數(shù)字圖像處理知識(shí)點(diǎn)總結(jié)

1、基礎(chǔ)1.什么是數(shù)字圖像一副圖像可定義為一個(gè)二維函數(shù)f(X、y),其中x和y是空間(平面)坐標(biāo)，而在任何一對(duì)空間坐標(biāo)(x、y)處的幅值f稱為圖像在該點(diǎn)處的強(qiáng)度或灰度。當(dāng)x、y和灰度值f是有限的離散數(shù)值時(shí)，我們稱該圖像為數(shù)字圖像。Thefunctionfmayrepresentintensity(formonochiomeimages)orcolor(forcolorimages)orotlierassociatedvalues.Digitalimage:animagetliathasbeendigitizedbotliinspatialcoordinatesandassociatedvalueC

2、onsistof2sets:(1)apointsetand(2)avaluesetCanberepresentedintlieformI=(x,a(x):x屬于X,a(x)屬于FWliydoweneedimagecompression?-Exampledigitalcamera(4Mpixel)Rawdata一24bits,4Mpixels一12Mbytes192Mmemoiycard_16pictures2-圖像坐標(biāo)系笛卡爾坐標(biāo)不能作為像素坐標(biāo)最小單位空間分辨率是圖像中可辨別的最小細(xì)節(jié)的度量?；叶确直媛适侵冈诨叶燃?jí)中可分辨的最小變化。數(shù)字圖像處理的概念、研究?jī)?nèi)容數(shù)字圖像處理是指借助于數(shù)字計(jì)算

3、機(jī)來處理數(shù)字圖像。數(shù)字圖像是由有限數(shù)量的元素組成的,每個(gè)元素都有一個(gè)特定的位置和幅值。這些元素成為圖畫元素、圖像元素或像素。Functions:1.Acquisition2.Storage3Processing4Communication5.DisplayimageSamplingandQuantization采樣和量化Imagesampling:digitizeanimageinthespatialdomainSpatial/imageresolution分辨率pixelsizeornumberofpixels圖像的領(lǐng)域(4,&對(duì)角)及連通的概念Neighborhoodrelationisu

4、sedtotelladjacent(鄰近，冊(cè)匕連)pixelsItisusedinestablishingboundariesofobjectsandcomponentsofregionsinanimageforanalyzingregions.位于坐標(biāo)(X、y)處的像素p有4個(gè)水平和垂直的相鄰像素，其坐標(biāo)由下式給出：(x+1,y),(x-Ey)t(x,y+1),(x,y+1)這組像素成為p的4鄰域，用M(P)表示。每個(gè)像素距(x,y)一個(gè)單位距離。Note:qWN4(p)impliespEN4(q)4-neighborhoodrelationconsidersonlyveitical(垂直)

5、andhorizontal(水平)neighbors.P的4個(gè)對(duì)角相鄰像素的坐標(biāo)如下：(x-l,y-l),(x,y-1),(x-l,y),(x+ly),(x,y+1),(x+1,y+1),(x+1,y-1),(x-by+1),(x-1,y-1)并用比(p)表示。這些點(diǎn)與4個(gè)鄰點(diǎn)一起稱為p的8鄰域，用(P)表示neighborhoodrelationconsidersallneighborpixels.Diagonal-neighborhoodrelationconsidersonlydiagonal(斜的)neighborpixels.(x-1,y-1),(x+1,y-1),(x-1,y+1)

6、,(x+1,y+1)6各不同電磁波譜的圖像成像技術(shù)，波段劃分？7圖像數(shù)字化過程(打描、采樣、量化)及各自含義？圖像分辨率(空間、灰度)與質(zhì)量的關(guān)系？（采樣間距與數(shù)據(jù)量的關(guān)系、采樣間距與質(zhì)量的關(guān)系、量化與數(shù)據(jù)量的關(guān)系、量化與質(zhì)量的關(guān)系）Imagequantization（數(shù)字It）digitizecontinuouspixelvaluesintodiscietenumbers空域增強(qiáng)8圖像增強(qiáng)的目的（不清晰的圖像變得清晰或強(qiáng)調(diào)某些感興趣的特征，改善圖像質(zhì)量，豐富信息量，加強(qiáng)圖像判讀和識(shí)別效果），分類及特點(diǎn)Objective:toprocessannnagesothattheresultismor

