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Dubois E. The Structure and Properties of Color Spaces and the Representation of Color Images

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Dubois E. The Structure and Properties of Color Spaces and the Representation of Color Images
Издательство Morgan & Claypool, 2010, -130 pp.
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 twodimensional
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.
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 for Still and Time-Varying Color Images
Concluding Remarks
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