mirror of
https://github.com/wassname/scikit-image.git
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Merge pull request #230 from dharhas/dharhas-lab-color-space
xyz <--> lab color space conversions
This commit is contained in:
tonysyu
+179
-43
@@ -44,7 +44,9 @@ References
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from __future__ import division
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__all__ = ['convert_colorspace', 'rgb2hsv', 'hsv2rgb', 'rgb2xyz', 'xyz2rgb',
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'rgb2rgbcie', 'rgbcie2rgb', 'rgb2grey', 'rgb2gray', 'gray2rgb']
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'rgb2rgbcie', 'rgbcie2rgb', 'rgb2grey', 'rgb2gray', 'gray2rgb',
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'xyz2lab', 'lab2xyz', 'lab2rgb', 'rgb2lab'
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]
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__docformat__ = "restructuredtext en"
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@@ -81,11 +83,8 @@ def convert_colorspace(arr, fromspace, tospace):
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Examples
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--------
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>>> import os
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>>> from skimage import data_dir
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>>> from skimage.io import imread
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>>> lena = imread(os.path.join(data_dir, 'lena.png'))
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>>> from skimage import data
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>>> lena = data.lena()
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>>> lena_hsv = convert_colorspace(lena, 'RGB', 'HSV')
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"""
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fromdict = {'RGB': lambda im: im, 'HSV': hsv2rgb, 'RGB CIE': rgbcie2rgb,
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@@ -149,11 +148,9 @@ def rgb2hsv(rgb):
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Examples
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--------
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>>> import os
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>>> from skimage import data_dir
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>>> from skimage.io import imread
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>>> lena = imread(os.path.join(data_dir, 'lena.png'))
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>>> from skimage import color
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>>> from skimage import data
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>>> lena = data.lena()
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>>> lena_hsv = color.rgb2hsv(lena)
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"""
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arr = _prepare_colorarray(rgb)
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@@ -229,11 +226,8 @@ def hsv2rgb(hsv):
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Examples
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--------
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>>> import os
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>>> from skimage import data_dir
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>>> from skimage.io import imread
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>>> lena = imread(os.path.join(data_dir, 'lena.png'))
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>>> from skimage import data
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>>> lena = data.lena()
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>>> lena_hsv = rgb2hsv(lena)
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>>> lena_rgb = hsv2rgb(lena_hsv)
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"""
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@@ -291,6 +285,9 @@ grey_from_rgb = np.array([[0.2125, 0.7154, 0.0721],
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[0, 0, 0],
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[0, 0, 0]])
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# CIE LAB constants for Observer= 2A, Illuminant= D65
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lab_ref_white = np.array([0.95047, 1., 1.08883])
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#-------------------------------------------------------------
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# The conversion functions that make use of the matrices above
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#-------------------------------------------------------------
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@@ -351,14 +348,11 @@ def xyz2rgb(xyz):
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Examples
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--------
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>>> import os
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>>> from skimage import data_dir
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>>> from skimage.io import imread
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>>> from skimage import data
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>>> from skimage.color import rgb2xyz, xyz2rgb
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>>> lena = imread(os.path.join(data_dir, 'lena.png'))
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>>> lena = data.lena()
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>>> lena_xyz = rgb2xyz(lena)
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>>> lena_rgb = xyz2rgb(lena_hsv)
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>>> lena_rgb = xyz2rgb(lena_xyz)
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"""
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return _convert(rgb_from_xyz, xyz)
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@@ -392,11 +386,8 @@ def rgb2xyz(rgb):
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Examples
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--------
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>>> import os
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>>> from skimage import data_dir
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>>> from skimage.io import imread
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>>> lena = imread(os.path.join(data_dir, 'lena.png'))
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>>> from skimage import data
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>>> lena = data.lena()
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>>> lena_xyz = rgb2xyz(lena)
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"""
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return _convert(xyz_from_rgb, rgb)
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@@ -426,12 +417,9 @@ def rgb2rgbcie(rgb):
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Examples
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--------
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>>> import os
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>>> from skimage import data_dir
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>>> from skimage.io import imread
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>>> from skimage import data
