After this discussion I was able in the end to implement a function for add or remove saturation modifying the rgb primaries, it was simpler than was I thought.
raw4_func.py (3.8 KB)
This python script accepts a linear rec.2020 .tif (floating point) and it converts the file to srgb at end.
It requires opencv, numpy and math.
def rgb_primaries_saturation (img,sat_r,sat_g,sat_b,rx,ry,gx,gy,bx,by,wx,wy):
The function itself takes in input sat_r, sat_g, sat_b for the saturation of the rgb primaries, 1 is the neutral value, values higher than 1 will desaturate the color primaries and values lower than 1 will increase the saturation
rx,ry,gx,gy,bx,by,wx,wy are the xy coordinates of the working space
Basically the function does this
- finds new rgb xy coordinates with linear interpolation
#rx=0.708
#ry=0.292
#gx=0.170
#gy=0.797
#bx=0.131
#by=0.046
#wx=0.3127
#wy=0.3290#new red xy chromaticity coordinates
rxnew=sat_r*(rx-wx)+wx
rynew=wy+((rxnew-wx)*(ry-wy))/(rx-wx)#new green xy chromaticity coordinates
gxnew=sat_g*(gx-wx)+wx
gynew=wy+((gxnew-wx)*(gy-wy))/(gx-wx)#new blu xy chromaticity coordinates
bxnew=sat_b*(bx-wx)+wx
bynew=wy+((bxnew-wx)*(by-wy))/(bx-wx)
- calculate the rgb to xyz matrix from the old xy coordinates
- calculate the xyz to rgb matrix with the new rgb coordinates
- build the correction matrix “joining” these two matrices
For example with this parameters (increase red saturation, reduce blue saturation)
rgb_primaries_saturation(…,sat_r=0.5,sat_g=1,sat_b=2.5,…)
We get this correction matrix
[[ 7.45518286 2.96645120 2.54481714]
[-2.95987568 1.04150585 2.54481714]
[-2.95987568 5.70137613 1.29598757]]
Before
After the matrix
