... Applications of Blind and Semi-Blind Signal Processing 231.2.1 Biomedical SignalProcessing 241.2.2 Blind Separation of Electrocardiographic Signals ofFetus and Mother 251.2.3 Enhancement and Decomposition ... HDTV, etc. As demand for high quality and reliability in recording and visualization systems increases, signalprocessing has aneven more important role to play.Blind SignalProcessing (BSP) ... difficult and even impossible to treat be-cause we have (m + n) unknown source signals (n sources and m noise signals, see Fig.1.8).Various signalprocessing methods have been developed for noise...
... IntroductionThischapterprovidesabriefintroductiontothetheoryofmorphologicalsignalprocessinganditsapplicationstoimageanalysisandnonlinearfiltering.By“morphologicalsignalprocessing”wemeanabroadandcoherentcollectionoftheoreticalconcepts,mathematicaltoolsforsignalanalysis,non-linearsignaloperators,designmethodologies,andapplicationssystemsthatarebasedonorrelatedtomathematicalmorphology(MM),aset-andlattice-theoreticmethodologyforimageanalysis.MMaimsatquantitativelydescribingthegeometricalstructureofimageobjects.Itsmathematicaloriginsstemfromsettheory,latticealgebra,convexanalysis,andintegralandstochasticgeometry.ItwasinitiatedmainlybyMatheron[42]andSerra[58]inthe1960s.SomeofitsearlysignaloperationsarealsofoundintheworkofotherresearcherswhousedcellularautomataandBoolean/thresholdlogictoanalyzebinaryimagedatainthe1950sand1960s,assurveyedin[49,54].MMhasformalizedtheseearlieroperationsandhasalsoaddednumerousnewconceptsandimageoperations.Inthe1970sitwasextendedtogray-levelimages[22,45,58,62].OriginallyMMwasappliedtoanalyzingc1999byCRCPressLLCdefined) ... operations of the Boolean type. For example, given asampled1binary imagesignal f[x] with values 1 for the image foreground and 0 for the background,typical signal transformations involving a neighborhood ... makemorphological signalprocessingarigorous andefficientframework tostudyandsolve manyproblemsin image analysis and nonlinear filtering.74.2 Morphological Operators for Sets and Signals74.2.1 Boolean...
... discussed further in an example in Chapter 10.1.6. Fusion in signalandimageprocessingand fusion in other fieldsFusion in signalandimageprocessing has specific features that need to be takeninto ... between information known beforehand and new information. Here, wewill be considering dynamic processes among others (particularly robotics), and itseems important for us to include revision and ... 201.6. Fusion in signalandimageprocessingand fusion in other fields . . . . 221.7.Bibliography 23Chapter 2. Fusion in SignalProcessing 25Jean-Pierre LE CADRE, Vincent NIMIER and Roger REYNAUD2.1....
... Fundamental SignalandImageProcessing Concepts 1 1 Architecture of the Basic Physiologic Recorder 3Jason Ng and Jeffrey J. Goldberger 2 Analog and Digital Signals 9Jason Ng and Jeffrey ... 379Indranil Sen-Gupta and Jason NgIndex 391xii Contents viiPreface Signal processing is the means and methodology of handling, manipulating, and convert-ing signals for the purposes of recording, ... would the understanding of signalandimageprocessing be important for a clinician, nurse, or technician in cardiology? Electrocardiograms, for example, can be practically performed with a touch...
... handbook on imageprocessingfor scientiÞc and technical applications / Berne Jèahne.— 2nd ed.p. cm.Includes bibliographical references and index.ISBN 0-8493-1900-5 (alk. paper)1. Imageprocessing Digital ... Sensors 1975.5.2 Standard Video Signals; Timing andSignal Forms 1995.5.3 Color Video Signals 2015.5.4 Cameras and Connectors 2045.5.5 Further References 2056 Digitalization and Quantization ... example for a systematic error is a calibration error.With respect to image processing, we can conclude that it is important to under-stand all the processes that form the imageand to understand...
... text Image Processingand Computer Vision (Parker, 1996). A recent text Computer Vision and Image Processing (Umbaugh, 1998) takes an applications-oriented approach to computer vision and image processing, ... oriented, like ImageProcessingand Advanced Imaging.These provide more general articles, and are often a good source of information about newcomputer vision products. For example, ImageProcessing ... maximum for x=1:cols %address all columns for y=1:rows %address all rowsinverted(y,x)=maxi -image( y,x);endendCode 1.7 Matlab function (invert.m) to invert an image 6 Feature Extraction andImage Processing (a)...
... filteringusing filters of radius 2 and 4 pixels, respectively.To My Parents and Mariko and Parviz2-D and 3-D Image Reg istration for Medical, Remote Sensing, and Industrial ApplicationsA. Ardeshir ... the resampled sensed imageand the reference image. Image registrationmakes it possible to compare information in reference and sensed images pixel bypixel and determine image differences that ... (d)Fig. 1.1(a) A Landsat MSS image used as the reference image. (b) A Landsat TM image used as the sensed image. (c) Resampling of the sensed image to register the reference image. (d) Overlaying...
... manifold. For further information on derivation and implementation of this hard constraintrefer to [1] and references therein.The closed form analytical expressions for first and second order informa-tion ... algorithms for first and third order TITO FIR demixingsystems over 10 trials.Figure 2-3. (a) and (b) are the two original signals, (c) and (d) are the convolutively mixedsignals, (e) and (f) ... combi-nations,” Digital Signal Processing, vol. 6, no. 1, pp. 5–16, Jan. 1996.K. J. Pope and R. E. Bogner, “Blind signal separation II: Linear, convolutive combi-nations,” Digital Signal Processing, vol....
... Line Slot Array Antenna for IEEE 802.11 B/G WLAN ApplicationsS.Zagriatski, and M. E. Bialkowski 197C.Tanriover, and B.Honary87 SIGNAL PROCESSING FOR TELECOMMUNICATIONS AND MULTIMEDIAedited ... chapter. We use bold upper and low-ercase letters to show matrices and vectors, respectively in the time, frequency and domains, e.g., for matrices andfor vectors. Ma-trix and vector transpose, ... is applied and theparameters for the HMM are found. The model parameter set for an HMMwith N states and M mixtures is8Chapter 1model, and the gain difference, g, between training and enhancementenvironment.The...