Module: color¶

Stain to RGB color space conversion.

Notes

Stain combination matrices available in the color module and their respective colorspace:

• rgb_from_hed: Hematoxylin + Eosin + DAB
• rgb_from_hdx: Hematoxylin + DAB
• rgb_from_fgx: Feulgen + Light Green
• rgb_from_bex: Giemsa stain : Methyl Blue + Eosin
• rgb_from_rbd: FastRed + FastBlue + DAB
• rgb_from_gdx: Methyl Green + DAB
• rgb_from_hax: Hematoxylin + AEC
• rgb_from_bro: Blue matrix Anilline Blue + Red matrix Azocarmine + Orange matrix Orange-G
• rgb_from_bpx: Methyl Blue + Ponceau Fuchsin
• rgb_from_ahx: Alcian Blue + Hematoxylin
• rgb_from_hpx: Hematoxylin + PAS

References

Examples

>>> from skimage import data
>>> from skimage.color import (separate_stains, combine_stains,
...                            hdx_from_rgb, rgb_from_hdx)
>>> ihc = data.immunohistochemistry()
>>> ihc_hdx = separate_stains(ihc, hdx_from_rgb)
>>> ihc_rgb = combine_stains(ihc_hdx, rgb_from_hdx)

Convert an image array to a new color space.

Notes

Conversion occurs through the “central” RGB color space, i.e. conversion from XYZ to HSV is implemented as XYZ -> RGB -> HSV instead of directly.

Examples

>>> from skimage import data
>>> lena = data.lena()
>>> lena_hsv = convert_colorspace(lena, 'RGB', 'HSV')

Euclidean distance between two points in Lab color space

References

Color difference as given by the CIEDE 2000 standard.

CIEDE 2000 is a major revision of CIDE94. The perceptual calibration is largely based on experience with automotive paint on smooth surfaces.

Notes

CIEDE 2000 assumes parametric weighting factors for the lightness, chroma, and hue (kL, kC, kH respectively). These default to 1.

References

Color difference according to CIEDE 94 standard

Accommodates perceptual non-uniformities through the use of application specific scale factors (kH, kC, kL, k1, and k2).

Notes

deltaE_ciede94 is not symmetric with respect to lab1 and lab2. CIEDE94 defines the scales for the lightness, hue, and chroma in terms of the first color. Consequently, the first color should be regarded as the “reference” color.

kL, k1, k2 depend on the application and default to the values suggested for graphic arts

References

Color difference from the CMC l:c standard.

This color difference was developed by the Colour Measurement Committee (CMC) of the Society of Dyers and Colourists (United Kingdom). It is intended for use in the textile industry.

The scale factors kL, kC set the weight given to differences in lightness and chroma relative to differences in hue. The usual values are kL=2, kC=1 for “acceptability” and kL=1, kC=1 for “imperceptibility”. Colors with dE > 1 are “different” for the given scale factors.

Notes

deltaE_cmc the defines the scales for the lightness, hue, and chroma in terms of the first color. Consequently deltaE_cmc(lab1, lab2) != deltaE_cmc(lab2, lab1)

References

Create an RGB representation of a gray-level image.

Make an educated guess about whether an image has a channels dimension.

Haematoxylin-Eosin-DAB (HED) to RGB color space conversion.

References

Examples

>>> from skimage import data
>>> from skimage.color import rgb2hed, hed2rgb
>>> ihc = data.immunohistochemistry()
>>> ihc_hed = rgb2hed(ihc)
>>> ihc_rgb = hed2rgb(ihc_hed)

HSV to RGB color space conversion.

Notes

The conversion assumes an input data range of [0, 1] for all color components.

Conversion between RGB and HSV color spaces results in some loss of precision, due to integer arithmetic and rounding [R43].

References

Examples

>>> from skimage import data
>>> lena = data.lena()
>>> lena_hsv = rgb2hsv(lena)
>>> lena_rgb = hsv2rgb(lena_hsv)

CIE-LAB to CIE-LCH color space conversion.

LCH is the cylindrical representation of the LAB (Cartesian) colorspace

Notes

The Hue is expressed as an angle between (0, 2*pi)

Examples

>>> from skimage import data
>>> from skimage.color import rgb2lab, lab2lch
>>> lena = data.lena()
>>> lena_lab = rgb2lab(lena)
>>> lena_lch = lab2lch(lena_lab)

Lab to RGB color space conversion.

Notes

This function uses lab2xyz and xyz2rgb.

CIE-LAB to XYZcolor space conversion.

Notes

Observer = 2A, Illuminant = D65 CIE XYZ tristimulus values x_ref = 95.047, y_ref = 100., z_ref = 108.883

References

Return an RGB image where color-coded labels are painted over the image.

CIE-LCH to CIE-LAB color space conversion.

LCH is the cylindrical representation of the LAB (Cartesian) colorspace

Examples

>>> from skimage import data
>>> from skimage.color import rgb2lab, lch2lab
>>> lena = data.lena()
>>> lena_lab = rgb2lab(lena)
>>> lena_lch = lab2lch(lena_lab)
>>> lena_lab2 = lch2lab(lena_lch)

Luv to RGB color space conversion.

