digital image processing by gonzalez pdf ebook free download

... 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 ... Cataloging-in-Pubblication Data Gonzalez, Rafael C. Digital Image Processing / Richard E. Woods p. cm. Includes bibliographical references ISBN 0-201-18075-8 1. Digital Imaging. 2. Digital Techniques. I....

... 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 ... 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, ... 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...

... serves c  1999 by CRC Press LLC 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 ... temporal DOF, denoted by N ps and N pt respectively, different from the system’s availables by what is so-called DOF reduction. However, the spatial DOF reduction should be avoided by establishing ... for adaptive suppression, free from strong clutter contamination. Available acquisition methods include the use of clutter -free range-cells for low PRF systems, clutter -free Doppler bins for high...

... replaced by a switch-beam antenna system. The SBS operates by sniffer scanning the beamformer outputs to detect the best two beams which are then c  1999 by CRC Press LLC Note that S(k) by definition ... higher order statistics, IEEE Trans. on Acoustics, Speech, and Signal Processing, 37(3), 360–377, March 1989. c  1999 by CRC Press LLC 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 ...

... by CRC Press LLC R. D. De Groat, et. Al. “Subspace Tracking.” 2000 CRC Press LLC. <http://www.engnetbase.com>. is bounded by a constant, assuming no significant errors are introduced by ... given by X (rect) k =[x k |x k−1 | |x k−N+1 ] and R (rect) k = 1 N X (rect) k  X (rect) k  H . Subtracting the rank one matrix from the correlation estimate is referred to as c  1999 by CRC ... similar processing elements (called artificial neurons) operating in parallel. High com- putational rates (due to massive parallelism) and robustness (due to local neural connectivity) are c  1999 by...

... . (23.14) c  1999 by CRC Press LLC Williamson, G.A. “Adaptive IIR Filters” Digital Signal Processing Handbook Ed. Vijay K. Madisetti and Douglas B. Williams Boca Raton: CRC Press LLC, 1999 c  1999byCRCPressLLC ... be A(q −1 ,n)= a 0 (n) + a 1 (n)q −1 +···+a N (n)q −N , (23.32) c  1999 by CRC Press LLC by considering the algorithm subclass represented by W(n + 1) = W(n) + à(n)U o (n)G(q 1 )[e o (n)] , (23.60) which ... lattice of [17]. The normalized structure is by nature stable, and hence no stability check is necessary in the adaptive algorithm. Furthermore, a c  1999 by CRC Press LLC there exist α and β satisfying...

... e a (i) by à(i) before ltering it by the lter F and then scaling the result by à(i)/ à(i). Similarly, the term à(i) v(i) is rst divided by à(i), then ltered by F, and is nally scaled by à(i)/ à(i). FIGURE ... 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 ... 2α opt , the error of the system diverges. c  1999 by CRC Press LLC Sayed, A.H. & Rupp, M. “Robustness Issues in Adaptive Filtering” Digital Signal Processing Handbook Ed. Vijay K. Madisetti and...

... d(n),orW(n). c  1999 by CRC Press LLC Although we have discussed qualitative criteria by which to choose a fixed step size, it is possible to define specific performance criteria by which to choose ... (19.2) whereW(n)=[w 0 (n)w 1 (n)ÃÃÃw L1 (n)] T isthecoefcientvector,X(n)=[x(n)x(n 1)ÃÃÃx(nL+1)] T istheinputsignalvector,d(n)isthedesiredsignal,e(n)istheerrorsignal, andà(n)isthestepsize. TherearethreemainreasonswhytheLMSadaptivelterissopopular.First,itisrelativelyeasyto implementinsoftwareandhardwareduetoitscomputationalsimplicityandefcientuseofmemory. Second,itperformsrobustlyinthepresenceofnumericalerrorscausedbynite-precisionarithmetic. Third,itsbehaviorhasbeenanalyticallycharacterizedtothepointwhereausercaneasilysetupthe systemtoobtainadequateperformancewithonlylimitedknowledgeabouttheinputanddesired responsesignals. c 1999byCRCPressLLC [22] Farden,D.C., Tracking properties of adaptivesignal processingalgorithms, IEEETrans.Acoust., Speech, Signal Processing, ASSP-29(3), 439–446, ... dominated by the slower-converging modes of the system as the length of adaptation time is increased. Thus, if the desired level of misadjustment is low, the speed of convergence is dominated by the...

... = q  k=−q r[k]e −j2πf k . (14.88) c  1999 by CRC Press LLC defined by x i [n]=x[n + (i − 1)D],n∈{0, 1,···,L− 1} (14.51) where i = 1, 2,···,K, and its periodogram by ˆ P (i) M (f ) = 1 L      L−1  n=0 w[n]x i [n]e −j2πf ... because the samples x[n] areweightedbya nonrectangular window w[n]. The Welch spectrum estimate is then given by ˆ P B (f ) = 1 K K  i=1 ˆ P (i) M (f ) . (14.53) By permitting overlap of sequences, ... process by a rectangular window. Then it is not difficult to show that the expected value of the periodogram is given by [8] E  ˆ P PER (f )  = 1 N  1 0 | W R (f − ξ) | 2 P(ξ)dξ (14.46) c  1999 by...

... 13.4. c  1999 by CRC Press LLC Hero, A. “Signal Detection and Classification” Digital Signal Processing Handbook Ed. Vijay K. Madisetti and Douglas B. Williams Boca Raton: CRC Press LLC, 1999 c  1999byCRCPressLLC ... formed by all linear combinations of the rows of B but are otherwise unknown. This gives a composite null and alternative hypothesis for which the generalized likelihood ratio test can be derived by ... Diego, 1989. c  1999 by CRC Press LLC Under the nullhypothesis the teststatistic T g is distributed as a complex central chi-square random variable with p degrees of freedom, while underthe...

... and Image Processing, vol. I, 150–153, 1995. [14] Singer, A.C., Signal Processing and Communication with Solitons, Ph.D. thesis, Massachusetts Institute of Technology, Feb. 1996. c  1999 by CRC ... with 30 nodes in a loop configuration. c  1999 by CRC Press LLC Singer, A.C. “Signal Processing and Communication with Solitons” Digital Signal Processing Handbook Ed. Vijay K. Madisetti and ... specified by the capacitor voltages. Rather than processing continuous-time signals as with the Toda lattice system, we can use this system to process discrete-time solitons as specified by v n ....

... decision-feedback filtering, IEEE Trans. Circuits Syst. II: Analog and Digital Signal Processing, 40 CAS-II, Jan. 1993. c  1999 by CRC Press LLC pulse shaping filter, the modulator, the channel, ... interference (ISI) is a phenomenon observed by the equalizer caused by frequency distortion of the transmitted signal. This distortion is usually caused by the frequency selective characteristics ... requires that Y =  X T X  −1 X T (31.12) c  1999 by CRC Press LLC Doherty, J.F. “Channel Equalization as a Regularized Inverse Problem” Digital Signal Processing Handbook Ed. Vijay K. Madisetti and...