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# This function written in Ruby is not affiliated with the CIE (International Commission on Illumination), # and is released into the public domain. It is provided "as is" without any warranty, express or implied. # The classic CIE ΔE2000 implementation, which operates on two L*a*b* colors, and returns their difference. # "l" ranges from 0 to 100, while "a" and "b" are unbounded and commonly clamped to the range of -128 to 127. def ciede_2000(l_1, a_1, b_1, l_2, a_2, b_2) # Working in Ruby with the CIEDE2000 color-difference formula. # k_l, k_c, k_h are parametric factors to be adjusted according to # different viewing parameters such as textures, backgrounds... k_l = k_c = k_h = 1.0 n = (Math.sqrt(a_1 * a_1 + b_1 * b_1) + Math.sqrt(a_2 * a_2 + b_2 * b_2)) * 0.5 n = n * n * n * n * n * n * n # A factor involving chroma raised to the power of 7 designed to make # the influence of chroma on the total color difference more accurate. n = 1.0 + 0.5 * (1.0 - Math.sqrt(n / (n + 6103515625.0))) # Application of the chroma correction factor. c_1 = Math.sqrt(a_1 * a_1 * n * n + b_1 * b_1) c_2 = Math.sqrt(a_2 * a_2 * n * n + b_2 * b_2) # atan2 is preferred over atan because it accurately computes the angle of # a point (x, y) in all quadrants, handling the signs of both coordinates. h_1 = Math.atan2(b_1, a_1 * n) h_2 = Math.atan2(b_2, a_2 * n) h_1 += 2.0 * Math::PI if h_1 < 0.0 h_2 += 2.0 * Math::PI if h_2 < 0.0 n = (h_2 - h_1).abs # Cross-implementation consistent rounding. n = Math::PI if Math::PI - 1E-14 < n && n < Math::PI + 1E-14 # When the hue angles lie in different quadrants, the straightforward # average can produce a mean that incorrectly suggests a hue angle in # the wrong quadrant, the next lines handle this issue. h_m = (h_1 + h_2) * 0.5 h_d = (h_2 - h_1) * 0.5 if Math::PI < n h_d += Math::PI # 📜 Sharma’s formulation doesn’t use the next line, but the one after it, # and these two variants differ by ±0.0003 on the final color differences. h_m += Math::PI # h_m += h_m < Math::PI ? Math::PI : -Math::PI end p = 36.0 * h_m - 55.0 * Math::PI n = (c_1 + c_2) * 0.5 n = n * n * n * n * n * n * n # The hue rotation correction term is designed to account for the # non-linear behavior of hue differences in the blue region. r_t = -2.0 * Math.sqrt(n / (n + 6103515625.0)) \ * Math.sin(Math::PI / 3.0 * Math.exp(p * p / (-25.0 * Math::PI * Math::PI))) n = (l_1 + l_2) * 0.5 n = (n - 50.0) * (n - 50.0) # Lightness. l = (l_2 - l_1) / (k_l * (1.0 + 0.015 * n / Math.sqrt(20.0 + n))) # These coefficients adjust the impact of different harmonic # components on the hue difference calculation. t = 1.0 + 0.24 * Math.sin(2.0 * h_m + Math::PI * 0.5) \ + 0.32 * Math.sin(3.0 * h_m + 8.0 * Math::PI / 15.0) \ - 0.17 * Math.sin(h_m + Math::PI / 3.0) \ - 0.20 * Math.sin(4.0 * h_m + 3.0 * Math::PI / 20.0) n = c_1 + c_2 # Hue. h = 2.0 * Math.sqrt(c_1 * c_2) * Math.sin(h_d) / (k_h * (1.0 + 0.0075 * n * t)) # Chroma. c = (c_2 - c_1) / (k_c * (1.0 + 0.0225 * n)) # Returning the square root ensures that dE00 accurately reflects the # geometric distance in color space, which can range from 0 to around 185. Math.sqrt(l * l + h * h + c * c + c * h * r_t) end # GitHub Project : https://github.com/michel-leonard/ciede2000-color-matching # Online Tests : https://michel-leonard.github.io/ciede2000-color-matching # L1 = 65.7 a1 = 54.9 b1 = -2.4 # L2 = 66.9 a2 = 48.8 b2 = 2.4 # CIE ΔE00 = 3.1475316605 (Bruce Lindbloom, Netflix’s VMAF, ...) # CIE ΔE00 = 3.1475185150 (Gaurav Sharma, OpenJDK, ...) # Deviation between implementations ≈ 1.3e-5 # See the source code comments for easy switching between these two widely used ΔE*00 implementation variants.