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This lecture describes the author's approach to the representation
of color spaces and their use for color image processing. The
lecture starts with a precise formulation of the space of physical
stimuli (light). The model includes both continuous spectra and
monochromatic spectra in the form of Dirac deltas. The spectral
densities are considered to be functions of a continuous wavelength
variable. This leads into the formulation of color space as a
three-dimensional vector space, with all the associated structure.
The approach is to start with the axioms of color matching for
normal human viewers, often called Grassmann's laws, and developing
the resulting vector space formulation. However, once the essential
defining element of this vector space is identified, it can be
extended to other color spaces, perhaps for different creatures and
devices, and dimensions other than three. The CIE spaces are
presented as main examples of color spaces. Many properties of the
color space are examined. Once the vector space formulation is
established, various useful decompositions of the space can be
established. The first such decomposition is based on luminance, a
measure of the relative brightness of a color. This leads to a
direct-sum decomposition of color space where a two-dimensional
subspace identifies the chromatic attribute, and a third coordinate
provides the luminance. A different decomposition involving a
projective space of chromaticity classes is then presented.
Finally, it is shown how the three types of color deficiencies
present in some groups of humans leads to a direct-sum
decomposition of three one-dimensional subspaces that are
associated with the three types of cone photoreceptors in the human
retina. Next, a few specific linear and nonlinear color
representations are presented. The color spaces of two digital
cameras are also described. Then the issue of transformations
between different color spaces is addressed. Finally, these ideas
are applied to signal and system theory for color images. This is
done using a vector signal approach where a general linear system
is represented by a three-by-three system matrix. The formulation
is applied to both continuous and discrete space images, and
specific problems in color filter array sampling and displays are
presented for illustration. The book is mainly targeted to
researchers and graduate students in fields of signal processing
related to any aspect of color imaging.
This book constitutes the refereed proceedings of the 18th
International Conference on Advanced Information Systems
Engineering, CAiSE 2006, held in Luxembourg, in June 2006. The book
presents 33 revised full papers together with 3 keynote talks. The
papers are organized in topical sections on security, conceptual
modeling, queries, document conceptualization, service composition,
workflow, business modeling, configuration and separation, business
process modeling, agent orientation, and requirements
management.
This book constitutes the refereed proceedings of the 29th
International Conference on Advanced Information Systems
Engineering, CAiSE 2017, held in Essen, Germany, in June 2017. The
37 papers presented together with 3 keynote papers in this volume
were carefully reviewed and selected from 175 submissions. The
papers are organized in topical sections on information systems
architecture; business process alignment; user knowledge discovery;
business process performance; big data exploration; process
variability management; information systems transformation and
evolution; business process modeling readability; business process
adaption; data mining; process discovery; business process modeling
notation.
This lecture describes the author's approach to the representation
of color spaces and their use for color image processing. The
lecture starts with a precise formulation of the space of physical
stimuli (light). The model includes both continuous spectra and
monochromatic spectra in the form of Dirac deltas. The spectral
densities are considered to be functions of a continuous wavelength
variable. This leads into the formulation of color space as a
three-dimensional vector space, with all the associated structure.
The approach is to start with the axioms of color matching for
normal human viewers, often called Grassmann's laws, and developing
the resulting vector space formulation. However, once the essential
defining element of this vector space is identified, it can be
extended to other color spaces, perhaps for different creatures and
devices, and dimensions other than three. The CIE spaces are
presented as main examples of color spaces. Many properties of the
color space are examined. Once the vector space formulation is
established, various useful decompositions of the space can be
established. The first such decomposition is based on luminance, a
measure of the relative brightness of a color. This leads to a
direct-sum decomposition of color space where a two-dimensional
subspace identifies the chromatic attribute, and a third coordinate
provides the luminance. A different decomposition involving a
projective space of chromaticity classes is then presented.
Finally, it is shown how the three types of color deficiencies
present in some groups of humans leads to a direct-sum
decomposition of three one-dimensional subspaces that are
associated with the three types of cone photoreceptors in the human
retina. Next, a few specific linear and nonlinear color
representations are presented. The color spaces of two digital
cameras are also described. Then the issue of transformations
between \emph{different} color spaces is addressed. Finally, these
ideas are applied to signal and system theory for color images.
This is done using a vector signal approach where a general linear
system is represented by a three-by-three system matrix. The
formulation is applied to both continuous and discrete space
images, and specific problems in color filter array sampling and
displays are presented for illustration. The book is mainly
targeted to researchers and graduate students in fields of signal
processing related to any aspect of color imaging. Table of
Contents: Introduction / Light: The Physical Color Stimulus / The
Color Vector Space / Subspaces and Decompositions of the Human
Color Space / Various Color Spaces, Representations, and
Transformations / Signals and Systems Theory / Concluding Remarks
For more than six years, The Communications Handbook stood as the definitive, one-stop reference for the entire field. With new chapters and extensive revisions that reflect recent technological advances, the second edition is now poised to take its place on the desks of engineers, researchers, and students around the world.
From fundamental theory to state-of-the-art applications, The Communications Handbook covers more areas of specialty with greater depth that any other handbook available.
Telephony Communication Networks Optical Communications Satellite Communications Wireless Communications Source Compression Data Recording
Expertly written, skillfully presented, and masterfully compiled, The Communications Handbook provides a perfect balance of essential information, background material, technical details, and international telecommunications standards. Whether you design, implement, buy, or sell communications systems, components, or services, you'll find this to be the one resource you can turn to for fast, reliable, answers.
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