7、esuitableforaspecificapplication.PioblemonentedThebestmetliodforenliancingX-rayimagesmaybenotthebestmetliod,evennotsuitableforenliancingpicturesofMars（火星）transmittedbyaspaceprobe（探測(cè)器）Theiearetwomaincategoriesoftechniquesforimageenliancement:Spatial（空間的）DomainMetliods-whichoperatedirectlyonpixels.Fre

8、quencyDomainMethods-v/hichoperateontlieFourierTransfoimoftheimage.Combinationalapproacheswithtliesetwocategoriesarenotunusual.9圖像增強(qiáng)點(diǎn)到點(diǎn)運(yùn)算有哪些？特點(diǎn)？?jī)?yōu)缺點(diǎn)？（對(duì)數(shù)、乘方率、分段線性、二值化、加法噪聲、減法變化）Enhancementatanypointinanimagedependsonlyontliegraylevelatthatpoint.Contraststretching乂寸比度擴(kuò)展:darkeningthegraylevelsbelownmithe

9、originalimage,bnghtenuigthegraylevelsabovemintlieonginalimageThresholdingI測(cè)值ft：thelimitnigcaseistogenerateabinaryimageSomeBasicGrayLevelTransfonnationsNegative（linear）Log（logandinveise-logtiansfbnnations）Powerlaw乘方律（nthpowerandn-tliioottiansfonnations.Theidentitytiansfonnationisatiivial（微不足道的）case:o

10、utput=input,onlyforcompleteness完備性）Piecewise-lineartiansfonnationfunctions（分段線性函數(shù)）Bitslicing位切片DefnntionThenegativeofanimagewithgraylevelsintlierange0,L-lcanbedefinedas:s=L-l-ri-L-1,s=0:Wlnte-Black1-0,s=L-l:Black-WhiteFunction:Reversingtheintensitylevelsofanimageintinsmannerproducestlieequivalent（等彳

11、介物）ofaphotogiaphicnegative（照相底片）Applications:Enliancingwhiteorgraydetailsembeddedindarkregions,especiallywhentheblackareasaredominantinsize“Log”Definition:Thegeneralfonnoftlielogtransformationisdefinedass=clog（l+r）L-l=clog（l+L-l）c=L1logLWlierecisaconstant,assumetliatr0uLognFunction:Tomapanairowrange

12、oflowgray-levelvaluesintlieinputimageintoavzideirangeofoutputlevels.Tomapavziderangeofhighgray-levelvaluesintheinputimageintoanairowerrangeofoutputlevels.uLognApplications:Toexpandtlievaluesofdarkpixelsinannnagevzhilecompressingthehigher-levelvaluesTocompressdynamicrangeIngeneral,loga門thmicmappingis

13、usefulifwewishtoenhancedetailinthedarkerregionsoftheimage,attheexpenseofdetailintlieblighterregionsuInverseLognDefinition:Thegeneralformoftlieinverselogtiansfonnationisdefinedass=101L1=gc（L-i）1c=L1WlierecisaconstantInverseLogFunction:TomapavziderangeoflowgrayJevelvaluesintheinputimageintoanairowerra

14、ngeofoutputlevels.Tomapanairowrangeofhighgiay-levelvaluesintlieinputimageintoawiderrangeofoutputlevels.InverseLogApplications:Toexpandthevaluesofbnglitpixelsinanimagewhilecompressingthelowei-levelvalueLogTransfomiationsconckisionNote:Anycuivehavingthegeneralshapeofthelogfunctionscanaccomplishtliesim

15、ilarfunctionofSpreading/Compressingofgraylevels.Comparedwithlogtransformation,Power-Lavztiansfonnations（discussedlater）aremoreversatile（通用的，多而于的）withdifferentparametersHowevei,logfiinctioncancompressthedynamicrangeofimageswithlargevariationsinpixelvalues.Power-LawTransformationsDefnntionsTheBasicfor