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>>> from skimage.color import rgb2rgbcie
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>>> lena = imread(os.path.join(data_dir, 'lena.png'))
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>>> lena = data.lena()
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>>> lena_rgbcie = rgb2rgbcie(lena)
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"""
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return _convert(rgbcie_from_rgb, rgb)
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@@ -461,14 +449,11 @@ def rgbcie2rgb(rgbcie):
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Examples
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--------
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>>> import os
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>>> from skimage import data_dir
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>>> from skimage.io import imread
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>>> from skimage import data
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>>> from skimage.color import rgb2rgbcie, rgbcie2rgb
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>>> lena = imread(os.path.join(data_dir, 'lena.png'))
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>>> lena = data.lena()
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>>> lena_rgbcie = rgb2rgbcie(lena)
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>>> lena_rgb = rgbcie2rgb(lena_hsv)
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>>> lena_rgb = rgbcie2rgb(lena_rgbcie)
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"""
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return _convert(rgb_from_rgbcie, rgbcie)
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@@ -508,12 +493,9 @@ def rgb2grey(rgb):
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Examples
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--------
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>>> import os
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>>> from skimage import data_dir
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>>> from skimage.io import imread
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>>> from skimage.color import rgb2grey
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>>> lena = imread(os.path.join(data_dir, 'lena.png'))
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>>> from skimage import data
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>>> lena = data.lena()
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>>> lena_grey = rgb2grey(lena)
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"""
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if rgb.ndim == 2:
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@@ -548,3 +530,157 @@ def gray2rgb(image):
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M, N = image.shape
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return np.dstack((image, image, image))
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def xyz2lab(xyz):
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"""XYZ to CIE-LAB color space conversion.
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Parameters
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----------
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xyz : array_like
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The image in XYZ format, in a 3-D array of shape (.., .., 3).
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Returns
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-------
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out : ndarray
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The image in CIE-LAB format, in a 3-D array of shape (.., .., 3).
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Raises
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------
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ValueError
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If `xyz` is not a 3-D array of shape (.., .., 3).
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Notes
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-----
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Observer= 2A, Illuminant= D65
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CIE XYZ tristimulus values x_ref = 95.047, y_ref = 100., z_ref = 108.883
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References
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----------
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.. [1] http://www.easyrgb.com/index.php?X=MATH&H=07#text7
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.. [2] http://en.wikipedia.org/wiki/Lab_color_space
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Examples
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--------
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>>> from skimage import data
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>>> from skimage.color import rgb2xyz, xyz2lab
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>>> lena = data.lena()
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>>> lena_xyz = rgb2xyz(lena)
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>>> lena_lab = xyz2lab(lena_xyz)
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"""
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arr = _prepare_colorarray(xyz)
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# scale by CIE XYZ tristimulus values of the reference white point
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arr = arr / lab_ref_white
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# Nonlinear distortion and linear transformation
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mask = arr > 0.008856
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arr[mask] = np.power(arr[mask], 1. / 3.)
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arr[~mask] = 7.787 * arr[~mask] + 16. / 116.
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x, y, z = arr[:, :, 0], arr[:, :, 1], arr[:, :, 2]
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# Vector scaling
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L = (116. * y) - 16.
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a = 500.0 * (x - y)
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b = 200.0 * (y - z)
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return np.dstack([L, a, b])
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def lab2xyz(lab):
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"""CIE-LAB to XYZcolor space conversion.
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Parameters
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----------
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lab : array_like
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The image in lab format, in a 3-D array of shape (.., .., 3).
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Returns
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-------
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out : ndarray
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The image in XYZ format, in a 3-D array of shape (.., .., 3).
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Raises
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------
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ValueError
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If `lab` is not a 3-D array of shape (.., .., 3).
