网络工程毕业论文外文翻译-数字图像处理与边缘检测.doc网络工程毕业论文外文翻译-数字图像处理与边缘检测.doc

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班级学号本科毕业设计论文题目扫描仪色彩增强及可视化系统设计与实现学院计算机学院专业网络工程学生姓名导师姓名DIGITALIMAGEPROCESSINGANDEDGEDETECTIONDIGITALIMAGEPROCESSINGINTERESTINDIGITALIMAGEPROCESSINGMETHODSSTEMSFROMTWOPRINCIPALAPPLICATIONAREASIMPROVEMENTOFPICTORIALINFORMATIONFORHUMANINTERPRETATION;ANDPROCESSINGOFIMAGEDATAFORSTORAGE,TRANSMISSION,ANDREPRESENTATIONFORAUTONOMOUSMACHINEPERCEPTIONANIMAGEMAYBEDEFINEDASATWODIMENSIONALFUNCTION,FX,Y,WHEREXANDYARESPATIALPLANECOORDINATES,ANDTHEAMPLITUDEOFFATANYPAIROFCOORDINATESX,YISCALLEDTHEINTENSITYORGRAYLEVELOFTHEIMAGEATTHATPOINTWHENX,Y,ANDTHEAMPLITUDEVALUESOFFAREALLFINITE,DISCRETEQUANTITIES,WECALLTHEIMAGEADIGITALIMAGETHEFIELDOFDIGITALIMAGEPROCESSINGREFERSTOPROCESSINGDIGITALIMAGESBYMEANSOFADIGITALCOMPUTERNOTETHATADIGITALIMAGEISCOMPOSEDOFAFINITENUMBEROFELEMENTS,EACHOFWHICHHASAPARTICULARLOCATIONANDVALUETHESEELEMENTSAREREFERREDTOASPICTUREELEMENTS,IMAGEELEMENTS,PELS,ANDPIXELSPIXELISTHETERMMOSTWIDELYUSEDTODENOTETHEELEMENTSOFADIGITALIMAGEVISIONISTHEMOSTADVANCEDOFOURSENSES,SOITISNOTSURPRISINGTHATIMAGESPLAYTHESINGLEMOSTIMPORTANTROLEINHUMANPERCEPTIONHOWEVER,UNLIKEHUMANS,WHOARELIMITEDTOTHEVISUALBANDOFTHEELECTROMAGNETICEMSPECTRUM,IMAGINGMACHINESCOVERALMOSTTHEENTIREEMSPECTRUM,RANGINGFROMGAMMATORADIOWAVESTHEYCANOPERATEONIMAGESGENERATEDBYSOURCESTHATHUMANSARENOTACCUSTOMEDTOASSOCIATINGWITHIMAGESTHESEINCLUDEULTRASOUND,ELECTRONMICROSCOPY,ANDCOMPUTERGENERATEDIMAGESTHUS,DIGITALIMAGEPROCESSINGENCOMPASSESAWIDEANDVARIEDFIELDOFAPPLICATIONSTHEREISNOGENERALAGREEMENTAMONGAUTHORSREGARDINGWHEREIMAGEPROCESSINGSTOPSANDOTHERRELATEDAREAS,SUCHASIMAGEANALYSISANDCOMPUTERVISION,STARTSOMETIMESADISTINCTIONISMADEBYDEFININGIMAGEPROCESSINGASADISCIPLINEINWHICHBOTHTHEINPUTANDOUTPUTOFAPROCESSAREIMAGESWEBELIEVETHISTOBEALIMITINGANDSOMEWHATARTIFICIALBOUNDARYFOREXAMPLE,UNDERTHISDEFINITION,EVENTHETRIVIALTASKOFCOMPUTINGTHEAVERAGEINTENSITYOFANIMAGEWHICHYIELDSASINGLENUMBERWOULDNOTBECONSIDEREDANIMAGEPROCESSINGOPERATIONONTHEOTHERHAND,THEREAREFIELDSSUCHASCOMPUTERVISIONWHOSEULTIMATEGOALISTOUSECOMPUTERSTOEMULATEHUMANVISION,INCLUDINGLEARNINGANDBEINGABLETOMAKEINFERENCESANDTAKEACTIONSBASEDONVISUALINPUTSTHISAREAITSELFISABRANCHOFARTIFICIALINTELLIGENCEAIWHOSEOBJECTIVEISTO4CHAPTER1■INTRODUCTIONEMULATEHUMANINTELLIGENCETHEFIELDOFAIISINITSEARLIESTSTAGESOFINFANCYINTERMSOFDEVELOPMENT,WITHPROGRESSHAVINGBEENMUCHSLOWERTHANORIGINALLYANTICIPATEDTHEAREAOFIMAGEANALYSISALSOCALLEDIMAGEUNDERSTANDINGISINBETWEENIMAGEPROCESSINGANDCOMPUTERVISIONTHEREARENOCLEARCUTBOUNDARIESINTHECONTINUUMFROMIMAGEPROCESSINGATONEENDTOCOMPUTERVISIONATTHEOTHERHOWEVER,ONEUSEFULPARADIGMISTOCONSIDERTHREETYPESOFCOMPUTERIZEDPROCESSESINTHISCONTINUUMLOW,MID,ANDHIGHLEVELPROCESSESLOWLEVELPROCESSESINVOLVEPRIMITIVEOPERATIONSSUCHASIMAGEPREPROCESSINGTOREDUCENOISE,CONTRASTENHANCEMENT,ANDIMAGESHARPENINGALOWLEVELPROCESSISCHARACTERIZEDBYTHEFACTTHATBOTHITSINPUTSANDOUTPUTSAREIMAGESMIDLEVELPROCESSINGONIMAGESINVOLVESTASKSSUCHASSEGMENTATIONPARTITIONINGANIMAGEINTOREGIONSOROBJECTS,DESCRIPTIONOFTHOSEOBJECTSTOREDUCETHEMTOAFORMSUITABLEFORCOMPUTERPROCESSING,ANDCLASSIFICATIONRECOGNITIONOFINDIVIDUALOBJECTSAMIDLEVELPROCESSISCHARACTERIZEDBYTHEFACTTHATITSINPUTSGENERALLYAREIMAGES,BUTITSOUTPUTSAREATTRIBUTESEXTRACTEDFROMTHOSEIMAGESEG,EDGES,CONTOURS,ANDTHEIDENTITYOFINDIVIDUALOBJECTSFINALLY,HIGHERLEVELPROCESSINGINVOLVES“MAKINGSENSE”OFANENSEMBLEOFRECOGNIZEDOBJECTS,ASINIMAGEANALYSIS,AND,ATTHEFARENDOFTHECONTINUUM,PERFORMINGTHECOGNITIVEFUNCTIONSNORMALLYASSOCIATEDWITHVISIONBASEDONTHEPRECEDINGCOMMENTS,WESEETHATALOGICALPLACEOFOVERLAPBETWEENIMAGEPROCESSINGANDIMAGEANALYSISISTHEAREAOFRECOGNITIONOFINDIVIDUALREGIONSOROBJECTSINANIMAGETHUS,WHATWECALLINTHISBOOKDIGITALIMAGEPROCESSINGENCOMPASSESPROCESSESWHOSEINPUTSANDOUTPUTSAREIMAGESAND,INADDITION,ENCOMPASSESPROCESSESTHATEXTRACTATTRIBUTESFROMIMAGES,UPTOANDINCLUDINGTHERECOGNITIONOFINDIVIDUALOBJECTSASASIMPLEILLUSTRATIONTOCLARIFYTHESECONCEPTS,CONSIDERTHEAREAOFAUTOMATEDANALYSISOFTEXTTHEPROCESSESOFACQUIRINGANIMAGEOFTHEAREACONTAININGTHETEXT,PREPROCESSINGTHATIMAGE,EXTRACTINGSEGMENTINGTHEINDIVIDUALCHARACTERS,DESCRIBINGTHECHARACTERSINAFORMSUITABLEFORCOMPUTERPROCESSING,ANDRECOGNIZINGTHOSEINDIVIDUALCHARACTERSAREINTHESCOPEOFWHATWECALLDIGITALIMAGEPROCESSINGINTHISBOOKMAKINGSENSEOFTHECONTENTOFTHEPAGEMAYBEVIEWEDASBEINGINTHEDOMAINOFIMAGEANALYSISANDEVENCOMPUTERVISION,DEPENDINGONTHELEVELOFCOMPLEXITYIMPLIEDBYTHESTATEMENT“MAKINGSENSE”ASWILLBECOMEEVIDENTSHORTLY,DIGITALIMAGEPROCESSING,ASWEHAVEDEFINEDIT,ISUSEDSUCCESSFULLYINABROADRANGEOFAREASOFEXCEPTIONALSOCIALANDECONOMICVALUETHEAREASOFAPPLICATIONOFDIGITALIMAGEPROCESSINGARESOVARIEDTHATSOMEFORMOFORGANIZATIONISDESIRABLEINATTEMPTINGTOCAPTURETHEBREADTHOFTHISFIELDONEOFTHESIMPLESTWAYSTODEVELOPABASICUNDERSTANDINGOFTHEEXTENTOFIMAGEPROCESSINGAPPLICATIONSISTOCATEGORIZEIMAGESACCORDINGTOTHEIRSOURCEEG,VISUAL,XRAY,ANDSOONTHEPRINCIPALENERGYSOURCEFORIMAGESINUSETODAYISTHEELECTROMAGNETICENERGYSPECTRUMOTHERIMPORTANTSOURCESOFENERGYINCLUDEACOUSTIC,ULTRASONIC,ANDELECTRONICINTHEFORMOFELECTRONBEAMSUSEDINELECTRONMICROSCOPYSYNTHETICIMAGES,USEDFORMODELINGANDVISUALIZATION,AREGENERATEDBYCOMPUTERINTHISSECTIONWEDISCUSSBRIEFLYHOWIMAGESAREGENERATEDINTHESEVARIOUSCATEGORIESANDTHEAREASINWHICHTHEYAREAPPLIEDIMAGESBASEDONRADIATIONFROMTHEEMSPECTRUMARETHEMOSTFAMILIAR,ESPECIALLYIMAGESINTHEXRAYANDVISUALBANDSOFTHESPECTRUMELECTROMAGNETICWAVESCANBECONCEPTUALIZEDASPROPAGATINGSINUSOIDALWAVESOFVARYINGWAVELENGTHS,ORTHEYCANBETHOUGHTOFASASTREAMOFMASSLESSPARTICLES,EACHTRAVELINGINAWAVELIKEPATTERNANDMOVINGATTHESPEEDOFLIGHTEACHMASSLESSPARTICLECONTAINSACERTAINAMOUNTORBUNDLEOFENERGYEACHBUNDLEOFENERGYISCALLEDAPHOTONIFSPECTRALBANDSAREGROUPEDACCORDINGTOENERGYPERPHOTON,WEOBTAINTHESPECTRUMSHOWNINFIGBELOW,RANGINGFROMGAMMARAYSHIGHESTENERGYATONEENDTORADIOWAVESLOWESTENERGYATTHEOTHERTHEBANDSARESHOWNSHADEDTOCONVEYTHEFACTTHATBANDSOFTHEEMSPECTRUMARENOTDISTINCTBUTRATHERTRANSITIONSMOOTHLYFROMONETOTHEOTHERIMAGEACQUISITIONISTHEFIRSTPROCESSNOTETHATACQUISITIONCOULDBEASSIMPLEASBEINGGIVENANIMAGETHATISALREADYINDIGITALFORMGENERALLY,THEIMAGEACQUISITIONSTAGEINVOLVESPREPROCESSING,SUCHASSCALINGIMAGEENHANCEMENTISAMONGTHESIMPLESTANDMOSTAPPEALINGAREASOFDIGITALIMAGEPROCESSINGBASICALLY,THEIDEABEHINDENHANCEMENTTECHNIQUESISTOBRINGOUTDETAILTHATISOBSCURED,ORSIMPLYTOHIGHLIGHTCERTAINFEATURESOFINTERESTINANIMAGEAFAMILIAREXAMPLEOFENHANCEMENTISWHENWEINCREASETHECONTRASTOFANIMAGEBECAUSE“ITLOOKSBETTER”ITISIMPORTANTTOKEEPINMINDTHATENHANCEMENTISAVERYSUBJECTIVEAREAOFIMAGEPROCESSINGIMAGERESTORATIONISANAREATHATALSODEALSWITHIMPROVINGTHEAPPEARANCEOFANIMAGEHOWEVER,UNLIKEENHANCEMENT,WHICHISSUBJECTIVE,IMAGERESTORATIONISOBJECTIVE,INTHESENSETHATRESTORATIONTECHNIQUESTENDTOBEBASEDONMATHEMATICALORPROBABILISTICMODELSOFIMAGEDEGRADATIONENHANCEMENT,ONTHEOTHERHAND,ISBASEDONHUMANSUBJECTIVEPREFERENCESREGARDINGWHATCONSTITUTESA“GOOD”ENHANCEMENTRESULTCOLORIMAGEPROCESSINGISANAREATHATHASBEENGAININGINIMPORTANCEBECAUSEOFTHESIGNIFICANTINCREASEINTHEUSEOFDIGITALIMAGESOVERTHEINTERNETITCOVERSANUMBEROFFUNDAMENTAL8CHAPTER1■INTRODUCTIONCONCEPTSINCOLORMODELSANDBASICCOLORPROCESSINGINADIGITALDOMAINCOLORISUSEDALSOINLATERCHAPTERSASTHEBASISFOREXTRACTINGFEATURESOFINTERESTINANIMAGEWAVELETSARETHEFOUNDATIONFORREPRESENTINGIMAGESINVARIOUSDEGREESOFRESOLUTIONINPARTICULAR,THISMATERIALISUSEDINTHISBOOKFORIMAGEDATACOMPRESSIONANDFORPYRAMIDALREPRESENTATION,INWHICHIMAGESARESUBDIVIDEDSUCCESSIVELYINTOSMALLERREGIONSCOMPRESSION,ASTHENAMEIMPLIES,DEALSWITHTECHNIQUESFORREDUCINGTHESTORAGEREQUIREDTOSAVEANIMAGE,ORTHEBANDWIDTHREQUIREDTOTRANSMIITALTHOUGHSTORAGETECHNOLOGYHASIMPROVEDSIGNIFICANTLYOVERTHEPASTDECADE,THESAMECANNOTBESAIDFORTRANSMISSIONCAPACITYTHISISTRUEPARTICULARLYINUSESOFTHEINTERNET,WHICHARECHARACTERIZEDBYSIGNIFICANTPICTORIALCONTENTIMAGECOMPRESSIONISFAMILIARPERHAPSINADVERTENTLYTOMOSTUSERSOFCOMPUTERSINTHEFORMOFIMAGEFILEEXTENSIONS,SUCHASTHEJPGFILEEXTENSIONUSEDINTHEJPEGJOINTPHOTOGRAPHICEXPERTSGROUPIMAGECOMPRESSIONSTANDARDMORPHOLOGICALPROCESSINGDEALSWITHTOOLSFOREXTRACTINGIMAGECOMPONENTSTHATAREUSEFULINTHEREPRESENTATIONANDDESCRIPTIONOFSHAPETHEMATERIALINTHISCHAPTERBEGINSATRANSITIONFROMPROCESSESTHATOUTPUTIMAGESTOPROCESSESTHATOUTPUTIMAGEATTRIBUTESSEGMENTATIONPROCEDURESPARTITIONANIMAGEINTOITSCONSTITUENTPARTSOROBJECTSINGENERAL,AUTONOMOUSSEGMENTATIONISONEOFTHEMOSTDIFFICULTTASKSINDIGITALIMAGEPROCESSINGARUGGEDSEGMENTATIONPROCEDUREBRINGSTHEPROCESSALONGWAYTOWARDSUCCESSFULSOLUTIONOFIMAGINGPROBLEMSTHATREQUIREOBJECTSTOBEIDENTIFIEDINDIVIDUALLYONTHEOTHERHAND,WEAKORERRATICSEGMENTATIONALGORITHMSALMOSTALWAYSGUARANTEEEVENTUALFAILUREINGENERAL,THEMOREACCURATETHESEGMENTATION,THEMORELIKELYRECOGNITIONISTOSUCCEEDREPRESENTATIONANDDESCRIPTIONALMOSTALWAYSFOLLOWTHEOUTPUTOFASEGMENTATIONSTAGE,WHICHUSUALLYISRAWPIXELDATA,CONSTITUTINGEITHERTHEBOUNDARYOFAREGIONIE,THESETOFPIXELSSEPARATINGONEIMAGEREGIONFROMANOTHERORALLTHEPOINTSINTHEREGIONITSELFINEITHERCASE,CONVERTINGTHEDATATOAFORMSUITABLEFORCOMPUTERPROCESSINGISNECESSARYTHEFIRSTDECISIONTHATMUSTBEMADEISWHETHERTHEDATASHOULDBEREPRESENTEDASABOUNDARYORASACOMPLETEREGIONBOUNDARYREPRESENTATIONISAPPROPRIATEWHENTHEFOCUSISONEXTERNALSHAPECHARACTERISTICS,SUCHASCORNERSANDINFLECTIONSREGIONALREPRESENTATIONISAPPROPRIATEWHENTHEFOCUSISONINTERNALPROPERTIES,SUCHASTEXTUREORSKELETALSHAPEINSOMEAPPLICATIONS,THESEREPRESENTATIONSCOMPLEMENTEACHOTHERCHOOSINGAREPRESENTATIONISONLYPARTOFTHESOLUTIONFORTRANSFORMINGRAWDATAINTOAFORMSUITABLEFORSUBSEQUENTCOMPUTERPROCESSINGAMETHODMUSTALSOBESPECIFIEDFORDESCRIBINGTHEDATASOTHATFEATURESOFINTERESTAREHIGHLIGHTEDDESCRIPTION,ALSOCALLEDFEATURESELECTION,DEALSWITHEXTRACTINGATTRIBUTESTHATRESULTINSOMEQUANTITATIVEINFORMATIONOFINTERESTORAREBASICFORDIFFERENTIATINGONECLASSOFOBJECTSFROMANOTHERRECOGNITIONISTHEPROCESSTHATASSIGNSALABELEG,“VEHICLE”TOANOBJECTBASEDONITSDESCRIPTORSASDETAILEDBEFORE,WECONCLUDEOURCOVERAGEOFDIGITALIMAGEPROCESSINGWITHTHEDEVELOPMENTOFMETHODSFORRECOGNITIONOFINDIVIDUALOBJECTSSOFARWEHAVESAIDNOTHINGABOUTTHENEEDFORPRIORKNOWLEDGEORABOUTTHEINTERACTIONBETWEENTHEKNOWLEDGEBASEANDTHEPROCESSINGMODULESINFIG2ABOVEKNOWLEDGEABOUTAPROBLEMDOMAINISCODEDINTOANIMAGEPROCESSINGSYSTEMINTHEFORMOFAKNOWLEDGEDATABASETHISKNOWLEDGEMAYBEASSIM
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