digital image processing with matlab 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 ... connected to the image border. (a) (c) (d) (b) Digital Image Processing – Part II 89 Image Segmentation 3.9 Object-oriented image segmentation The challenge of understanding images is...

... corrections and image registration also are covered. Chapter 6: Color Image Processing. This chapter deals with pseudocolor and full-color image processing. Color models applicable to digital image process- ing ... Image Processing Toolbox, also are available. Areas of Image Processing Covered in the Book Every chapter in this book contains the pertinent MATLAB and IPT material needed to implement the image ... sense.” Digital image processing, as we have defined it, is used successfully in a broad range of areas of exceptional social and economic value. Background on MATLAB and the Image Processing...

... used interchangeably when deal- ing with monochrome (i.e., gray-scale) images. When dealing with color images, the term intensity is used to denote a color image component in certain color spaces, ... 250 0 5000 10000 15000 c a b d FIGURE 3.7 Various ways to plot an image histogram. (a) imhist, (b) bar, (c) stem, (d) plot. Digital Image Processing Using MATLAB đ Second Edition Rafael C. Gonzalez University ... probability density function (PDF) of the intensity levels in a given image, where the subscript is used for differentiating between the PDFs of the input and output images. Suppose that we perform...

... Mathematical Summary for Digital Signal Processing Applications with Matlab Dedicated to my son G.V. Vasig and my wife G. Viji Contents 1 Matrices ... matrix with number of Rows is equal to the number of Columns. (i) Identity matrix The square matrix with all the elements is filled up with zeros except the diag- onal elements which are filled up with ... 1.12. A D 2 4 123 4 557 12 6 7 10 16 3 5 E.S. Gopi Mathematical Summary for Digital Signal Processing Applications with Matlab 123 1.15 Solutions for the System of Linear Equation [A] x Db 35 2 4 4 5 6 3 5 T 0 @ b  2 4 14 25 36 3 5 Ä c x 1 bx 2  1 A D...

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... xix 1 Introduction 15 1.1 What Is Digital Image Processing? 15 1.2 The Origins of Digital Image Processing 17 1.3 Examples of Fields that Use Digital Image Processing 21 1.3.1 Gamma-Ray Imaging ... Used 34 1.4 Fundamental Steps in Digital Image Processing 39 1.5 Components of an Image Processing System 42 Summary 44 References and Further Reading 45 2 Digital Image Fundamentals 34 2.1 Elements ... Representing Digital Images 54 2.4.3 Spatial and Gray-Level Resolution 57 2.4.4 Aliasing and Moiré Patterns 62 2.4.5 Zooming and Shrinking Digital Images 64 vii GONZFM-i-xxii. 5-10-2001 14:22 Page vii Digital...

... image processing is intimately tied to the development of the digital computer. In fact, digital images require so much storage and computational power that progress in the field of digital image ... on images generated by sources that humans are not accustomed to associating with images. These include ultra- sound, electron microscopy, and computer-generated images.Thus, digital image processing ... 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...

... Space-TimeAdaptiveProcessing forAirborneSurveillanceRadar HongWang SyracuseUniversity 70.1MainReceiveApertureandAnalogBeamforming 70.2DatatobeProcessed 70.3TheProcessingNeedsandMajorIssues 70.4TemporalDOFReduction 70.5AdaptiveFilteringwithNeededandSample-Supportable DOFandEmbeddedCFARProcessing 70.6Scan-To-ScanTrack-Before-DetectProcessing 70.7Real-TimeNonhomogeneityDetectionandSample ConditioningandSelection 70.8SpaceorSpace-RangeAdaptivePre-SuppressionofJammers 70.9ASTAPExamplewithaRevisittoAnalogBeamforming 70.10Summary References Space-TimeAdaptiveProcessing(STAP)isamulti-dimensionalfilteringtechniquedevelopedfor minimizingtheeffectsofvariouskindsofinterferenceontargetdetectionwithapulsedairborne surveillanceradar.Themostcommondimensions,orfilteringdomains,generallyincludetheaz- imuthangle,elevationangle,polarizationangle,dopplerfrequency,etc.inwhichtherelativelyweak targetsignaltobedetectedandtheinterferencehavecertaindifferences.Inthefollowing,theSTAP principlewillbeillustratedforfilteringinthejointazimuthangle(space)anddopplerfrequency (time)domainonly. STAPhasbeenaveryactiveresearchanddevelopmentareasincethepublicationofReedetal.’s seminalpaper[1].WiththerecentlycompletedMultichannelAirborneRadarMeasurementproject (MCARM)[2]–[5],STAPhasbeenestablishedasavaluablealternativetothetraditionalapproaches, suchasultra-lowsidelobebeamformingandDisplacedPhaseCenterAntenna(DPCA)[6].Muchof STAPresearchanddevelopmenteffortshavebeendrivenbytheneedstomakethesystemaffordable, tosimplifyitsfront-hardwarecalibration,andtominimizethesystem’sperformancelossinseverely nonhomogeneousenvironments.Figure70.1isageneralconfigurationofSTAPfunctionalblocks[5, 7]whoseprincipleswillbediscussedinthefollowingsections. c  1999byCRCPressLLC ... Unfortunately, such a wish can rarely materialize for a system with a practical aperture size operated in nonhomogeneous environments. With a spatial DOF reductionrequired bythese approachesto bring ... Signal and Data Processing of Small Targets, SPIE Proc. Series, Vol. 1305, Paper 16, 180–192, Orlando, FL, April 16-18, 1990. [27] Wang, H. and Cai, L., On adaptive multiband signal detection with SMI...