16、mofPower-LawTransfomiations:S=CryWlierecandyarepositiveconstantsFunctions:Thecaseofyl:similartothecaseofinveiselogfunctionPiecewise-LinearTransfonnationFunction分段線性Advantage:ThefonnofpiecevziseflinctioncanbearbitranlycomplexDisadvantage:TheirspecificationrequiresmoreuserinputApplicationsContrastStre

17、tching（對(duì)比度拉伸）Incieasethedynamicrangeoftliegraylevelsinanlow-confaastnnage.Gray-LevelSlicing（灰度切割/灰度窗II變換）:Highlight吏顯著）aspecificrangeofgraylevelsinanimageBit-PlaneSlicing（位平面切割）HighliglittliecontnbutionmadetototalimageappearancebyspecificbitsGraylevelmapping-ConclusionsTheprocessoftakingtheonginalda

18、tanumbersandchangingtliemtonewvaluesiscalledmappuig.Amathematicaldescnptionoftliemappingiscalledamappingfunction.ApplicationBnghtness/contiastenliancementDisplaycalibration(顯示標(biāo)定)/photometiiccalibration(光度學(xué)標(biāo)定)Contourlinedetenmnation(輪廓線確定)Pointprocesses-operationsatapixeldependonlyonthatpixelThesimpl

19、estcaseisthresholdingwheretlieintensityprofileisreplacedbyastepfunction階躍函數(shù)，activeatachosenthresholdvalue.Intinscaseanypixelwithagreylevelbelov/thethresholdintheinputimagegetsmappedto0intheoutputimage.Otlierpixelsaremappedto255加法、減法：Definitionsofaritlimetic/logicoperationsOperationsareperfonnedonapi

20、xel-by-pixelbasisbetweentv/oormoreimages.r(x,y)=gIl(x,y),I2(x,y)Basedonthesoftwareorhardwarebeingused,tlieycanbedoneSequentiallyorinParallelImageSubtractionInputimages:f(x9y)ndh(x9y),subtractionofthem:g(x,刃=f(x9y)h(x,y)Purpose:enliancetliedifferencesbetweenimagesOriginalfractalimageResultofsettingst

21、hefourlower-orderbitplanestozero.Differencebetween(a)and(b).HistogramequalizeddifferenceimageEvaluatingtlieeffectofsettingto0thelower-orderplanesImageCombiningThisissimilartoadditionbutproportionsofthecoirespondingpixelsofthetwounagesareaddedtogether.Wemaywishtogivemoreemphasistooneimagethantheother

22、.Thiscanbedonebyalphablending1混合g(x,y)=afl(x,y)+(1-a)C(x,y)WliencanthisEquationis05,g(x,y)becomesasimple,evenly-vzeightedaverageoftlietwoinputimages.Itispossibleforaatovaiy,eveiypixelofanunagecanhaveitsowna,storedinaseparatealphachannel.如何設(shè)計(jì)映射函數(shù)？(計(jì)算大題)直方圖的定義、圖像與灰度直方圖間的對(duì)應(yīng)關(guān)系？不同圖像直方圖的特點(diǎn)(高調(diào)、中調(diào)、低調(diào))？Image

23、Histogivam(直方圖):BrilitnesshistogramprovidesthefrequencyofthebrightnessvalueintheimageGraylevelmappingandhistogram：D0=axDr+bb0,histogrammovestothenglittomakeimagebrightei*bl,histogramcontiastincreasesal,histogramcontiastdecreases例:Do=1.2xDf+50ExamplesofHistogramsDarkimage-concentiatedonthelowsideoftl

24、iegrayscale.Brightimage-biasedtowardthehighsideoftliegrayscaleLowcontrastimage-narrowandcenteredtowardthemiddleofthegrayscaleHigli-contiastimagecoverabroadrange,thedistnbutionisnottoofarfromunifbim11坐標(biāo)軸參數(shù)的含義？直方圖運(yùn)算(算數(shù)、奇與偶的關(guān)系)，圖像運(yùn)算與直方圖的關(guān)系？直方圖均衡的基本思想是什么？ContinuousCase:Considerforthecaseofcontinuousimag

