digital image processing matlab gonzalez pdf download
Digital Image Processing Part II pdf
... Digital Image Processing – Part II 54 Morphological Image Processing (a)(c)(d)(b) Digital Image Processing – Part II 87 Image Segmentation (a) (b)(c)(a)(b) Digital Image ... Digital Image Processing – Part II 13 Colour Image Processing (b) Figure 5 Illustration of intensity slicing and colour assignment. Digital Image Processing – Part II 10 Colour Image ... (a)(b)(c)(a)(b)(c) Digital Image Processing – Part II 59 Morphological Image Processing Figure 43 Example of morphological reconstruction.(a) A binary image of the blobs as the mask image; (b)...
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Digital Image Processing [GONZALEZ R C WOOD] COVERS
... xix1Introduction 151.1 What Is Digital Image Processing? 151.2 The Origins of Digital Image Processing 171.3 Examples of Fields that Use Digital Image Processing 211.3.1 Gamma-Ray Imaging ... Used 341.4 Fundamental Steps in Digital Image Processing 391.5 Components of an Image Processing System 42Summary 44References and Further Reading 452 Digital Image Fundamentals 342.1 Elements ... Cataloging-in-Pubblication Data Gonzalez, Rafael C. Digital Image Processing / Richard E. Woodsp. cm.Includes bibliographical referencesISBN 0-201-18075-81. Digital Imaging. 2. Digital Techniques. I....
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digital image processing using matlab
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Digital Image Processing CHAPTER 01-02-03
... image processing is intimately tied to the development of the digital computer. In fact, digital images require so much storage and computational power that progressin the field of digital image ... Publishing, NY.Baxes, G.A. [1994]. Digital Image Processing: Principles and Applications, John Wiley &Sons, NY. Gonzalez, R. C. and Woods, R. E. [1992]. Digital Image Processing, Addison-Wesley,Reading, ... overlap be-tween image processing and image analysis is the area of recognition of indi-vidual regions or objects in an image. Thus, what we call in this book digital image processing encompasses...
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Tài liệu Digital Signal Processing Handbook P70 pdf
... unknown at this stage of processing in practice [7]. There are several non-optimized temporalDOF reduction methods available, such as the Doppler-domain (joint domain) localized processing (DDL/JDL) ... Press LLC Space-TimeAdaptiveProcessingforAirborneSurveillanceRadarHongWangSyracuseUniversity70.1MainReceiveApertureandAnalogBeamforming70.2DatatobeProcessed70.3TheProcessingNeedsandMajorIssues70.4TemporalDOFReduction70.5AdaptiveFilteringwithNeededandSample-SupportableDOFandEmbeddedCFARProcessing70.6Scan-To-ScanTrack-Before-DetectProcessing70.7Real-TimeNonhomogeneityDetectionandSampleConditioningandSelection70.8SpaceorSpace-RangeAdaptivePre-SuppressionofJammers70.9ASTAPExamplewithaRevisittoAnalogBeamforming70.10SummaryReferencesSpace-TimeAdaptiveProcessing(STAP)isamulti-dimensionalfilteringtechniquedevelopedforminimizingtheeffectsofvariouskindsofinterferenceontargetdetectionwithapulsedairbornesurveillanceradar.Themostcommondimensions,orfilteringdomains,generallyincludetheaz-imuthangle,elevationangle,polarizationangle,dopplerfrequency,etc.inwhichtherelativelyweaktargetsignaltobedetectedandtheinterferencehavecertaindifferences.Inthefollowing,theSTAPprinciplewillbeillustratedforfilteringinthejointazimuthangle(space)anddopplerfrequency(time)domainonly.STAPhasbeenaveryactiveresearchanddevelopmentareasincethepublicationofReedetal.’sseminalpaper[1].WiththerecentlycompletedMultichannelAirborneRadarMeasurementproject(MCARM)[2]–[5],STAPhasbeenestablishedasavaluablealternativetothetraditionalapproaches,suchasultra-lowsidelobebeamformingandDisplacedPhaseCenterAntenna(DPCA)[6].MuchofSTAPresearchanddevelopmenteffortshavebeendrivenbytheneedstomakethesystemaffordable,tosimplifyitsfront-hardwarecalibration,andtominimizethesystem’sperformancelossinseverelynonhomogeneousenvironments.Figure70.1isageneralconfigurationofSTAPfunctionalblocks[5,7]whoseprincipleswillbediscussedinthefollowingsections.c1999byCRCPressLLC ... Space-TimeAdaptiveProcessingforAirborneSurveillanceRadarHongWangSyracuseUniversity70.1MainReceiveApertureandAnalogBeamforming70.2DatatobeProcessed70.3TheProcessingNeedsandMajorIssues70.4TemporalDOFReduction70.5AdaptiveFilteringwithNeededandSample-SupportableDOFandEmbeddedCFARProcessing70.6Scan-To-ScanTrack-Before-DetectProcessing70.7Real-TimeNonhomogeneityDetectionandSampleConditioningandSelection70.8SpaceorSpace-RangeAdaptivePre-SuppressionofJammers70.9ASTAPExamplewithaRevisittoAnalogBeamforming70.10SummaryReferencesSpace-TimeAdaptiveProcessing(STAP)isamulti-dimensionalfilteringtechniquedevelopedforminimizingtheeffectsofvariouskindsofinterferenceontargetdetectionwithapulsedairbornesurveillanceradar.Themostcommondimensions,orfilteringdomains,generallyincludetheaz-imuthangle,elevationangle,polarizationangle,dopplerfrequency,etc.inwhichtherelativelyweaktargetsignaltobedetectedandtheinterferencehavecertaindifferences.Inthefollowing,theSTAPprinciplewillbeillustratedforfilteringinthejointazimuthangle(space)anddopplerfrequency(time)domainonly.STAPhasbeenaveryactiveresearchanddevelopmentareasincethepublicationofReedetal.’sseminalpaper[1].WiththerecentlycompletedMultichannelAirborneRadarMeasurementproject(MCARM)[2]–[5],STAPhasbeenestablishedasavaluablealternativetothetraditionalapproaches,suchasultra-lowsidelobebeamformingandDisplacedPhaseCenterAntenna(DPCA)[6].MuchofSTAPresearchanddevelopmenteffortshavebeendrivenbytheneedstomakethesystemaffordable,tosimplifyitsfront-hardwarecalibration,andtominimizethesystem’sperformancelossinseverelynonhomogeneousenvironments.Figure70.1isageneralconfigurationofSTAPfunctionalblocks[5,7]whoseprincipleswillbediscussedinthefollowingsections.c1999byCRCPressLLC...
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Tài liệu Digital Signal Processing Handbook P68 pdf
... IntroductionandMotivationThischapterreviewstheapplicationsofantennaarraysignalprocessingtomobilenetworks.Cellularnetworksarerapidlygrowingaroundtheworldandanumberofemergingtechnologiesareseentobecriticaltotheirimprovedeconomicsandperformance.Amongtheseistheuseofmultipleantennasandspatialsignalprocessingatthebasestation.ThistechnologyisreferredtoasSmartAntennasor,moreaccurately,asSpace-TimeProcessing(STP).STPreferstoprocessingtheantennaoutputsinbothspaceandtimetomaximizesignalquality.Acellulararchitectureisusedinanumberofmobile/portablecommunicationsapplications.Cellsizesmayrangefromlargemacrocells,whichservehighspeedmobiles,tosmallermicrocellsorverysmallpicocells,whicharedesignedforoutdoorandindoorapplications.Eachoftheseoffersdifferentchannelcharacteristicsand,therefore,posesdifferentchallengesforSTP.Likewise,differentservicedeliverygoalssuchasgradeofserviceandtypeofservice:voice,data,orvideo,alsoneedspecicSTPsolutions.STPprovidesthreeprocessingleverages.Therstisarraygain.Multipleantennascapturemoresignalenergy,whichcanbecombinedtoimprovethesignal-to-noiseratio(SNR).Nextisspatialdiversitytocombatspace-selectivefading.Finally,STPcanreduceco-channel,adjacentchannel,andinter-symbolinterference.Theorganizationofthischapterisasfollows.InSection68.2,wedescribethevectorchannelmodelforabasestationantennaarray.InSection68.3wediscussthealgorithmsforSTP.Section68.4outlinestheapplicationsofSTPincellularnetworks.Finally,weconcludewithasummaryinSection68.5.c1999byCRCPressLLC ... York, 1974.[23] Krim, H. and Viberg, M., Two decades of array signal processing research: the parametricapproach,IEEE Signal Processing Magazine,13(4), 67–94, July 1996.[24] Lee, W.C.,Mobile ... blindidentification of multichannel FIR filters,IEEE Trans. on Signal Processing, 1995.[29] Orfanidis, S.J.,Optimal Signal Processing – An Introduction,Macmillan Publishing Co., NewYork, 1985.[30]...
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Tài liệu Digital Signal Processing Handbook P66 pdf
... 1995.[35] Reddy, V.U., Mathew, G. and Paulraj, A., Some algorithms for eigensubspaceestimation, Digital Signal Processing, 5, 97–115, 1995.[36] Regalia, P.A. and Loubaton, P., Rational subspaceestimation ... data matrix where the kth column corresponds to the kthsnapshot vector, xk∈ Cn. With block processing, the correlation matrix for a zero mean, stationary,ergodic vector process is typically ... sensor noise usually dominates numerical errors, this choice may not becritical in most signal processing applications.66.2.2 Short Memory Windows for Time Varying EstimationUltimately, weareinterestedin...
