提问人：Gabi 提问时间：10/12/2023 最后编辑：SeonGabi 更新时间：10/13/2023 访问量：70
将光谱转换为颜色 （Python）
Convert spectrum to Color (Python)
问：
我开发了一个代码来将反射光谱转换为具有 LAB 值的颜色：
import numpy as np
from colour import SpectralDistribution, XYZ_to_Lab, sd_to_XYZ
# Input the given data
wavelengths = np.arange(440, 1821, 20)
reflectance = ynp.array([0.02033, 0.0231, 0.00721, 0.00116, 0.00797, 0.0289, 0.05816, 0.08086, 0.08994, 0.05639, 0.03445, 0.03571, 0.09977, 0.22134, 0.26598, 0.27834, 0.2801, 0.28464, 0.28439, 0.27859, 0.26321, 0.2569, 0.25816, 0.2506, 0.24, 0.23622, 0.22916, 0.21983, 0.21327, 0.20822, 0.20621, 0.20368, 0.20444, 0.20696, 0.2115, 0.21529, 0.21831, 0.22008, 0.21932, 0.2168, 0.19738, 0.18099, 0.17191, 0.16409, 0.17645, 0.18906, 0.19107, 0.18981, 0.18275, 0.16838, 0.15324, 0.13256, 0.08666, 0.04555, 0.03143, 0.02966, 0.03269, 0.04051, 0.05211, 0.06447, 0.07808, 0.08767, 0.09599, 0.10255, 0.10709, 0.10911, 0.10431, 0.08868, 0.06068, 0.05539])
# Calculate the tristimulus values from the spectral data
sd = SpectralDistribution(reflectance, wavelengths)
xyz = sd_to_XYZ(sd)
# Convert the XYZ values to LAB
lab = XYZ_to_Lab(xyz/100)
# Print the resulting LAB values
print("The resulting LAB values:", lab)
到目前为止，我的代码运行良好，从我尝试的数据集中，我收到了我预期的颜色。
但是现在有一个数据集给了我褐色的色调，而不是红色的东西（参见上面的输入值）：LAB = [ 26.01444853 15.31231523 21.21644098]
我怀疑错误可能是我使用的其他数据集是由我获取它们的论文的作者标准化的。
所以我也尝试用这个公式来规范我的值：(X-min(X))/(max(X)-min(X))
但我的结果是，这是一种更明亮但仍然呈褐色的色调。[ 47.43 23.55 33.01]
你知道我还能做什么吗？还有其他公式如何标准化值吗？或者你认为错误来自我的代码？
举个例子，这是我用代码成功完成的其他数据集之一（颜色完全符合我的预期）：
wavelengths = np.arange(440, 801, 5)
np.array([0.03376, 0.07618, 0.12939, 0.14376, 0.15309, 0.15235, 0.14153, 0.1336, 0.12566, 0.11916, 0.10835, 0.10185, 0.09104, 0.08814, 0.08596, 0.08306, 0.08088, 0.07942, 0.07939, 0.08009, 0.07935, 0.07645, 0.07211, 0.07137, 0.07062, 0.06772, 0.06339, 0.06264, 0.06262, 0.06548, 0.06617, 0.06543, 0.06541, 0.06826, 0.07903, 0.09052, 0.1092, 0.14442, 0.17318, 0.20984, 0.23931, 0.26375, 0.28675, 0.3119, 0.3277, 0.34207, 0.355, 0.36504, 0.37797, 0.39378, 0.41677, 0.43185, 0.44406, 0.4577, 0.47063, 0.47996, 0.48815, 0.49493, 0.49853, 0.50531, 0.50936, 0.51251, 0.51295, 0.51292, 0.5061, 0.49792, 0.49201, 0.48383, 0.46704, 0.46883, 0.47062, 0.46425, 0.4597, 0.46964, 0.46011, 0.45193, 0.45009, 0.44146, 0.43192, 0.42374, 0.41647])
Result: [ 42.86401144 43.94910661 8.95057537]
答：
0赞
Kel Solaar
10/13/2023
#1
由于要计算样品的反射率，因此需要将光源传递到光谱到三刺激的转换程序，例如：colour.SDS_ILLUMINANTS["D65"]
import numpy as np
import colour.plotting
from colour import SpectralDistribution, XYZ_to_Lab, sd_to_XYZ
# Input the given data
wavelengths = np.arange(440, 1821, 20)
reflectance = np.array([0.02033, 0.0231, 0.00721, 0.00116, 0.00797, 0.0289, 0.05816, 0.08086, 0.08994, 0.05639, 0.03445, 0.03571, 0.09977, 0.22134, 0.26598, 0.27834, 0.2801, 0.28464, 0.28439, 0.27859, 0.26321, 0.2569, 0.25816, 0.2506, 0.24, 0.23622, 0.22916, 0.21983, 0.21327, 0.20822, 0.20621, 0.20368, 0.20444, 0.20696, 0.2115, 0.21529, 0.21831, 0.22008, 0.21932, 0.2168, 0.19738, 0.18099, 0.17191, 0.16409, 0.17645, 0.18906, 0.19107, 0.18981, 0.18275, 0.16838, 0.15324, 0.13256, 0.08666, 0.04555, 0.03143, 0.02966, 0.03269, 0.04051, 0.05211, 0.06447, 0.07808, 0.08767, 0.09599, 0.10255, 0.10709, 0.10911, 0.10431, 0.08868, 0.06068, 0.05539])
# Calculate the tristimulus values from the spectral data
sd = SpectralDistribution(reflectance, wavelengths)
colour.plotting.plot_single_sd(sd)
xyz = sd_to_XYZ(sd, illuminant=colour.SDS_ILLUMINANTS["D65"]) / 100
colour.plotting.plot_single_colour_swatch(colour.XYZ_to_sRGB(xyz))
# Convert the XYZ values to LAB
lab = XYZ_to_Lab(xyz)
# Print the resulting LAB values
print("The resulting LAB values:", lab)
查看反射率曲线，在红色灵敏度区域的 10-20% 之间：
这个sRGB渲染对我来说是正确的：
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