25、esandcontinuoustransformationfunctions.LetthetransformationflinctionbeS=T(r),0r1Wlierer=0representsblackandr=lrepresentsvzhite.AssumetliatthefaansfonnationfunctionT(r)satisfiesthefollowingtwoConditions:A9T(r)issingle-valued單值的andmonotonicallyincreasing單調(diào)遞inOrguaranteetheinveisetiansfonnationwillexis

26、t.T(r)ismonotonicallyincreasnigtopreseivetheincreasingorderfiomblacktowhiteintlieoutputimage.B.T(r)lforOrguaianteestheoutputlevelisinthesamerangeastheinputlevelsDiscreteVersion:Justuseprobabilities概率andsummations總和insteadofprobabilitydensityfunctionsandintegrals.Theprobabilityofoccuirenceofgraylevel

27、inanimageisapproxunatedbyPg=0,1,2,，厶-1ThetransformationfunctionisSk=k=0丄2,.L2inTomapeachpixelwitlilevelintheinputimageintoacoirespondingpixelwithlevelS*intheoutputimageThetransformationgiveninaboveequationiscalledhistogramequalizationorhistogiamlinearization空域?yàn)V波、平滑、銳化典型方法、種類、應(yīng)用特點(diǎn)(平滑均值、平滑中值：銳化拉普拉斯算子，

28、銳化微分算子)Filtersletthroughorattenuate肖ij弱specificrangesofimagedetailseg.slow/gradualorfastchangesinpixelvalueHencetlieclassificationoffiltersintolow-passfiltersAttenuates(變?nèi)?fastchangesnipixelvaluebutletsthroulislow/gradualchangesTypicalapplication:noiseremovalTendstoblurunagehigh-passfiltersAttenuate

29、sslow/giadualchangesinpixelvaluebutletsthrouifastchangesTypicalapplication:edgeenhancementTendstobesensitivetonoiseOutputvaluesmaybeoutsidenumericalrangeofpixelvalueScalingmayberequuedAndotheitypesoffiltersband-passfilteis,band-rejectfilteis,SmootliingSpatialFiltersMotivationbluiring（模糊）andnoiseredu

30、ctionBlurringisusedinpreprocessingstepsRemovalofsmalldetailsfromanimagepriortoobjectextractionBridgingofsmallgaps（MJ隙）inlinesorcuivesReductionoffalsecontours（ducedbyzooming）NoiseReductionCanbeaccomplishedbyblurringwithalinearfilterandalsobynonlinearfiltenng.SmootliingLinearFiltersAveragingfilt

31、er,lowpassfilterIdea:Toreplacethevalueofeveiypixelinanimagebytlieaverageoftliegraylevelsintlieneighboihooddefinedbythefilteimask,whichresultsinanimagewithreduced“sharptransitionsingraylevelsApplicationsNoisereductionHowever,becauseofshaiptiansitionsreduction,edgescanalsobebluired.（Undesirable）Thesmo

32、othingoffalsecontoursThefalsecontoursresultfiomusinganinsufficientnumberofgraylevelsThereductionofciirelevant1detailinanimagecIrrelevantdetailnmeanspixelregionstliataresmallwithrespecttothesizeoffilteimask.SharpeningSpatialFiltersObjectiveofSharpeningTohighlightfinedetailToenliancedetailthathasbeenb

33、luiTed（模糊）EitherinerrorOrasanaturaleffectofaparticularimageacquisition（采集）methodApplicationsElectronprinting（電子E卩刷）andmedicalimagingIndustrialinspection匸業(yè)檢測(cè)andautonomousguidance自制導(dǎo)inmilitaiysystemsLaplacianhfasksIsotiopic各向同性的filtersRotationmvanantCoefficientsThecenteicoefficientoftlieLaplacianmaski

34、snegative,theothersarepositive,orviceversa.Thesumofcoefficientsis0Themaskcontainingthediagonalteimsusuallyarealittleshaiper.TheLaplaciancanhighlightsgrayleveldiscontinuitiesanddeemphasizeregionwithslowlyvaiyinggraylevelsItproducesgrayishedgelinesandotlierdiscontinuities.Howevei;tliesefeaturesaresupe

