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Calculates coordinates and colorimetric variables that represent reflectance spectra in either the CIEXYZ (1931), CIELAB (1971), or CIELCh (1971) colourspaces.
cie(vismodeldata, space = c("XYZ", "LAB", "LCh"))
(required) quantum catch color data. Can be either the result
from vismodel()
or independently calculated data (in the form of a
data frame with three columns representing trichromatic viewer).
(required) Choice between XYZ (default), LAB, or LCh colour models.
Object of class colspace
containing:
X, Y, Z
: Tristimulus values.
x, y, z
: Cartesian coordinates, when using space = XYZ
.
L, a, b
: Lightness, L
, and colour-opponent a
(redness-greenness) and
b
(yellowness-blueness) values, in a Cartesian coordinate space. Returned
when using space = LAB
.
L, a, b, C, h
: Lightness, L
, colour-opponent a
(redness-greenness)
and b
(yellowness-blueness) values, as well as chroma C
and hue-angle h
(degrees), the latter of which are cylindrical representations of a
and b
from the CIELAB model. Returned when using space = LCh
.
Smith T, Guild J. (1932) The CIE colorimetric standards and their use. Transactions of the Optical Society, 33(3), 73-134.
Westland S, Ripamonti C, Cheung V. (2012). Computational colour science using MATLAB. John Wiley & Sons.
Stockman, A., & Sharpe, L. T. (2000). Spectral sensitivities of the middle- and long-wavelength sensitive cones derived from measurements in observers of known genotype. Vision Research, 40, 1711-1737.
CIE (2006). Fundamental chromaticity diagram with physiological axes. Parts 1 and 2. Technical Report 170-1. Vienna: Central Bureau of the Commission Internationale de l Eclairage.
# NOT RUN {
data(flowers)
vis.flowers <- vismodel(flowers, visual = "cie10", illum = "D65", vonkries = TRUE, relative = FALSE)
flowers.ciexyz <- colspace(vis.flowers, space = "ciexyz")
flowers.cielab <- colspace(vis.flowers, space = "cielab")
flowers.cielch <- colspace(vis.flowers, space = "cielch")
# }
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