colour.difference.delta_E_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 (Annotated[_Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str], 100]) – CIE L*a*b* colourspace array 1.
Lab_2 (Annotated[_Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str], 100]) – 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 \(k_L=k_C=k_H=1\).

Returns:

Colour difference \(\Delta E_{00}\).

Return type:

numpy.ndarray

Notes

Domain	Scale - Reference	Scale - 1
`Lab_1`	100	1
`Lab_2`	100	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

[Mel13], [SWD05]

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)
1.6709303...
>>> delta_E_CIE2000(Lab_1, Lab_2, textiles=True)
0.8412338...

colour.difference.delta_E_CIE2000#

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