... separable with respect to the unknowns, one approach to minimize the cost function in Eq. (68.31) is alternating projections. Starting with an initial estimate of A, we minimize Eq. (68.31) with respect ... described earlier in this chapter. 68.4.3 Channel Reuse Within Cell Reuse within cell (RWC) refers to the reuse of a channel or radio resource within a cell by exploiting differences in the channels. ... ArrayProcessingforMobile Communications A.Paulraj StanfordUniversity C.B.Papadias StanfordUniversity 68.1IntroductionandMotivation 68.2VectorChannelModel PropagationLossandFading ã MultipathEffects ã Typical Channels ã SignalModel ã Co-ChannelInterference ã Signal- Plus-InterferenceModel ã BlockSignalModel ã Spatialand TemporalStructure 68.3AlgorithmsforSTP Single-UserST-MLandST-MMSE ã Multi-UserAlgorithms ã SimulationExample 68.4ApplicationsofSpatialProcessing SwitchedBeamSystems ã Space-TimeFiltering ã Channel ReuseWithinCell 68.5Summary 68.6References 68.1 IntroductionandMotivation Thischapterreviewstheapplicationsofantennaarraysignalprocessingtomobilenetworks.Cellular networksarerapidlygrowingaroundtheworldandanumberofemergingtechnologiesareseentobe criticaltotheirimprovedeconomicsandperformance.Amongtheseistheuseofmultipleantennas andspatialsignalprocessingatthebasestation.ThistechnologyisreferredtoasSmartAntennasor, moreaccurately,asSpace-TimeProcessing(STP).STPreferstoprocessingtheantennaoutputsin bothspaceandtimetomaximizesignalquality. Acellulararchitectureisusedinanumberofmobile/portablecommunicationsapplications.Cell sizesmayrangefromlargemacrocells,whichservehighspeedmobiles,tosmallermicrocellsorvery smallpicocells,whicharedesignedforoutdoorandindoorapplications.Eachoftheseoffersdifferent channelcharacteristicsand,therefore,posesdifferentchallengesforSTP.Likewise,differentservice deliverygoalssuchasgradeofserviceandtypeofservice:voice,data,orvideo,alsoneedspecic STPsolutions.STPprovidesthreeprocessingleverages.Therstisarraygain.Multipleantennas capturemoresignalenergy,whichcanbecombinedtoimprovethesignal-to-noiseratio(SNR).Next isspatialdiversitytocombatspace-selectivefading.Finally,STPcanreduceco-channel,adjacent channel,andinter-symbolinterference. Theorganizationofthischapterisasfollows.InSection68.2,wedescribethevectorchannelmodel forabasestationantennaarray.InSection68.3wediscussthealgorithmsforSTP.Section68.4outlines theapplicationsofSTPincellularnetworks.Finally,weconcludewithasummaryinSection68.5. c 1999byCRCPressLLC ...

... revealing structure involve O(n 3 ) flops per update. An analysis of problems associated with RRQR methods along with a fairly extensive reference list on RRQR methods can be found in [6]. An O(nr) ... ranges from O(nr 2 ) to O(nr). A family of Subspace methods Without EigenDEcomposition (SWEDE) has been proposed by Eriksson et al. [16]. With SWEDE, portions of the correlation matrix must be updated ... n ì N data matrix where the kth column corresponds to the kth snapshot vector, x k ∈ C n . With block processing, the correlation matrix for a zero mean, stationary, ergodic vector process is...

... à(n). As with RLS methods, P(0) = γI with γ a large, positive number. The vector U iv (n) is typically chosen as U iv (n) = [ x(n) ···x(n − M) − z(n − 1) ···−z(n − N) ] T (23.27) with either z(n) ... chosen. With the normalized step size, we require 0 < à<2 and >0 for stability, with typical choices of à = 0.1 and = 0.001. In 23.20, we require that λ satisfy 0 <λ≤ 1, with λ typically ... follows. Property 4: [18] Consider the adaptive filter in Fig. 23.1 with A(q −1 ,n)givenby(23.32), with v(n) an uncorrelated signal and with H u (q −1 ) = 0 (the sufficient order case). Then the parameter...