-
-
Notifications
You must be signed in to change notification settings - Fork 274
Open
Milestone
Description
We are currently using pre-computed Optimal Colour Stimuli tables from MacAdam (1935) and they are not very precise, only account from Luminance domain [10, 95] with the negative side-effect of labelling a lot of Munsell Real colours outside the MacAdam limits:
import colour
xyY_r = []
for _HVC, xyY in colour.MUNSELL_COLOURS_REAL:
xyY_r.append(xyY * np.array([1.0, 1.0, 1.0 / 100.0]))
xyY_r = np.array(xyY_r)
iml = colour.is_within_macadam_limits(xyY_r, 'C')
print(len(xyY_r))
print(len(iml[iml == False]))
# 2734
# 829
We should improve this behaviour by implementing an analytical computation for Optimal Colour Stimuli.
References
- Francisco Martínez-Verdú, Esther Perales, Elisabet Chorro, Dolores de Fez, Valentín Viqueira, and Eduardo Gilabert, "Computation and visualization of the MacAdam limits for any lightness, hue angle, and light source," J. Opt. Soc. Am. A 24, 1501-1515 (2007)
- https://webserver2.tecgraf.puc-rio.br/~mgattass/fcg/Color/aic_1MacAdamLimits.pdf
- https://github.com/rodrimc/ColourGamut
- https://www.researchgate.net/publication/44673524_Fast_and_accurate_model_for_optimal_color_computation