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Tài liệu Digital Signal Processing Handbook P23 pdf
... limn→∞E{W(n)} .(23.14)c1999 by CRC Press LLC Williamson, G.A. “Adaptive IIR Filters” Digital Signal Processing HandbookEd. Vijay K. Madisetti and Douglas B. WilliamsBoca Raton: CRC Press ... Signal Processing, 41(2), 617–628, 1993.[14] Lin, J N. and Unbehauen, R., Bias-remedy least mean square equation error algorithm for IIRparameter recursive estimation,IEEE Trans. Signal Processing, 40(1), ... Acoustics, Speech, Signal Processing, 38(7), 1222–1227,1990.[17] Regalia, P.A., Stable and efficient latticealgorithms for adaptive IIR filtering,IEEE Trans.Signal Processing, 40(2), 375–388,...
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Tài liệu Digital Signal Processing Handbook P20 pdf
... Ling, F., and Nikias, C.L.,Advanced Digital Signal Processing ,Macmillan Publishing, New York, 1992.[3] Widrow, B. and Stearns, S.D.,Adaptive Signal Processing , Prentice-Hall, Englewood ... diverges.c1999 by CRC Press LLC Sayed, A.H. & Rupp, M. “Robustness Issues in Adaptive Filtering” Digital Signal Processing HandbookEd. Vijay K. Madisetti and Douglas B. WilliamsBoca Raton: CRC Press ... algorithms,IEEE Trans.Signal Processing , 44(8), 1982–1989, Aug. 1996.[19] Sayed, A.H. and Kailath, T., A state-space approach to adaptive RLS filtering,IEEE Signal Processing Magazine, 11(3),...
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Tài liệu Digital Signal Processing Handbook P19 pdf
... (19.2)whereW(n)=[w0(n)w1(n)ÃÃÃwL1(n)]Tisthecoefcientvector,X(n)=[x(n)x(n1)ÃÃÃx(nL+1)]Tistheinputsignalvector,d(n)isthedesiredsignal,e(n)istheerrorsignal,andà(n)isthestepsize.TherearethreemainreasonswhytheLMSadaptivelterissopopular.First,itisrelativelyeasytoimplementinsoftwareandhardwareduetoitscomputationalsimplicityandefcientuseofmemory.Second,itperformsrobustlyinthepresenceofnumericalerrorscausedbynite-precisionarithmetic.Third,itsbehaviorhasbeenanalyticallycharacterizedtothepointwhereausercaneasilysetupthesystemtoobtainadequateperformancewithonlylimitedknowledgeabouttheinputanddesiredresponsesignals.c1999byCRCPressLLC [22] Farden,D.C., Tracking properties of adaptivesignal processingalgorithms,IEEETrans.Acoust.,Speech, Signal Processing, ASSP-29(3), 439–446, June 1981.[23] Bitmead, R.R. and Anderson, ... algorithms,IEEE Trans. Signal Processing, 41(9), 2811–2825, Sept. 1993.[25] Douglas, S.C. and Meng, T.H Y., Normalized data nonlinearities for LMS adaptation,IEEETrans. Signal Processing, 42(6), 1352–1365, ... Signal Processing, 4(3), 219–216, May-June 1990.[28] Harris, R.W., Chabries, D.M., and Bishop, F.A., A variable step (VS) adaptive filter algorithm,IEEE Trans. Acoust., Speech, Signal Processing, ASSP-34(2),...
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Tài liệu Digital Signal Processing Handbook P14 pdf
... 1995.[8] Hayes, M.S.,Statistical Digital Signal Processing and Modeling,John Wiley & Sons, New York,1996.[9] Haykin, S.,Advances in Spectrum Analysis and Array Processing, Prentice Hall, EnglewoodCliffs, ... which plays a majorrole in many applied sciences such as radar, speech processing, underwater acoustics, biomedicalsignal processing, sonar, seismology, vibration analysis, control theory, and ... n2(14.70)c1999 by CRC Press LLC Djuric, P.M. & Kay S.M. “Spectrum Estimation and Modeling” Digital Signal Processing HandbookEd. Vijay K. Madisetti and Douglas B. WilliamsBoca Raton: CRC Press...
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Tài liệu Digital Signal Processing Handbook P13 pdf
... 13.3 and 13.4.c1999 by CRC Press LLC Hero, A. “Signal Detection and Classification” Digital Signal Processing HandbookEd. Vijay K. Madisetti and Douglas B. WilliamsBoca Raton: CRC Press ... and Estimation, Prentice-Hall, Englewood Cliffs,NJ, 1995.[8] Scharf, L.L.,Statistical Signal Processing: Detection, Estimation, and Time Series Analysis,Addison-Wesley, Reading, MA, 1991.[9] ... =qj=1ajpk=1sjkbk(ti) + w(ti), i = 1, ,n.This model applies to a wide range of applications in narrowband array processing and has beenthoroughly studied in the context of signal detection in [14]. The m-element...
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