35、rimposedonadark,featurelessbackground.Howcanwerecovertheonginalbackgioundwhilepreseivingthesharpeningeffect?Theanswerissunpie,justaddbacktheonginalimageasfollowsSharpeningspatialfilterSmoothingspatialfilterLinearfilter(meanfilter)NoisereductionblurringBlur(smooth)ApplicationsSmoothingNoiseReductiona

36、ndObjectDetectionExample2ndDerivative(Laplacian)EnhancedetailDeblur(sharpen)Non-linear(Medianfilter)1stDerivative(gradient)尺寸與濾波效果的關(guān)系？濾波器系數(shù)的特點(diǎn)？濾波器形狀？濾波器的結(jié)構(gòu)，濾波算法的實(shí)現(xiàn)SmootliingLinearFiltersThelargeitliesize,themorebluiredtheunageandtlielesstliedetailsCoefficients(系數(shù))Largertlian0Averaging/vzeiglited(red

37、ucingeffectofborder)Nonnalization：Smootliingmasksarenomiallyadjustedtopreseiveaveragevalue(Ewi=1)頻域增強(qiáng)16傅里葉變換公式、定義、性質(zhì)，有哪些特點(diǎn)？譜與空域特征的關(guān)系？17.頻域?yàn)V波（理想、巴特沃斯、高斯）（低通、高通）特點(diǎn)？振鈴效應(yīng)？各個(gè)濾波器之間的比較，適用情況ButterworthfiltersOrder=2Thereislessnngingeffectcomparedtotlioseofideallowpassfilters!Ringingeffect振鈴效應(yīng)Ringingiscaused

38、asthelow-passfilteiingintioducesthesin（r）/nnthekernel.復(fù)原18圖像質(zhì)量退化的原因？模型？SimplifiedassumptionsNoiseisindependentofsignalNoisetypesIndependentofspatiallocationImpulsenoiseAdditivewhiteGaussiannoiseSpatiallydependentPeiiodicnoise處理技術(shù)？（中值一孤立點(diǎn)、椒鹽；帶阻、陷波一去除圖像中某一頻率分量、周期噪聲）PeriodicNoiseSource:electncalorelect

39、romechanicalinterferenceduringimageacquisitionCharacteristicsSpatiallydependentPeiiodic-easytoobseiveinfrequencydomainProcessingmetliodSuppressingnoisecomponentinfrequencydomainPeriodicnoisecanbereducedbysettingfrequencycoinponentscoirespendingtonoisetozero.BandRejectFilters頻帶抑制（帶阻）濾波器Usetoeluninate

40、fiequencycomponentsinsomebandsPenodicNotchRejectFilters陷波濾波器Anotchrejectfilterisusedtoeliminatesomefrequencycomponents.增強(qiáng)與復(fù)原的關(guān)系？彩色幾個(gè)彩色系統(tǒng)（RGB、CMY、CMYK、HSI）各自特點(diǎn)？各分量含義？RGBmodel:Red,Green,BlueColormonitors,colorvideocamerasBasicknowledgeofRGBBasedonCartesiancoordinatesystemColorsaredefinedbyvectorsexten

41、dingf?omtlieongininR,GandBcomponentsAllvaluesofR,GandBarenoimalizedintherange0,1ImagesrepresentedintheRGBmodelConsistsof3coinponents,R,GandBIftliepixeldepthofeachcomponentis8bits,thereare24bitsinRGBcolorpixelFull-colorunageisoftenusedtodenotea24-bitRGBcolorimageAndtotalnumberofcolorsoftheimageis（28）3=16,777,216Indigitalimages,weoftenusetheintegerrange0,1,2,.,255,ratlierthantlienonnalizedrealrange0,1foreachcolorcoinponent.CMYandCMYKmodels:CMY:Cyan青,Magenta品紅,Yellow,CMYK：Cyan,Magenta,Yellow,BlackColorprin