Last chance! 50% off unlimited learning
Sale ends in
Creates an object of
class "im"
representing a two-dimensional pixel image
whose pixel values are colours.
rgbim(R, G, B, A, maxColorValue=255, autoscale=FALSE)
hsvim(H, S, V, A, autoscale=FALSE)
Pixel images (objects of class "im"
) or constants
giving the red, green, and blue components of a colour, respectively.
Optional. Pixel image or constant value giving the alpha (transparency) component of a colour.
Maximum colour channel value for R,G,B,A
.
Pixel images (objects of class "im"
) or constants
giving the hue, saturation, and value components of
a colour, respectively.
Logical. If TRUE
, input values are automatically rescaled
to fit the permitted range. RGB values are scaled to lie between
0 and maxColorValue
. HSV values are scaled to lie between 0
and 1.
These functions take three pixel images, with real or integer pixel values, and create a single pixel image whose pixel values are colours recognisable to R.
Some of the arguments may be constant numeric values, but at least one of the arguments must be a pixel image. The image arguments should be compatible (in array dimension and in spatial position).
rgbim
calls rgb
to compute the colours,
while hsvim
calls hsv
. See the help for the relevant
function for more information about the meaning of the colour
channels.
See colourtools
for additional colour tools.
# NOT RUN {
# }
# NOT RUN {
# create three images with values in [0,1]
X <- setcov(owin())
X <- eval.im(pmin(1,X))
M <- Window(X)
Y <- as.im(function(x,y){(x+1)/2}, W=M)
Z <- as.im(function(x,y){(y+1)/2}, W=M)
RGB <- rgbim(X, Y, Z, maxColorValue=1)
HSV <- hsvim(X, Y, Z)
plot(RGB, valuesAreColours=TRUE)
plot(HSV, valuesAreColours=TRUE)
# }
Run the code above in your browser using DataLab