The tool decomposes an RGB image into it’s channels in different colour spaces. sRGB (including linear RGB), HSL, HSV, HBW, XYZ, xyY, L*a*b*, LChab, L*u*v*, LCHuv, CMY and CMYK models are supported.
For each of those the program will load input image as an sRGB image, convert it to given colour space and then create an image which includes coordinates
An example image is included in data directory which can be used to
test the program:
cargo run -- -f --resize 256x256 --crop 200x200+28+28 \
-o out data/lenna.png
As a result, the tool generates handful of WebP images and saves them
in the out directory with names matching lenna-*.webp pattern.
Each of the image includes decomposition of the source image into
separate channels in given colour space.
For example:
Perhaps the most familiar decomposition showing how much red, green and blue is in each pixel of the image. RGB model is additive thus the result comes from adding all those colours.
HSL attempts to be more user friendly by introducing more natural hue, saturation and lightness controls. The model isn’t perceptually uniform though so changing only hue affects luminosity of the colour.
The image being quite uniform in hue of the colour leaves hue channel to have comparatively little variance leaving just the blue feather to pop.
L*u*v* colour space tries to be perceptually uniform. The decomposition demonstrates the L* channel corresponds to luminosity while u* and v* coordinates fall on the green-red and blue-yellow axes.
The L*C*h model makes the model easier to interpret by representing chromaticity with more familiar hue and chroma values.
CMY and CMYK colour models are subtractive. This is demonstrated by the channels being ‘inverses’ of the image. The less cyan the image has, the higher value in the cyan channel. Similarly for other channels.
Addition of black channel means that the more black is used the less of all the other channels is used (which is useful in printing of course).