colour.difference.delta_E_CIE2000#
- colour.difference.delta_E_CIE2000(Lab_1: Domain100, Lab_2: Domain100, textiles: bool = False, *, additional_data: Literal[False] = False) NDArrayFloat[source]#
- colour.difference.delta_E_CIE2000(Lab_1: Domain100, Lab_2: Domain100, textiles: bool = False, *, additional_data: Literal[True]) DeltaE_Specification_CIE2000
Compute the colour difference \(\Delta E_{00}\) between two specified CIE L*a*b* colourspace arrays using the CIE 2000 recommendation.
- Parameters:
Lab_1 (Domain100) – CIE L*a*b* colourspace array 1.
Lab_2 (Domain100) – CIE L*a*b* colourspace array 2.
textiles (bool) – Textiles application specific parametric factors. \(k_L=2,\ k_C=k_H=1\) weights are used instead of \(k_L=k_C=k_H=1\).
additional_data (bool) – Whether to output additional data.
- Returns:
Colour difference \(\Delta E_{00}\).
- Return type:
numpy.ndarrayorDeltaE_Specification_CIE2000
Notes
Domain
Scale - Reference
Scale - 1
Lab_1100
1
Lab_2100
1
Parametric factors \(k_L=k_C=k_H=1\) weights under reference conditions:
Illumination: D65 source
Illuminance: 1000 lx
Observer: Normal colour vision
Background field: Uniform, neutral gray with \(L^*=50\)
Viewing mode: Object
Sample size: Greater than 4 degrees
Sample separation: Direct edge contact
Sample colour-difference magnitude: Lower than 5.0 \(\Delta E_{00}\)
Sample structure: Homogeneous (without texture)
References
Examples
>>> Lab_1 = np.array([48.99183622, -0.10561667, 400.65619925]) >>> Lab_2 = np.array([50.65907324, -0.11671910, 402.82235718]) >>> delta_E_CIE2000(Lab_1, Lab_2) np.float64(1.6709303...) >>> delta_E_CIE2000( ... Lab_1, ... Lab_2, ... additional_data=True, ... ) DeltaE_Specification_CIE2000(dE=np.float64(1.6709303...), dL=np.float64(1.6670667...), dC=np.float64(0.1135407...), dH=np.float64(0.0022239...)) >>> delta_E_CIE2000(Lab_1, Lab_2, textiles=True) np.float64(0.8412338...) >>> delta_E_CIE2000( ... Lab_1, ... Lab_2, ... textiles=True, ... additional_data=True, ... ) DeltaE_Specification_CIE2000(dE=np.float64(0.8412338...), dL=np.float64(0.8335333...), dC=np.float64(0.1135407...), dH=np.float64(0.0022239...))