Mode of access: World Wide Web.

System requirements: Adobe Acrobat reader.

Part of: Synthesis digital library of engineering and computer science.

Series from website.

Includes bibliographical references (p. 105-109).

1. Introduction -- 2. Light: the physical color stimulus -- Basic radiometric concepts -- The space of physical stimuli -- The set P of physical light stimuli -- Algebraic structure of the set P -- Embedding of P in a vector space A -- Metric on A -- Discrete representation of elements of A -- 3. The color vector space -- Introduction -- Properties of metamerism -- Extension of metameric properties to A -- Proofs of propositions and theorems of section 3.3 -- Definition and properties of the color vector space -- The mapping from A to C: computing tristimulus values -- Black space and the canonical decomposition of the stimulus space -- Change of primaries -- The visual subspace and general color spaces -- The CIE color spaces -- Physically realizable colors -- The cone of physically realizable colors -- Additive reproduction of colors -- Indentification of primaries -- New primaries specified in terms of existing primaries -- Matrix for transformation of tristimulus values specified -- Spectral densities of primaries specified -- Color matching functions of new primaries specified -- 4. Subspaces and decompositions of the human color space -- Introduction -- Luminance and associated decompositions of the color vector space -- Chromaticity classes -- Determination of tristimulus values from luminance and chromaticities -- Additive reproduction of colors revisited -- Decomposition of color space corresponding to certain color deficiencies.

5. Various color spaces, representations, and transformations -- Linear color space representations -- Digital camera color spaces -- Non-linear color coordinates -- Perceptually uniform spaces -- Device-dependent coordinates -- Transformation between color spaces -- 6. Signals and systems theory for still and time-varying color images -- Continuous-domain systems for color images -- Frequency response and Fourier transform -- Discrete-domain color images -- Color signals with all components on the same lattice -- Color signals with different components on different sampling structures -- Analysis of color mosaic displays -- 7. Concluding remarks -- A. Semigroups and groups -- B. Equivalence relations -- C. Vector spaces -- D. Lattices -- Bibliography -- Author's biography.

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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. 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.

Also available in print.

Title from PDF t.p. (viewed on November 4, 2009).