Source code for colour.appearance.cam16

"""
CAM16 Colour Appearance Model
=============================

Define the *CAM16* colour appearance model objects:

-   :class:`colour.appearance.InductionFactors_CAM16`
-   :attr:`colour.VIEWING_CONDITIONS_CAM16`
-   :class:`colour.CAM_Specification_CAM16`
-   :func:`colour.XYZ_to_CAM16`
-   :func:`colour.CAM16_to_XYZ`

References
----------
-   :cite:`Li2017` : Li, C., Li, Z., Wang, Z., Xu, Y., Luo, M. R., Cui, G.,
    Melgosa, M., Brill, M. H., & Pointer, M. (2017). Comprehensive color
    solutions: CAM16, CAT16, and CAM16-UCS. Color Research & Application,
    42(6), 703-718. doi:10.1002/col.22131
"""

from __future__ import annotations

from collections import namedtuple
from dataclasses import astuple, dataclass, field

import numpy as np

from colour.adaptation import CAT_CAT16
from colour.algebra import spow, vecmul
from colour.appearance.ciecam02 import (
    VIEWING_CONDITIONS_CIECAM02,
    InductionFactors_CIECAM02,
    P,
    achromatic_response_forward,
    achromatic_response_inverse,
    brightness_correlate,
    chroma_correlate,
    colourfulness_correlate,
    degree_of_adaptation,
    eccentricity_factor,
    hue_angle,
    hue_quadrature,
    lightness_correlate,
    matrix_post_adaptation_non_linear_response_compression,
    opponent_colour_dimensions_forward,
    opponent_colour_dimensions_inverse,
    post_adaptation_non_linear_response_compression_forward,
    post_adaptation_non_linear_response_compression_inverse,
    saturation_correlate,
    temporary_magnitude_quantity_inverse,
    viewing_conditions_dependent_parameters,
)
from colour.hints import ArrayLike, NDArrayFloat
from colour.utilities import (
    CanonicalMapping,
    MixinDataclassArithmetic,
    as_float,
    as_float_array,
    from_range_100,
    from_range_degrees,
    has_only_nan,
    ones,
    to_domain_100,
    to_domain_degrees,
    tsplit,
)

__author__ = "Colour Developers"
__copyright__ = "Copyright 2013 Colour Developers"
__license__ = "BSD-3-Clause - https://opensource.org/licenses/BSD-3-Clause"
__maintainer__ = "Colour Developers"
__email__ = "colour-developers@colour-science.org"
__status__ = "Production"

__all__ = [
    "MATRIX_16",
    "MATRIX_INVERSE_16",
    "InductionFactors_CAM16",
    "VIEWING_CONDITIONS_CAM16",
    "CAM_Specification_CAM16",
    "XYZ_to_CAM16",
    "CAM16_to_XYZ",
]

MATRIX_16: NDArrayFloat = CAT_CAT16
"""Adaptation matrix :math:`M_{16}`."""

MATRIX_INVERSE_16: NDArrayFloat = np.linalg.inv(MATRIX_16)
"""Inverse adaptation matrix :math:`M^{-1}_{16}`."""


