color for image processing - Center for Machine Perception

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COLOR FOR IMAGE PROCESSING
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Václav Hlaváč, Jan Kybic
Czech Technical University, Faculty of Electrical Engineering
Center for Machine Perception, Prague, Czech Republic
[email protected]
http://cmp.felk.cvut.cz/∼hlavac
Courtesy to K. Ikeuchi, T. Darrell for inspiration and some pictures found in their teaching
presentations.
COLOR IN SEVERAL DOMAINS
Physics.
Human vision, physiology.
Psychophysics, perception.
Computer vision.
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Painting, photography, movies.
COLOR IN COMPUTER VISION
Color in image formation, reflection physics.
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Color for segmentation.
LIGHT AND COLOR
Light = electromagnetic radiation.
Spectrum visible to humans h400nm, 700nmi.
Sensors do not have direct access to color, i.e., wavelength
λ. Exception: spectrometer.
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Response of i-th sensor
Zλ2
si =
s(λ)ri dλ ,
λ1
ri is spectral density of i-th sensor,
s(λ) is spectral density of light.
where
BUNSEN PRISM MONOCHROMATOR
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DIFFRACTION (GRATING)
MONOCHROMATOR
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SPECTRAL REFLECTANCE OF FLOWERS
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VISIBLE SPECTRUM
Retina – 4 types of
receptors.
R, G, B cones,
color vision.
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Rods, monochromatic vision with
higher sensitivity.
RADIOMETRY FOR COLOR
All definitions are now “per unit wavelength”.
All units are now per unit wavelength.
All terms are now “spectral”.
Radiance becomes spectral radiance [watts per square
meter per steradian per unit wavelength].
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Irradiance becomes spectral irradiance [watts per square
meter per unit wavelength].
RADIOMETRY FOR COLOR 2
Dependence on wavelength λ is introduced into BRDF.
L becomes spectral radiance.
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E becomes spectral irradiance.
L(Θi, Φi, λ)
BRDF = f (Θi, Φi, Θe, Φe, λ) =
E(Θe, Φe, λ)
In computer vision, simplified models are often used which use
relative measures instead of absolute absolute measures.
ILLUMINATION SPECTRUM
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RELATIVE REFLECTANCE
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RELATIVE TRANSMITTANCE
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HUMANS AND TRICHROMACY
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The eye reduces all the wavelengths at a given ‘pixel’ to just the
total amount of red, green, and blue.
RGB COMPONENTS OF A COLOR IMAGE
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MIXTURE OF COLORS
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ADDITIVE COLOR MIXING
400 nm
500 nm
+
600 nm
500 nm
600 nm
700 nm
=
YELLOW
400 nm
500 nm
600 nm
Red plus
yellow.
Additive mixing model
holds for CRT phosphors,
multiple projectors aimed at
a screen, Polachromeslide
film, human eye cones.
700 nm
GREEN
400 nm
RED
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700 nm
green
makes
SUBTRACTIVE COLOR MIXING
Applies when colors mix
by multiplying the color
spectra.
Cyan (called blue in
crayons) minus (actually
multiply) yellow makes
green.
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Subtractive mixing model
holds for most photographic
films,
paint,
crayons,
printing, cascaded optical
filters.
CYAN
400 nm
500 nm
600 nm
-
700 nm
YELLOW
400 nm
500 nm
600 nm
700 nm
=
GREEN
400 nm
500 nm
600 nm
700 nm
COLOR CAMERAS
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1 chip camera + filter
3 chip camera
HUE, SATURATION, VALUE
COLOR SPACE
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COLOR CONSTANCY, MOTIVATION
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Colorimetry versus color perception.
FAILURES IN COLOR CONSTANCY
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FAILURES IN COLOR CONSTANCY (2)
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FAILURES IN COLOR CONSTANCY (3)
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INFLUENCE OF ILLUMINATION
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INFLUENCE OF ILLUMINATION (2)
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INFLUENCE OF OUTLINE
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Bezold effect
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