colorfulness: Quantify the colorfulness of an image.
In GastonMauroDiaz/caiman: Canopy Image Analysis

Description Usage Arguments Details Value See Also Examples

Quantify the colorfulness of a sRGB image using a bidimensional space form by the green/red and the blue/yellow axes of the CIE L*a*b* space, in other words, the lightness is excluded. In this bidimensional space, the algorithm creates a square with sides of 200 and centered in 0. Next, it compute how much area of this square is covered by the image pixels. The index is the percentage of cover.

colorfulness(x, mask = NULL, plot = FALSE, returnRaster = FALSE)

## S4 method for signature 'CanopyPhoto'
colorfulness(x, mask = NULL, plot = FALSE, returnRaster = FALSE)

`x`	`CanopyPhoto`. Is the image that you want to know how colorful is.
`mask`	BinImage. The default value `NULL` means that all the pixels will be taking into account in the computations. If you provide a BinImage, it must have the same extent and resolution of `x`. All pixels from the image covered by pixels of the mask with value `1` will be taking into account in the computations.
`plot`	logical. By default it is `FALSE`, if `TRUE` a plot will be printed. See Details.
`returnRaster`	logical. By default it is `FALSE`, if `TRUE` this method returns the raster that you can see when plot is `TRUE`. See Details.

When you request a plot with argument plot = TRUE, the colorfulness is returned but also a plot is sent to the active graphics Device. The plot shows the color of the image represented in a bidimensional space made by the axis a and b of the CIE L*a*b* space.

numeric or Raster.

normalize, outOfDR.

x <- loadPhoto()
x <- normalize(x, 0, 255)
z <- makeZimage(ncol(x), lensPolyCoef(c(0.6427, 0.0346, -0.024491)))
m <- doMask(z, alim = asAngle(c(0, 10)), zlim = asAngle(c(30, 40)))
m <- doMask(z)
colorfulness(x, m, TRUE)
r <- colorfulness(x, m, TRUE, TRUE)
plotRGB(r)