... Applications of Blind and Semi-Blind Signal
Processing 23
1.2.1 Biomedical SignalProcessing 24
1.2.2 Blind Separation of Electrocardiographic Signals of
Fetus and Mother 25
1.2.3 Enhancement and Decomposition ... HDTV, etc. As demand for high quality
and reliability in recording and visualization systems increases, signalprocessing has an
even 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...
... Introduction
Thischapterprovidesabriefintroductiontothetheoryofmorphologicalsignalprocessingandits
applicationstoimageanalysisandnonlinearfiltering.By“morphologicalsignalprocessing”wemean
abroadandcoherentcollectionoftheoreticalconcepts,mathematicaltoolsforsignalanalysis,non-
linearsignaloperators,designmethodologies,andapplicationssystemsthatarebasedonorrelated
tomathematicalmorphology(MM),aset-andlattice-theoreticmethodologyforimageanalysis.MM
aimsatquantitativelydescribingthegeometricalstructureofimageobjects.Itsmathematicalorigins
stemfromsettheory,latticealgebra,convexanalysis,andintegralandstochasticgeometry.Itwas
initiatedmainlybyMatheron[42]andSerra[58]inthe1960s.Someofitsearlysignaloperationsare
alsofoundintheworkofotherresearcherswhousedcellularautomataandBoolean/thresholdlogic
toanalyzebinaryimagedatainthe1950sand1960s,assurveyedin[49,54].MMhasformalized
theseearlieroperationsandhasalsoaddednumerousnewconceptsandimageoperations.Inthe
1970sitwasextendedtogray-levelimages[22,45,58,62].OriginallyMMwasappliedtoanalyzing
c
1999byCRCPressLLC
defined) ... operations of the Boolean type. For example, given a
sampled
1
binary imagesignal f[x] with values 1 for the image foreground and 0 for the background,
typical signal transformations involving a neighborhood ... make
morphological signalprocessingarigorous andefficientframework tostudyandsolve manyproblems
in image analysis and nonlinear filtering.
74.2 Morphological Operators for Sets and Signals
74.2.1 Boolean...
... discussed further in an example in Chapter 10.
1.6. Fusion in signalandimageprocessingand fusion in other fields
Fusion in signalandimageprocessing has specific features that need to be taken
into ... between information known beforehand and new information. Here, we
will be considering dynamic processes among others (particularly robotics), and it
seems important for us to include revision and ... 20
1.6. Fusion in signalandimageprocessingand fusion in other fields . . . . 22
1.7.Bibliography 23
Chapter 2. Fusion in SignalProcessing 25
Jean-Pierre L
E CADRE, Vincent NIMIER and Roger REYNAUD
2.1....
... Fundamental SignalandImageProcessing Concepts 1
1 Architecture of the Basic Physiologic Recorder 3
Jason Ng and Jeffrey J. Goldberger
2 Analog and Digital Signals 9
Jason Ng and Jeffrey ... 379
Indranil Sen-Gupta and Jason Ng
Index 391
xii Contents
vii
Preface
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 197
5.5.2 Standard Video Signals; Timing andSignal Forms 199
5.5.3 Color Video Signals 201
5.5.4 Cameras and Connectors 204
5.5.5 Further References 205
6 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 new
computer vision products. For example, ImageProcessing ... maximum
for x=1:cols %address all columns
for y=1:rows %address all rows
inverted(y,x)=maxi -image( y,x);
end
end
Code 1.7 Matlab function (invert.m) to invert an image
6 Feature Extraction andImage Processing
(a)...
... filtering
using filters of radius 2 and 4 pixels, respectively.
To My Parents
and Mariko and Parviz
2-D and 3-D
Image Reg istration
for Medical, Remote Sensing,
and Industrial Applications
A. Ardeshir ... the resampled sensed imageand the reference image. Image registration
makes it possible to compare information in reference and sensed images pixel by
pixel 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 constraint
refer 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 demixing
systems over 10 trials.
Figure 2-3. (a) and (b) are the two original signals, (c) and (d) are the convolutively mixed
signals, (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 Applications
S.Zagriatski, and M. E. Bialkowski 197
C.Tanriover, and B.Honary
87
SIGNAL PROCESSING FOR
TELECOMMUNICATIONS
AND MULTIMEDIA
edited ... 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 the
parameters for the HMM are found. The model parameter set for an HMM
with N states and M mixtures is
8
Chapter 1
model, and the gain difference, g, between training and enhancement
environment.
The...