[docs] class InductionFactors_CAM16(namedtuple("InductionFactors_CAM16", ("F", "c", "N_c"))): """ *CAM16* colour appearance model induction factors. Parameters ---------- F Maximum degree of adaptation :math:`F`. c Exponential non-linearity :math:`c`. N_c Chromatic induction factor :math:`N_c`. Notes ----- - The *CAM16* colour appearance model induction factors are the same as *CIECAM02* colour appearance model. References ---------- :cite:`Li2017` """
VIEWING_CONDITIONS_CAM16: CanonicalMapping = CanonicalMapping( VIEWING_CONDITIONS_CIECAM02 ) VIEWING_CONDITIONS_CAM16.__doc__ = """ Reference *CAM16* colour appearance model viewing conditions. References ---------- :cite:`Li2017` """
[docs] @dataclass class CAM_Specification_CAM16(MixinDataclassArithmetic): """ Define the *CAM16* colour appearance model specification. Parameters ---------- J Correlate of *Lightness* :math:`J`. C Correlate of *chroma* :math:`C`. h *Hue* angle :math:`h` in degrees. s Correlate of *saturation* :math:`s`. Q Correlate of *brightness* :math:`Q`. M Correlate of *colourfulness* :math:`M`. H *Hue* :math:`h` quadrature :math:`H`. HC *Hue* :math:`h` composition :math:`H^C`. References ---------- :cite:`Li2017` """ J: float | NDArrayFloat | None = field(default_factory=lambda: None) C: float | NDArrayFloat | None = field(default_factory=lambda: None) h: float | NDArrayFloat | None = field(default_factory=lambda: None) s: float | NDArrayFloat | None = field(default_factory=lambda: None) Q: float | NDArrayFloat | None = field(default_factory=lambda: None) M: float | NDArrayFloat | None = field(default_factory=lambda: None) H: float | NDArrayFloat | None = field(default_factory=lambda: None) HC: float | NDArrayFloat | None = field(default_factory=lambda: None)
[docs] def XYZ_to_CAM16( XYZ: ArrayLike, XYZ_w: ArrayLike, L_A: ArrayLike, Y_b: ArrayLike, surround: ( InductionFactors_CIECAM02 | InductionFactors_CAM16 ) = VIEWING_CONDITIONS_CAM16["Average"], discount_illuminant: bool = False, compute_H: bool = True, ) -> CAM_Specification_CAM16: """ Compute the *CAM16* colour appearance model correlates from given *CIE XYZ* tristimulus values. Parameters ---------- XYZ *CIE XYZ* tristimulus values of test sample / stimulus. XYZ_w *CIE XYZ* tristimulus values of reference white. L_A Adapting field *luminance* :math:`L_A` in :math:`cd/m^2`, (often taken to be 20% of the luminance of a white object in the scene). Y_b Luminous factor of background :math:`Y_b` such as :math:`Y_b = 100 x L_b / L_w` where :math:`L_w` is the luminance of the light source and :math:`L_b` is the luminance of the background. For viewing images, :math:`Y_b` can be the average :math:`Y` value for the pixels in the entire image, or frequently, a :math:`Y` value of 20, approximate an :math:`L^*` of 50 is used. surround Surround viewing conditions induction factors. discount_illuminant Truth value indicating if the illuminant should be discounted. compute_H Whether to compute *Hue* :math:`h` quadrature :math:`H`. :math:`H` is rarely used, and expensive to compute. Returns ------- :class:`colour.CAM_Specification_CAM16` *CAM16* colour appearance model specification. Notes ----- +------------+-----------------------+---------------+ | **Domain** | **Scale - Reference** | **Scale - 1** | +============+=======================+===============+ | ``XYZ`` | [0, 100] | [0, 1] | +------------+-----------------------+---------------+ | ``XYZ_w`` | [0, 100] | [0, 1] | +------------+-----------------------+---------------+ +-------------------------------+-----------------------+---------------+ | **Range** | **Scale - Reference** | **Scale - 1** | +===============================+=======================+===============+ | ``CAM_Specification_CAM16.J`` | [0, 100] | [0, 1] | +-------------------------------+-----------------------+---------------+ | ``CAM_Specification_CAM16.C`` | [0, 100] | [0, 1] | +-------------------------------+-----------------------+---------------+ | ``CAM_Specification_CAM16.h`` | [0, 360] | [0, 1] | +-------------------------------+-----------------------+---------------+ | ``CAM_Specification_CAM16.s`` | [0, 100] | [0, 1] | +-------------------------------+-----------------------+---------------+ | ``CAM_Specification_CAM16.Q`` | [0, 100] | [0, 