... 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....
... 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)...
... 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...
... utilizing signalprocessing to improve
system performance and allow for a cost reduction. The issues considered
range from antenna design and channel equalisation through multi-rate
digital signalprocessing ... will be transformed into the log
spectral domain
SIGNAL PROCESSING FOR
TELECOMMUNICATIONS
AND MULTIMEDIA
SIGNAL PROCESSING FOR
TELECOMMUNICATIONS
AND MULTIMEDIA
edited by
Tadeusz A. Wysocki
University ... 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,...
... 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 ... (a) and (b) are the two original signals, (c) and (d) are the convolutively mixed
signals, (e) and (f) are the permuted separated results.
(2.18,2.19) for K = 401 frames of the two mixed signals. ... 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....