pavo (version 2.9.0)

cie: CIE colour spaces

Description

Calculates coordinates and colorimetric variables that represent reflectance spectra in either the CIEXYZ (1931), CIELAB (1971), or CIELCh (1971) colourspaces.

Usage

cie(
  vismodeldata,
  space = c("XYZ", "LAB", "LCh"),
  visual = c("cie2", "cie10"),
  illum = c("D65", "bluesky", "forestshade")
)

Value

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.

Arguments

vismodeldata

(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).

space

(required) Choice between XYZ (default), LAB, or LCh colour models.

visual

the visual system used when estimating XYZ values, if vismodeldata are not the result of a call to vismodel() (otherwise the argument is ignored). Options are:

• a data frame such as one produced containing by sensmodel(), containing user-defined sensitivity data for the receptors involved in colour vision. The data frame must contain a 'wl' column with the range of wavelengths included, and the sensitivity for each other cone as a column.

• 'cie2': 2-degree colour matching functions for CIE models of human colour vision. Functions are linear transformations of the 2-degree cone fundamentals of Stockman & Sharpe (2000), as ratified by the CIE (2006).

• 'cie10': 10-degree colour matching functions for CIE models of human colour vision. Functions are linear transformations of the 10-degree cone fundamentals of Stockman & Sharpe (2000), as ratified by the CIE (2006).

illum

the illuminant used when estimating XYZ values, if vismodeldata are not the result of a call to vismodel() (otherwise the argument is ignored). Either a data frame containing a 'wl' column and the illuminant spectrum, or one of the built-in options:

• 'D65': standard daylight.

• 'bluesky' open blue sky.

• 'forestshade' forest shade.

Author

Thomas White

References

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.

Examples

# Load floral reflectance spectra
data(flowers)

# Estimate quantum catches, using the cie10-degree viewer matching function
vis.flowers <- vismodel(flowers, visual = "cie10", illum = "D65", vonkries = TRUE, relative = FALSE)

# Model floral spectra in the CIEXYZ space
flowers.ciexyz <- colspace(vis.flowers, space = "ciexyz")

# Model floral spectra in the CIELab space
flowers.cielab <- colspace(vis.flowers, space = "cielab")

# Model floral spectra in the CIELch space
flowers.cielch <- colspace(vis.flowers, space = "cielch")