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Notes
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-----
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Observer= 2A, Illuminant= D65
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CIE XYZ tristimulus values x_ref = 95.047, y_ref = 100., z_ref = 108.883
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References
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----------
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.. [1] http://www.easyrgb.com/index.php?X=MATH&H=07#text7
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.. [2] http://en.wikipedia.org/wiki/Lab_color_space
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"""
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arr = _prepare_colorarray(lab).copy()
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L, a, b = arr[:, :, 0], arr[:, :, 1], arr[:, :, 2]
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y = (L + 16.) / 116.
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x = (a / 500.) + y
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z = y - (b / 200.)
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out = np.dstack([x, y, z])
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mask = out > 0.2068966
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out[mask] = np.power(out[mask], 3.)
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out[~mask] = (out[~mask] - 16.0 / 116.) / 7.787
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# rescale Observer= 2 deg, Illuminant= D65
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out *= lab_ref_white
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return out
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def rgb2lab(rgb):
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"""RGB to lab color space conversion.
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Parameters
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----------
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rgb : array_like
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The image in RGB format, in a 3-D array of shape (.., .., 3).
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Returns
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-------
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out : ndarray
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The image in Lab format, in a 3-D array of shape (.., .., 3).
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Raises
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------
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ValueError
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If `rgb` is not a 3-D array of shape (.., .., 3).
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Notes
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-----
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This function uses rgb2xyz and xyz2lab.
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"""
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return xyz2lab(rgb2xyz(rgb))
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def lab2rgb(lab):
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"""Lab to RGB color space conversion.
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Parameters
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----------
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rgb : array_like
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The image in Lab format, in a 3-D array of shape (.., .., 3).
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Returns
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-------
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out : ndarray
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The image in RGB format, in a 3-D array of shape (.., .., 3).
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Raises
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------
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ValueError
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If `lab` is not a 3-D array of shape (.., .., 3).
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Notes
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-----
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This function uses lab2xyz and xyz2rgb.
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"""
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return xyz2rgb(lab2xyz(lab))
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@@ -23,7 +23,9 @@ from skimage.color import (
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rgb2xyz, xyz2rgb,
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rgb2rgbcie, rgbcie2rgb,
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convert_colorspace,
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rgb2grey, gray2rgb
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rgb2grey, gray2rgb,
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xyz2lab, lab2xyz,
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lab2rgb, rgb2lab
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)
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from skimage import data_dir
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@@ -43,6 +45,19 @@ class TestColorconv(TestCase):
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colbars_point75 = colbars * 0.75
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colbars_point75_array = np.swapaxes(colbars_point75.reshape(3, 4, 2), 0, 2)
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xyz_array = np.array([[[0.4124, 0.21260, 0.01930]], # red
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[[0, 0, 0]], # black
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[[.9505, 1., 1.089]], # white
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[[.1805, .0722, .9505]], # blue
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[[.07719, .15438, .02573]], # green
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])
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lab_array = np.array([[[53.233, 80.109, 67.220]], # red
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[[0., 0., 0.]], # black
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[[100.0, 0.005, -0.010]], # white
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[[32.303, 79.197, -107.864]], # blue
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[[46.229, -51.7, 49.898]], # green
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])
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# RGB to HSV
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def test_rgb2hsv_conversion(self):
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rgb = img_as_float(self.img_rgb)[::16, ::16]
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@@ -149,6 +164,20 @@ class TestColorconv(TestCase):
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def test_rgb2grey_on_grey(self):
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rgb2grey(np.random.random((5, 5)))
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# test matrices for xyz2lab and lab2xyz generated using http://www.easyrgb.com/index.php?X=CALC
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# Note: easyrgb website displays xyz*100
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def test_xyz2lab(self):
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assert_array_almost_equal(xyz2lab(self.xyz_array),
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self.lab_array, decimal=3)
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def test_lab2xyz(self):
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assert_array_almost_equal(lab2xyz(self.lab_array),
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self.xyz_array, decimal=3)
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def test_lab_rgb_roundtrip(self):
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img_rgb = img_as_float(self.img_rgb)
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assert_array_almost_equal(lab2rgb(rgb2lab(img_rgb)), img_rgb)
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def test_gray2rgb():
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x = np.array([0, 0.5, 1])
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