... Recognition 364Nonlinear Audio Processing 368Chapter 23. Image Formation and Display 373 Digital Image Structure 373Cameras and Eyes 376Television Video Signals 384Other Image Acquisition and Display ... Filter Comparison 343APPLICATIONSChapter 22. Audio Processing 351Chapter 23. Image Formation and Display 373Chapter 24. Linear ImageProcessing 397Chapter 25. Special Imaging Techniques ... The Scientist and Engineer's Guide to Digital Signal Processing Second Edition xiiPrefaceGoals and Strategies of this BookThe technical world is changing...
... xix1Introduction 151.1 What Is DigitalImage Processing? 151.2 The Origins of DigitalImageProcessing 171.3 Examples of Fields that Use DigitalImageProcessing 211.3.1 Gamma-Ray Imaging ... Used 341.4 Fundamental Steps in DigitalImageProcessing 391.5 Components of an ImageProcessing System 42Summary 44References and Further Reading 452 Digital Image Fundamentals 342.1 Elements ... Representing Digital Images 542.4.3 Spatial and Gray-Level Resolution 572.4.4 Aliasing and Moiré Patterns 622.4.5 Zooming and Shrinking Digital Images 64viiGONZFM-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 progressin the field of digitalimage ... overlap be-tween imageprocessing 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 imageprocessing encompasses ... involve digital images, they are not con-sidered digitalimageprocessing results in the context of our definition becausecomputers were not involved in their creation.Thus, the history of digital...
... 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...
... 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]...
... 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...
... 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,...
... S.,Adaptive Filter Theory, 3rd ed., Prentice-Hall, Englewood Cliffs, NJ, 1996.[2] Proakis, J.G., Rader, C.M., Ling, F., and Nikias, C.L.,Advanced Digital Signal Processing ,Macmillan Publishing, ... S.D.,Adaptive Signal Processing , Prentice-Hall, Englewood Cliffs, NJ,1985.[4] Sayed, A.H. and Kailath, T., A state-space approach to adaptive RLS filtering,IEEE Signal Processing Magazine, ... 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...
... 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...
... 1960 McGraw-Hill edition) , 1987.[4] Davenport, W. and Root, W.,An Introduction to the Theory of Random Signals and Noise,IEEE Press, New York (reprint of 1958 McGraw-Hill edition) , 1987.[5] ... 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]...
... using solitons, inProc. IEEE Workshop onNonlinear Signal and Image Processing, vol. I, 150–153, 1995.[14] Singer, A.C., Signal Processing and Communication with Solitons, Ph.D. thesis, MassachusettsInstitute ... loop configuration.c1999 by CRC Press LLC Singer, A.C. “Signal Processing and Communication with Solitons” Digital Signal Processing HandbookEd. Vijay K. Madisetti and Douglas B. WilliamsBoca ... can beFIGURE 75.3: Two-soliton signal processing by a soliton system.viewed as special-purpose signal processors that are naturally suited to such signal processing tasks assignal separation...
... algorithm is that instantaneous throughput may be high due to the block -processing required.References[1] Proakis, J., Digital Communications,2nd ed., McGraw-Hill, New York, 1989.[2] Hatzinakos, ... algorithm for stable decision-feedback filtering,IEEE Trans. Circuits Syst. II: Analog and Digital Signal Processing, 40 CAS-II, Jan. 1993.c1999 by CRC Press LLC pulse shaping filter, the modulator, ... by CRC Press LLC Doherty, J.F. “Channel Equalization as a Regularized Inverse Problem” Digital Signal Processing HandbookEd. Vijay K. Madisetti and Douglas B. WilliamsBoca Raton: CRC Press...
... Speech Processing as an Inverse Problem” Digital Signal Processing HandbookEd. Vijay K. Madisetti and Douglas B. WilliamsBoca Raton: CRC Press LLC, 1999c1999byCRCPressLLC 27Robust Speech Processing ... issmall and has a negligible contribution to the cepstral distance.27.4 Robust Speech Processing Robust speech processing attempts to maintain the performance of speaker and speech recognitionsystem ... recursion can be used tosolve for a [3].27.3 Template-Based Speech Processing The template-based matching algorithms for speech processing are generally conducted using thesimilarity of the vocal...