digital image processing in 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 ... the structuring element, the final thinning is produced. Figure 33 Illustration of thinning for line detection. (a) A binary original image; (b) After 10 iterations of thinning; (c) After ... Image Processing – Part II 61 Morphological Image Processing Problems (7) Write down the equations of combined Boolean operations to produce the following binary images by using the images...

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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 ... Imaging Modalities Are 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 ... Imaging 23 1.3.3 Imaging in the Ultraviolet Band 25 1.3.4 Imaging in the Visible and Infrared Bands 26 1.3.5 Imaging in the Microwave Band 32 1.3.6 Imaging in the Radio Band 34 1.3.7 Examples in...

... processing in a digital domain. Color is used also in later chapters as the basis for extracting features of interest in an image. Wavelets are the foundation for representing images in various ... single-headed arrows linking the processing modules. Although we do not discuss image display explicitly at this point, it is impor- tant to keep in mind that viewing the results of image processing can take ... specif- ically for image processing. Although large-scale image processing systems still are being sold for mas- sive imaging applications, such as processing of satellite images, the trend con- tinues toward...

... Adaptive clutter rejection in the joint angle-doppler domain can be incorporated into existing radar systems by digitizing the difference channel, or making relatively minor antenna modifications ... Doppler-domain (joint domain) localized processing (DDL/JDL) [12, 15, 16] and the PRI-staggered Doppler-decomposed processing (PRI-SDD) [17], which are well behaved and easy to implement. The DDL/JDL principle ... 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 ...

... filtering. Because of significant delay spread in the channel, array processing in mobile communications can be greatly leveraged by processing the signals in space and in time (STP) to minimize ... co-channel interference and inter symbol interference while maximizing SNR. See [35] for a review of channel equalization. We begin with the single-user case where we are only interested in demodulating ... reduced interference, and trunking efficiency. 68.4.2 Space-Time Filtering Space-time filtering (STF) applies space-time processing to maximize signal power and minimize intersymbol and co-channel interference....

... dominates numerical errors, this choice may not be critical in most signal processing applications. 66.2.2 Short Memory Windows for Time Varying Estimation Ultimately, weareinterestedin trackingsome ... exponentially faded window has some advantages over the moving rectangular window. The main advantage of a (short) rectangular window is in tracking sudden changes. Assuming stationar- ity within the effective ... to many updating methods is a fading factor. For cold start initialization (e.g., starting from nothing) at k = 0, initial convergence can often be sped up by ramping up the fading factor, e.g., α k =...

... error E{e 2 o (n)}. In most adaptive filtering applications, the desired signal, d(n), is available only during a “training phase” in which the filter parameters are adapted. At the conclusion of the training ... algorithms used in adaptive FIR filtering. For equation error meth- ods, we also examine the instrumental variables (IV) algorithm, as well as algorithms that constrain the parameters in the denominator ... needed to destabilize the resulting model. Nonetheless, under certain operating conditions, thiskind of instability can be shown not to occur, as described in the following. Property 2: [18] Consider...

... tech- nological advancements in digital circuit and VLSI design have spurred an increase in the range of new adaptive filtering applications in fields ranging from biomedical engineering to wireless com- munications. ... structure in Fig. 20.5 that has a lossless mapping T in its feedforward path and an arbitrary mapping F in its feedback path. The input/output signals of interest are denoted by{x, y, r, v,e}. In this ... adaptive scheme. In the remaining sections of this chapter, we discuss the combined issues of robustness and convergence from a deterministic standpoint. In particular, the following issues are...

... can draw the following two conclusions regarding this quantity: ã The misadjustment increases as the step size is increased. ã The misadjustment increases as the lter length is increased. Both results ... requires more information than is typically available in practice. Modeling criteria, such as Akaike’s Information Criterion [18] and minimum description length (MDL) [19] could be used in this situation. Choice ... this problem for i.i.d. input signals, see [20]. 19.5.3 Tracking Time-Varying Systems Since the LMS adaptive filter continually adjusts its coefficientsto approximately minimize the mean- squared...