color instability: additive and subtractive
The model and its equations for calibrated tools (every unit = 1,) in additive and subtractive synthesis processes. Notice that the equations for additive process are far simpler.
The subtractive process implies 8 colors from paper + 3 primaries, the additive process 4 opaque colors.
Calculations to obtain the same neutral grey (50% reflectance) in additive and subtractive. The list of numbers on the top are actual color measurements. In theory, it is possible to match 2 color samples from the different processes.
Of course, the parameters (u, v, w, and: x, y, z) that refer to the proportions of colors are different.
What happens if the system is wrongly calibrated?
On the left column, the unit has been varied between 0.5 and 1.8, as if the measurement had been badly made. We see that in both cases the color changes, becomes darker and gets some Chroma. What’s funny is that De-calibrating the additive and the subtractive processes produce opposite effects, see the CIELAB graphs below:
I didn’t expect that.
From the simulated data here, we see that the subtractive system is slightly more unstable than the additive one, but this is only half of the truth: when you think about all the inconsistencies possible with transparent colors, it gets even much more unstable. Opaque colors are more reliable when working with colorimetric data (it’s hard to reproduce anything twice with transparent colors without proper instruments such as a good printer for ex.)
When lines a too bold (too much paint or ink) the additive mixture turns reddish while the subtractive turns bluish, and vice-versa when lines are too thin. Image in sRGB gamma 2,4:
Top: additive / Down: subtractive
Left: too less paint or ink on the paper / Right: too much
Nothing’s perfect in this world :)
Now guess what?
The average 50/50% of the De-calibrated processes all produce a Chroma under 1!
means they are very-near complementary :)