spatstat (version 1.52-1)

Kovesi: Colour Sequences with Uniform Perceptual Contrast

Description

A collection of 41 different sequences of colours, each sequence having a uniform perceptual contrast over its whole range. These sequences make very good colour maps which avoid introducing artefacts when displaying image data.

Usage

data(Kovesi)

Format

A hyperframe with the following columns:

linear	Logical: whether the sequence is linear.
diverging	Logical: whether the sequence is diverging.
rainbow	Logical: whether the sequence is a rainbow.
cyclic	Logical: whether the sequence is cyclic.
isoluminant	Logical: whether the sequence is isoluminant.
ternary	Logical: whether the sequence is ternary.
colsig	Character: colour signature (see Details)
l1, l2	Numeric: lightness parameters
chro	Numeric: average chroma (percent)
n	Numeric: length of colour sequence
cycsh	Numeric: cyclic shift (percent)

Details

Kovesi (2014, 2015) presented a collection of colour sequences that have uniform perceptual contrast over their whole range.

The dataset Kovesi provides these data. It is a hyperframe with 41 rows, in which each row provides information about one colour sequence.

Additional information in each row specifies whether the colour sequence is ‘linear’, ‘diverging’, ‘rainbow’, ‘cyclic’, ‘isoluminant’ and/or ‘ternary’ as defined by Kovesi (2014, 2015).

The ‘colour signature’ is a string composed of letters representing the successive hues, using the following code:

r	red
g	green
b	blue
c	cyan
m	magenta
y	yellow
o	orange
v	violet
k	black
w	white

For example kryw is the sequence from black to red to yellow to white.

The column values contains the colour data themselves. The ith colour sequence is Kovesi$values[[i]], a character vector of length 256.

References

Kovesi, P. (2014) Website CET Uniform Perceptual Contrast Colour Maps www.peterkovesi.com/projects/colourmaps/

Kovesi, P. (2015) Designing colour maps with uniform perceptual contrast. Manuscript submitted for publication.

Examples

# NOT RUN {
  Kovesi
  LinearBMW <- Kovesi$values[[28]]
  plot(colourmap(LinearBMW, range=c(0,1)))

  ## The following would be suitable for spatstat.options(image.colfun)
  BMWfun <- function(n) { interp.colours(LinearBMW, n) }
# }