1] | +-------------------------------+-----------------------+---------------+ | ``CAM_Specification_CAM16.M`` | [0, 100] | [0, 1] | +-------------------------------+-----------------------+---------------+ | ``CAM_Specification_CAM16.H`` | [0, 400] | [0, 1] | +-------------------------------+-----------------------+---------------+ References ---------- :cite:`Li2017` Examples -------- >>> XYZ = np.array([19.01, 20.00, 21.78]) >>> XYZ_w = np.array([95.05, 100.00, 108.88]) >>> L_A = 318.31 >>> Y_b = 20.0 >>> surround = VIEWING_CONDITIONS_CAM16["Average"] >>> XYZ_to_CAM16(XYZ, XYZ_w, L_A, Y_b, surround) # doctest: +ELLIPSIS CAM_Specification_CAM16(J=41.7312079..., C=0.1033557..., \ h=217.0679597..., s=2.3450150..., Q=195.3717089..., M=0.1074367..., \ H=275.5949861..., HC=None) """ XYZ = to_domain_100(XYZ) XYZ_w = to_domain_100(XYZ_w) _X_w, Y_w, _Z_w = tsplit(XYZ_w) L_A = as_float_array(L_A) Y_b = as_float_array(Y_b) # Step 0 # Converting *CIE XYZ* tristimulus values to sharpened *RGB* values. RGB_w = vecmul(MATRIX_16, XYZ_w) # Computing degree of adaptation :math:`D`. D = ( np.clip(degree_of_adaptation(surround.F, L_A), 0, 1) if not discount_illuminant else ones(L_A.shape) ) n, F_L, N_bb, N_cb, z = viewing_conditions_dependent_parameters(Y_b, Y_w, L_A) D_RGB = D[..., None] * Y_w[..., None] / RGB_w + 1 - D[..., None] RGB_wc = D_RGB * RGB_w # Applying forward post-adaptation non-linear response compression. RGB_aw = post_adaptation_non_linear_response_compression_forward(RGB_wc, F_L) # Computing achromatic responses for the whitepoint. A_w = achromatic_response_forward(RGB_aw, N_bb) # Step 1 # Converting *CIE XYZ* tristimulus values to sharpened *RGB* values. RGB = vecmul(MATRIX_16, XYZ) # Step 2 RGB_c = D_RGB * RGB # Step 3 # Applying forward post-adaptation non-linear response compression. RGB_a = post_adaptation_non_linear_response_compression_forward(RGB_c, F_L) # Step 4 # Converting to preliminary cartesian coordinates. a, b = tsplit(opponent_colour_dimensions_forward(RGB_a)) # Computing the *hue* angle :math:`h`. h = hue_angle(a, b) # Step 5 # Computing eccentricity factor *e_t*. e_t = eccentricity_factor(h) # Computing hue :math:`h` quadrature :math:`H`. H = hue_quadrature(h) if compute_H else np.full(h.shape, np.nan) # TODO: Compute hue composition. # Step 6 # Computing achromatic responses for the stimulus. A = achromatic_response_forward(RGB_a, N_bb) # Step 7 # Computing the correlate of *Lightness* :math:`J`. J = lightness_correlate(A, A_w, surround.c, z) # Step 8 # Computing the correlate of *brightness* :math:`Q`. Q = brightness_correlate(surround.c, J, A_w, F_L) # Step 9 # Computing the correlate of *chroma* :math:`C`. C = chroma_correlate(J, n, surround.N_c, N_cb, e_t, a, b, RGB_a) # Computing the correlate of *colourfulness* :math:`M`. M = colourfulness_correlate(C, F_L) # Computing the correlate of *saturation* :math:`s`. s = saturation_correlate(M, Q) return CAM_Specification_CAM16( as_float(from_range_100(J)), as_float(from_range_100(C)), as_float(from_range_degrees(h)), as_float(from_range_100(s)), as_float(from_range_100(Q)), as_float(from_range_100(M)), as_float(from_range_degrees(H, 400)), None, )
[docs] def CAM16_to_XYZ( specification: CAM_Specification_CAM16, XYZ_w: ArrayLike, L_A: ArrayLike, Y_b: ArrayLike, surround: ( InductionFactors_CIECAM02 | InductionFactors_CAM16 ) = VIEWING_CONDITIONS_CAM16["Average"], discount_illuminant: bool = False, ) -> NDArrayFloat: """ Convert from *CAM16* specification to *CIE XYZ* tristimulus values. Parameters ---------- specification *CAM16* colour appearance model specification. Correlate of *Lightness* :math:`J`, correlate of *chroma* :math:`C` or correlate of *colourfulness* :math:`M` and *hue* angle :math:`h` in degrees must be specified, e.g. :math:`JCh` or :math:`JMh`. XYZ_w *CIE XYZ* tristimulus values of reference white. L_A Adapting field *luminance* :math:`L_A` in :math:`cd/m^2`, (often taken to be 20% of the luminance of a white object in the scene). Y_b Luminous factor of background :math:`Y_b` such as :math:`Y_b = 100 x L_b / L_w` where :math:`L_w` is the luminance of the light source and :math:`L_b` is the luminance of the background. For viewing images, :math:`Y_b` can be the average :math:`Y` value for the pixels in the entire