Notes

This function uses luv2xyz and xyz2rgb.

CIE-Luv to XYZ color space conversion.

Notes

XYZ conversion weights use Observer = 2A. Reference whitepoint for D65 Illuminant, with XYZ tristimulus values of (95.047, 100., 108.883).

References

Compute luminance of an RGB image.

Notes

The weights used in this conversion are calibrated for contemporary CRT phosphors:

Y = 0.2125 R + 0.7154 G + 0.0721 B

If there is an alpha channel present, it is ignored.

References

Examples

>>> from skimage.color import rgb2gray
>>> from skimage import data
>>> lena = data.lena()
>>> lena_gray = rgb2gray(lena)

Compute luminance of an RGB image.

Notes

The weights used in this conversion are calibrated for contemporary CRT phosphors:

Y = 0.2125 R + 0.7154 G + 0.0721 B

If there is an alpha channel present, it is ignored.

References

Examples

>>> from skimage.color import rgb2gray
>>> from skimage import data
>>> lena = data.lena()
>>> lena_gray = rgb2gray(lena)

RGB to Haematoxylin-Eosin-DAB (HED) color space conversion.

References

Examples

>>> from skimage import data
>>> from skimage.color import rgb2hed
>>> ihc = data.immunohistochemistry()
>>> ihc_hed = rgb2hed(ihc)

RGB to HSV color space conversion.

Notes

The conversion assumes an input data range of [0, 1] for all color components.

Conversion between RGB and HSV color spaces results in some loss of precision, due to integer arithmetic and rounding [R51].

References

Examples

>>> from skimage import color
>>> from skimage import data
>>> lena = data.lena()
>>> lena_hsv = color.rgb2hsv(lena)

RGB to lab color space conversion.

Notes

This function uses rgb2xyz and xyz2lab.

RGB to CIE-Luv color space conversion.

Notes

This function uses rgb2xyz and xyz2luv.

RGB to RGB CIE color space conversion.

References

Examples

>>> from skimage import data
>>> from skimage.color import rgb2rgbcie
>>> lena = data.lena()
>>> lena_rgbcie = rgb2rgbcie(lena)

RGB to XYZ color space conversion.

Notes

The CIE XYZ color space is derived from the CIE RGB color space. Note however that this function converts from sRGB.

References

Examples

>>> from skimage import data
>>> lena = data.lena()
>>> lena_xyz = rgb2xyz(lena)

RGB CIE to RGB color space conversion.

References

Examples

>>> from skimage import data
>>> from skimage.color import rgb2rgbcie, rgbcie2rgb
>>> lena = data.lena()
>>> lena_rgbcie = rgb2rgbcie(lena)
>>> lena_rgb = rgbcie2rgb(lena_rgbcie)

RGB to stain color space conversion.

Notes

Stain separation matrices available in the color module and their respective colorspace:

• hed_from_rgb: Hematoxylin + Eosin + DAB
• hdx_from_rgb: Hematoxylin + DAB
• fgx_from_rgb: Feulgen + Light Green
• bex_from_rgb: Giemsa stain : Methyl Blue + Eosin
• rbd_from_rgb: FastRed + FastBlue + DAB
• gdx_from_rgb: Methyl Green + DAB
• hax_from_rgb: Hematoxylin + AEC
• bro_from_rgb: Blue matrix Anilline Blue + Red matrix Azocarmine + Orange matrix Orange-G
• bpx_from_rgb: Methyl Blue + Ponceau Fuchsin
• ahx_from_rgb: Alcian Blue + Hematoxylin
• hpx_from_rgb: Hematoxylin + PAS

References

Examples

>>> from skimage import data
>>> from skimage.color import separate_stains, hdx_from_rgb
>>> ihc = data.immunohistochemistry()
>>> ihc_hdx = separate_stains(ihc, hdx_from_rgb)

XYZ to CIE-LAB color space conversion.

Notes

Observer= 2A, Illuminant= D65 CIE XYZ tristimulus values x_ref = 95.047, y_ref = 100., z_ref = 108.883

References

Examples

>>> from skimage import data
>>> from skimage.color import rgb2xyz, xyz2lab
>>> lena = data.lena()
>>> lena_xyz = rgb2xyz(lena)
>>> lena_lab = xyz2lab(lena_xyz)

XYZ to CIE-Luv color space conversion.

Notes

XYZ conversion weights use Observer = 2A. Reference whitepoint for D65 Illuminant, with XYZ tristimulus values of (95.047, 100., 108.883).

References

Examples

>>> from skimage import data
>>> from skimage.color import rgb2xyz, xyz2luv
>>> lena = data.lena()
>>> lena_xyz = rgb2xyz(lena)
>>> lena_luv = xyz2luv(lena_xyz)

XYZ to RGB color space conversion.

Notes

The CIE XYZ color space is derived from the CIE RGB color space. Note however that this function converts to sRGB.

References

Examples

>>> from skimage import data
>>> from skimage.color import rgb2xyz, xyz2rgb
>>> lena = data.lena()
>>> lena_xyz = rgb2xyz(lena)
>>> lena_rgb = xyz2rgb(lena_xyz)