ThestructureoftheCBMF,thecomputationprocedureandthedesignofthefouraforementionedunitsareillustratedinFig.3.P1P2P3P4P5P6P7P8P9MedianfilterMedianfiltermuitiplexerSmuitiplexerSubtractorarrycomparatoraddercomparatoradderfabcfabc(x)valuewindoeFigure1:BlockdiagramofthefilteringmethodFigure2:ResultsoftheapplicationoftheCBMF:(a)Originalimage,(b)noisecorruptedimage(c)Restoredimagebya3x3MF,(d)Restoredimagebya3x3CBMF,(e)Restoredimagebya5x5MFand(f)Restoredimagebya5x5CBMF.4.IMPLEMENTATIONISSUESTheproposedstructurewasimplementedinFPGA,whichofferanattractivecombinationoflowcost,highperformanceandapparentflexibility,usingthesoftwarepackage+PLUSIIofAlteraCorporation.TheFPGAusedistheEPF10K200SFC484-1deviceoftheFLEX10KEdevicefamily,adevicefamilysuitablefordesignsthatrequirehighdensitiesandhighI/Ocount.The99%ofthelogiccells(9965/9984logiccells)ofthedevicewasutilizedtoimplementthecircuit.Thetypicaloperatingclockfrequencyofthesystemis55MHz.Asacomparison,thetimerequiredtoperformfilteringofagray-scaleimageof260×244pixelsusingMatlab®softwareonaPentium4/2.4GHzcomputersystemisapproximately7.2sec,whereasthecorrespondingtimeusinghardwareisapproximately10.6msec.Themodificationofthesystemtoaccommodatewindowsoflargersizescanbedoneinastraightforwardway,requiringonlyasmallnumberofchanges.Morespecifically,inthefirstunitthesizeoftheserpentinememoryandthecorrespondingnumberofmultiplexersincreasefollowingasquarelaw.Inthesecondunit,thesortermoduleshouldbemodified,andinthethirdunitthenumberoftheadderdevicesincreasesfollowingasquarelaw.Inthelastunitnochangesarerequired.5.CONCLUSIONSThispaperpresentsanewhardwarestructureofacontentbasedmedianfilter,capableofperformingadaptiveimpulsenoiseremovalforgray-scaleimages.Thenoisedetectionproceduretakesintoaccountthedifferencesbetweenthecentralpixelandthesurroundingpixelsofaneighborhood.Theproposeddigitalcircuitiscapableofprocessinggrayscaleimagesof8-bitresolution,with3×3or5×5-pixelneighborhoodsasoptionsforthecomputationofthefilteroutput.However,thedesignofthecircuitisdirectlyexpandabletoaccommodatelargersizeimagewindows.TheadaptivefilterwasdeignedandimplementedinFPGA.Thetypicalclockfrequencyis55MHzandthesystemissuitableforreal-timeimagingapplications.REFERENCES[1]W.K.Pratt,DigitalImageProcessing.NewYork:Wiley,1991.[2]G.R.Arce,N.C.GallagherandT.Nodes,“Medianfilters:Theoryandapplications,”inAdvancesinComputerVisionandImageProcessing,Greenwich,CT:JAI,1986.