... corrections and image registration also are covered.Chapter 6: Color Image Processing. This chapter deals with pseudocolor andfull-color image processing. Color models applicable to digitalimage process-ing ... ImageProcessing Toolbox,also are available.Areas of ImageProcessing Covered in the BookEvery chapter in this book contains the pertinent MATLAB and IPT materialneeded to implement the image ... sense.” Digital image processing, as we have defined it, is used successfully in a broad range ofareas of exceptional social and economic value.Background on MATLAB and the Image Processing...
... with Images in MATLAB a) Image types and classesb) Read/write imagesc) Display images2. Basic Image Processing a) Image contrast and brightness enhancementb) Image arithmetic3. Block Processing ... with Images in MATLAB Image Types: Binary Images• In a binary image, each pixel assumes one of only two discrete values: 0 (off) and 1 (on).>> imshow(bwImg) Image ProcessingUsing MATLAB Copyrighted ... Bhd.Working with Images in MATLAB Image Types: Index Images• An indexed image consists of a data matrix, X, and a colormap matrix, map.>> imshow(indexImg, map) Image ProcessingUsing MATLAB Copyrighted...
... ‘ Using vectorization = %.3f\n ’ , tstop − tstart); 2.14 USINGMATLAB FOR PROCESSING SIGNALS We are now in a position to use MATLAB to process some signals. Once a signal is sampled (in digital ... ′ MyImage.bmp ′ ; [ImageMat cmap] = imread (FileName); if ( ˜ isempty (cmap) ) disp ( ′ This image has a colormap ′ ); end [ImageHeight ImageWidth NumColorPlanes] = size (ImageMat); ... CHAPTER 2 MATLAB FOR SIGNAL PROCESSING It is worth noting that DSP systems are often developed in MATLAB, and implemented on the target hardware using the C language. This is because MATLAB provides...
... Digital ImageProcessing – Part II 54 Morphological Image Processing (a)(c)(d)(b) Digital ImageProcessing – Part II 87 Image Segmentation (a) (b)(c)(a)(b) Digital Image ... compartments(a)(b) Digital ImageProcessing – Part II 13 Colour Image Processing (b) Figure 5 Illustration of intensity slicing and colour assignment. Digital ImageProcessing – Part II 10 Colour Image ... (a)(b)(c)(a)(b)(c) Digital ImageProcessing – Part II 59 Morphological Image Processing Figure 43 Example of morphological reconstruction.(a) A binary image of the blobs as the mask image; (b)...
... 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 ... Using a Single Sensor 472.3.2 Image Acquisition Using Sensor Strips 482.3.3 Image Acquisition Using Sensor Arrays 492.3.4 A Simple Image Formation Model 502.4 Image Sampling and Quantization...
... 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...
... for adaptive suppression, free from strong cluttercontamination. Available acquisition methods include the use of clutter -free range-cells for low PRFsystems, clutter -free Doppler bins for high ... 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 LLCSpace-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.c1999byCRCPressLLCFIGURE...
... VII European Signal Processing Conference,Edinburgh, Scotland, Sept. 13-16, 1994.[33] Porat, B. and Friedlander, B., Blind equalization of digital communication channels using higher order moments,IEEE ... multiusercommunications,IEEE Trans. on Signal Processing, Special Issue on Signal Processing forAdvanced Communications,45(1), Jan. 1997.[10] Ding, Z., Blind channel identification and equalization using spectral correlation ... IntroductionandMotivationThischapterreviewstheapplicationsofantennaarraysignalprocessingtomobilenetworks.Cellularnetworksarerapidlygrowingaroundtheworldandanumberofemergingtechnologiesareseentobecriticaltotheirimprovedeconomicsandperformance.Amongtheseistheuseofmultipleantennasandspatialsignalprocessingatthebasestation.ThistechnologyisreferredtoasSmartAntennasor,moreaccurately,asSpace-TimeProcessing(STP).STPreferstoprocessingtheantennaoutputsinbothspaceandtimetomaximizesignalquality.Acellulararchitectureisusedinanumberofmobile/portablecommunicationsapplications.Cellsizesmayrangefromlargemacrocells,whichservehighspeedmobiles,tosmallermicrocellsorverysmallpicocells,whicharedesignedforoutdoorandindoorapplications.Eachoftheseoffersdifferentchannelcharacteristicsand,therefore,posesdifferentchallengesforSTP.Likewise,differentservicedeliverygoalssuchasgradeofserviceandtypeofservice:voice,data,orvideo,alsoneedspecificSTPsolutions.STPprovidesthreeprocessingleverages.Thefirstisarraygain.Multipleantennascapturemoresignalenergy,whichcanbecombinedtoimprovethesignal-to-noiseratio(SNR).Nextisspatialdiversitytocombatspace-selectivefading.Finally,STPcanreduceco-channel,adjacentchannel,andinter-symbolinterference.Theorganizationofthischapterisasfollows.InSection68.2,wedescribethevectorchannelmodelforabasestationantennaarray.InSection68.3wediscussthealgorithmsforSTP.Section68.4outlinestheapplicationsofSTPincellularnetworks.Finally,weconcludewithasummaryinSection68.5.c1999byCRCPressLLCxi(t)...
... Some algorithms for eigensubspaceestimation, Digital Signal Processing, 5, 97–115, 1995.[36] Regalia, P.A. and Loubaton, P., Rational subspaceestimation using adaptivelossless filters,IEEETrans. ... 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 LLCWilliamson, 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,...