image, or frequently, a :math:`Y` value of 20, approximate an :math:`L^*` of 50 is used. surround Surround viewing conditions. discount_illuminant Discount the illuminant. Returns ------- :class:`numpy.ndarray` *CIE XYZ* tristimulus values. Raises ------ ValueError If neither :math:`C` or :math:`M` correlates have been defined in the ``specification`` argument. Notes ----- +-------------------------------+-----------------------+---------------+ | **Domain** | **Scale - Reference** | **Scale - 1** | +===============================+=======================+===============+ | ``CAM_Specification_CAM16.J`` | [0, 100] | [0, 1] | +-------------------------------+-----------------------+---------------+ | ``CAM_Specification_CAM16.C`` | [0, 100] | [0, 1] | +-------------------------------+-----------------------+---------------+ | ``CAM_Specification_CAM16.h`` | [0, 360] | [0, 1] | +-------------------------------+-----------------------+---------------+ | ``CAM_Specification_CAM16.s`` | [0, 100] | [0, 1] | +-------------------------------+-----------------------+---------------+ | ``CAM_Specification_CAM16.Q`` | [0, 100] | [0, 1] | +-------------------------------+-----------------------+---------------+ | ``CAM_Specification_CAM16.M`` | [0, 100] | [0, 1] | +-------------------------------+-----------------------+---------------+ | ``CAM_Specification_CAM16.H`` | [0, 360] | [0, 1] | +-------------------------------+-----------------------+---------------+ | ``XYZ_w`` | [0, 100] | [0, 1] | +-------------------------------+-----------------------+---------------+ +-----------+-----------------------+---------------+ | **Range** | **Scale - Reference** | **Scale - 1** | +===========+=======================+===============+ | ``XYZ`` | [0, 100] | [0, 1] | +-----------+-----------------------+---------------+ References ---------- :cite:`Li2017` Examples -------- >>> specification = CAM_Specification_CAM16( ... J=41.731207905126638, C=0.103355738709070, h=217.067959767393010 ... ) >>> XYZ_w = np.array([95.05, 100.00, 108.88]) >>> L_A = 318.31 >>> Y_b = 20.0 >>> CAM16_to_XYZ(specification, XYZ_w, L_A, Y_b) # doctest: +ELLIPSIS array([ 19.01..., 20... , 21.78...]) """ J, C, h, _s, _Q, M, _H, _HC = astuple(specification) J = to_domain_100(J) C = to_domain_100(C) h = to_domain_degrees(h) M = to_domain_100(M) L_A = as_float_array(L_A) XYZ_w = to_domain_100(XYZ_w) _X_w, Y_w, _Z_w = tsplit(XYZ_w) # Step 0 # Converting *CIE XYZ* tristimulus values to sharpened *RGB* values. RGB_w = vecmul(MATRIX_16, XYZ_w) # Computing degree of adaptation :math:`D`. D = ( np.clip(degree_of_adaptation(surround.F, L_A), 0, 1) if not discount_illuminant else ones(L_A.shape) ) n, F_L, N_bb, N_cb, z = viewing_conditions_dependent_parameters(Y_b, Y_w, L_A) D_RGB = D[..., None] * Y_w[..., None] / RGB_w + 1 - D[..., None] RGB_wc = D_RGB * RGB_w # Applying forward post-adaptation non-linear response compression. RGB_aw = post_adaptation_non_linear_response_compression_forward(RGB_wc, F_L) # Computing achromatic responses for the whitepoint. A_w = achromatic_response_forward(RGB_aw, N_bb) # Step 1 if has_only_nan(C) and not has_only_nan(M): C = M / spow(F_L, 0.25) elif has_only_nan(C): raise ValueError( 'Either "C" or "M" correlate must be defined in ' 'the "CAM_Specification_CAM16" argument!' ) # Step 2 # Computing temporary magnitude quantity :math:`t`. t = temporary_magnitude_quantity_inverse(C, J, n) # Computing eccentricity factor *e_t*. e_t = eccentricity_factor(h) # Computing achromatic response :math:`A` for the stimulus. A = achromatic_response_inverse(A_w, J, surround.c, z) # Computing *P_1* to *P_3*. P_n = P(surround.N_c, N_cb, e_t, t, A, N_bb) _P_1, P_2, _P_3 = tsplit(P_n) # Step 3 # Computing opponent colour dimensions :math:`a` and :math:`b`. ab = opponent_colour_dimensions_inverse(P_n, h) a, b = tsplit(ab) * np.where(t == 0, 0, 1) # Step 4 # Applying post-adaptation non-linear response compression matrix. RGB_a = matrix_post_adaptation_non_linear_response_compression(P_2, a, b) # Step 5 # Applying inverse post-adaptation non-linear response compression. RGB_c = post_adaptation_non_linear_response_compression_inverse(RGB_a, F_L) # Step 6 RGB = RGB_c / D_RGB # Step 7 XYZ = vecmul(MATRIX_INVERSE_16, RGB) return from_range_100(XYZ)