[3]T.A.NodesandN.C.Gallagher,Jr.,“Theoutputdistributionofmediantypefilters,”IEEETransactionsonCommunications,vol.COM-32,pp.532-541,May1984.[4]T.SunandY.Neuvo,“Detail-preservingmedianbasedfiltersinimageprocessing,”PatternRecognitionLetters,vol.15,pp.341-347,Apr.1994.[5]E.Abreau,M.Lightstone,S.K.Mitra,andK.Arakawa,“Anewefficientapproachfortheremovalofimpulsenoisefromhighlycorruptedimages,”IEEETransactionsonImageProcessing,vol.5,pp.1012-1025,June1996.[6]E.R.DoughertyandP.Laplante,IntroductiontoReal-TimeImaging,Bellingham:SPIE/IEEEPress,1995.英文翻译基于中值滤波的新的内容摘要在本设计中的提出了基于中值滤波的硬件实现用来抑制脉冲噪声的干扰。拟议的电路功能是自适应；只有在必要时它才检测到存在邻域图像中的脉冲噪声中并应用中值滤波运算符。用这种方式，可以避免使图像在处理过程中变模糊并且完整的保留了图像边缘和细节的重要信息。拟议的数字硬件结构是能够处理的8位灰度图像决议和完全流水线，而将用来并行处理计的算时间降至最低，FPGA的现场可编程结构和其在图像处理领域的应用，在这些领域内快速的运算是极为重要的。典型的系统时钟频率为55Mhz.介绍在图像处理过程中有非常重要的应用程序分别是噪声过滤和图像增强。在图像处理过程中这些都是很必要的，不管最终图像是否用于视觉解释或自动分析。噪声滤波的目的是消除噪声及对原始图像影响，同尽可能少的时损坏原来的图像。因此非线性（例如中值滤波哦，一般情况下的顺序统计滤波器）与线性的滤波器先比，提供了更令人满意结果。脉冲噪声存在许多实际的应用程序中，并且来源广泛，包括一些人类的行为，例如作为保护的开关、工业机械、和汽车点火系统。由于嘈杂的传感器或通道传输错误的脉冲噪声早造成工图像的损坏。最常见用于灰度和彩色图像脉冲噪声抑制的方法是中值滤波。中值滤波的缺点是在应在模糊图像的滤波过程中。在一般情况下，筛选器是将应用于整个图像，修改的像素的均匀从而不受噪音污染。这种方式，有效的消除脉冲噪声往往是以整体图像的模糊或扭曲功能的退化为代价的。在本设计中提出的一种基于有效率才不脉冲噪声的中值滤波器上提出的。提出的电路电路具有只有当检测到当前图像中存在噪声时才启动相应的中值滤波程序。噪音检测过程基于图像的内容和计算中央像素和周围的邻居的像素之间的差异。这种自适应的方法主要优势是避免图像的模糊和保留边缘详细信息的完整性。这种数字硬件结构是有能够进行8位分辨率的灰度图象处理和执行这两个正面和负面的脉冲噪声去除。选择这种电路结构是基于四种基本的系列功能和在每一个阶段并行执行的流水线功能。但是，系统可以轻松地扩展以容纳更大的窗口大小。这个结构将使用可编程门阵列。数字电路的设计在由Altera公司提供的的可编程逻辑发展系统MAX+plusii下成功编译和仿真。本系统将使用EPF10K200SFC484-1FPGAFLEX10KE系列的芯片。其时钟频率是55MHZ并且此系统能被用于实时成像应用程序，在此系统中快熟处理是很必要的。例如对一张像素为260×244灰度图像所需要的时间为10.6毫秒。2.自适应的筛选过程图像f点的中值输出取决于图像附近x点的值。这个小区由w的窗口，位于点f附近有n个x1，x2与n=2k+1个。自适应内容基于中值滤波器器可用于脉冲抑制灰度图像的噪声。自适应滤波的块状图过程如图1所示。噪声检测过程正面和负面的噪音如下所示：（一）我们认为附近窗口w位于图像f的x点处，同x点的差异并计算其附近的n-1个像素值，包括中间值。(二)这些差异的总和是绝对值的计算，用fab（x）表示。这个值提供了中间点和周围点之间最密切的关系。（三）将值fabs(x)与fthreshold(x)进行对比，看哪一个更适合作为正确的正整数阈值并可以进行修改。当fans（x）大于阈值值fthreshold(x)时中央像素就会被认为是噪声。（四)中央像素被认为是噪音时，将被附近的中值所取代，及fk+1是中值滤波器的正常输出值。在相反的情况下，中间像素值不会改变，并重复该过程下一步的邻域窗口。从所述的噪声检测方案中，应该提到噪声检测水平过程是可以控制，并且像素值的范围（和不只固定值0和255，盐和胡椒粉噪音）被认为是脉冲噪声。在图2中位数的应用程序的结果进行筛选和描述"椒盐"的灰度图像中的CBMF。更具体地说，在图2(a)的原始的、未损坏的图像描述"椒盐"。在图2(b)原始图像5%，这两个正面和负面的脉冲噪声被降级说明了。无花果2(c)和2(d)的结果图像3×3像素窗口中值滤波和CBMF中的应用显示，分别。最后，结果的图像5×5像素的中值滤波和CBMF的应用窗口载列于无花果2(e)和2(f)。相比中值滤波器可以看到CBMF的应用可以保留好得多边缘和细节的图像。可以利用一些不同的客观措施来评价这些结果。使用最广泛的方法是均方错误(MSE)和规范化均方误差（NMSE）。对这些措施的结果的评估对比如表一。对于这些措施的评估输出的图像将与原始的、为受损的图像进行比较。从表可以看出对于CBMF的MSE和NMSE评估在任何情况下比所有的中值滤波器都要小。3硬件结构体系自适应滤波器的结构包括四个基