colour.difference.delta_E_CIE1994#
- colour.difference.delta_E_CIE1994(Lab_1: ArrayLike, Lab_2: ArrayLike, textiles: bool = False) NDArrayFloat [source]#
Return the difference \(\Delta E_{94}\) between two given CIE L*a*b* colourspace arrays using CIE 1994 recommendation.
- Parameters:
Lab_1 (ArrayLike) – CIE L*a*b* colourspace array 1.
Lab_2 (ArrayLike) – CIE L*a*b* colourspace array 2.
textiles (bool) – Textiles application specific parametric factors, \(k_L=2,\ k_C=k_H=1,\ k_1=0.048,\ k_2=0.014\) weights are used instead of \(k_L=k_C=k_H=1,\ k_1=0.045,\ k_2=0.015\).
- Returns:
Colour difference \(\Delta E_{94}\).
- Return type:
Notes
Domain
Scale - Reference
Scale - 1
Lab_1
L_1
: [0, 100]a_1
: [-100, 100]b_1
: [-100, 100]L_1
: [0, 1]a_1
: [-1, 1]b_1
: [-1, 1]Lab_2
L_2
: [0, 100]a_2
: [-100, 100]b_2
: [-100, 100]L_2
: [0, 1]a_2
: [-1, 1]b_2
: [-1, 1]CIE 1994 colour differences are not symmetrical: difference between
Lab_1
andLab_2
may not be the same as difference betweenLab_2
andLab_1
thus one colour must be understood to be the reference against which a sample colour is compared.
References
[Lin11]
Examples
>>> Lab_1 = np.array([48.99183622, -0.10561667, 400.65619925]) >>> Lab_2 = np.array([50.65907324, -0.11671910, 402.82235718]) >>> delta_E_CIE1994(Lab_1, Lab_2) 1.6711191... >>> delta_E_CIE1994(Lab_1, Lab_2, textiles=True) 0.8404677...