COLOR VISION
© Stephen E. Palmer, 2002
COLOR VISION
“The Color Story” is a prototype for Cognitive Science
Contributions from:
Physics (Newton)
Philosophy (Locke)
Art (Munsell)
Psychophysics (Maxwell)
Physiology (De Valois)
Cognitive Psychology (Rosch)
Neurology (Zeki)
Linguistics (Lakoff)
Cognitive Anthropology (Berlin & Kay)
Computer Science (Zadeh)
© Stephen E. Palmer, 2002
COLOR VISION
“The Color Story” is a prototype for Cognitive Science
Contributions from: * Berkeley faculty
Physics (Newton)
Philosophy (Locke)
Art (Munsell)
Psychophysics (Maxwell)
Physiology (De Valois)
Cognitive Psychology (Rosch)
Neurology (Zeki)
Linguistics (Lakoff)
Cognitive Anthropology (Berlin & Kay)
Computer Science (Zadeh)
© Stephen E. Palmer, 2002
The Physics of Light
Light: Electromagnetic energy whose
wavelength is between 400 nm and 700 nm.
(1 nm = 10 -6 meter)
© Stephen E. Palmer, 2002
The Physics of Light
Some examples of the spectra of light sources
.
B. Gallium Phosphide Crystal
# Photons
# Photons
A. Ruby Laser
400 500
600
700
400 500
Wavelength (nm.)
700
Wavelength (nm.)
D. Normal Daylight
# Photons
C. Tungsten Lightbulb
# Photons
600
400 500
600
700
400 500
600
700
© Stephen E. Palmer, 2002
The Physics of Light
% Photons Reflected
Some examples of the reflectance spectra of surfaces
Red
400
Yellow
700 400
Blue
700 400
Wavelength (nm)
Purple
700 400
700
© Stephen E. Palmer, 2002
The Psychophysical Correspondence
There is no simple functional description for the perceived
color of all lights under all viewing conditions, but …...
A helpful constraint:
Consider only physical spectra with normal distributions
mean
area
# Photons
400
500
variance
600
700
Wavelength (nm.)
© Stephen E. Palmer, 2002
The Psychophysical Correspondence
# Photons
Mean
blue
Hue
green yellow
Wavelength
© Stephen E. Palmer, 2002
The Psychophysical Correspondence
# Photons
Variance
Saturation
hi. high
med. medium
low
low
Wavelength
© Stephen E. Palmer, 2002
The Psychophysical Correspondence
Area
Brightness
# Photons
B. Area
Lightness
bright
dark
Wavelength
© Stephen E. Palmer, 2002
Physiology of Color Vision
Two types of light-sensitive receptors
Cones
cone-shaped
less sensitive
operate in high light
color vision
Rods
rod-shaped
highly sensitive
operate at night
gray-scale vision
© Stephen E. Palmer, 2002
The Microscopic View
Rods and Cones in the Retina
http://www.iit.edu/~npr/DrJennifer/visual/retina.html
What Rods and Cones Detect
Notice how they aren’t distributed evenly, and the
rod is more sensitive to shorter wavelengths
•
Center /
Surround
Strong activation in center,
inhibition on surround
• The effect you get using these
center / surround cells is
enhanced edges
top:
the stimuli itself
middle: brightness of the stimuli
bottom: response of the retina
• You’ll see this idea get used in
Regier’s model
http://www-psych.stanford.edu/~lera/psych115s/notes/lecture3/figures1.html
How They
Fire
• No stimuli:
– both fire at base rate
• Stimuli in center:
– ON-center-OFF-surround
fires rapidly
– OFF-center-ON-surround
doesn’t fire
• Stimuli in surround:
– OFF-center-ON-surround
fires rapidly
– ON-center-OFF-surround
doesn’t fire
• Stimuli in both regions:
– both fire slowly
Theories of Color Vision
Two main algorithmic theories of color vision:
Trichromatic Theory
(Palmer/Young/Helmholtz)
Hermann von Helmholtz
Opponent Process
Theory (Hering)
Ewald Hering
© Stephen E. Palmer, 2002
Physiology of Color Vision
Three kinds of cones: Absorption spectra
440
RELATIVE ABSORBANCE (%)
.
530 560 nm.
100
S
M
L
Opponent Processes:
R/G = L-M
G/R = M-L
B/Y = S-(M+L)
Y/B = (M+L)-S
50
400
450
500
550
600 650
WAVELENGTH (nm.)
Implementation of Trichromatic theory
© Stephen E. Palmer, 2002
Physiology of Color Vision
Opponent-Process Cells in LGN (De Valois)
max.
max.
G+R-
Firing
Rate
R+G-
BL
0
Firing
Rate
BL
B+Y-
Y+B-
0
400
500
600
Wavelength
700
400
500
600
Wavelength
700
Implementation of opponent process theory
(Similar color behavior in retinal ganglion cells)
© Stephen E. Palmer, 2002
Physiology of Color Vision
Double Opponent Cells in V1
G+ R -
Y+B-
R +G -
B+Y-
R + G-
B+Y-
G+ R -
Y+B-
Red/Green
Blue/Yellow
© Stephen E. Palmer, 2002
Color Blindness
Not everybody perceives colors in the same way!
What numbers do you see in these displays?
© Stephen E. Palmer, 2002
Color Blindness
There are several forms of inherited variations
of color vision.
Trichromatic (“normal”) color vision
Dichromatic color vision
2 forms of red-green color blindness
1 form of yellow-blue color blindness
Monochromatic color vision
4 forms
Various forms of “color weakness”
© Stephen E. Palmer, 2002
Color Blindness
What does the world look like to a color blind person?
Normal
Trichromat
Protanope
Deuteranope
Tritanope
© Stephen E. Palmer, 2002
Theories of Color Vision
Opponent Process theory (Hering): All colors are
combinations of responses in three underlying
bipolar systems (Red/Green, Blue/Yellow, Black/White).
+
+
Red
+
Yellow
0
0
0
Green
Red/Green
Receptors
White
Blue
Blue/Yellow
Receptors
Black
Black/White
Receptors
© Stephen E. Palmer, 2002
Theories of Color Vision
Dual Process Theory (Hurvich & Jameson): The color
vision system contains two stages: an initial trichromatic
stage and a later opponent-process stage.
Trichromatic
stage
OpponentProcess stage
Dual Process Theory
© Stephen E. Palmer, 2002
Theories of Color Vision
A Dual Process Wiring Diagram
Trichromatic Stage
S
M
+
B+ Y-
L
+
ML +
+
S
+
-
R+ G-
M
-
-
+
S+M+L
+
ML
Y+ B- +
-
W+ Bk-
S-M-L
L
G+ R-
Bk+ W-
L-M
-S+M+L
-S-M-L
M-L
Opponent Process Stage
© Stephen E. Palmer, 2002
COLOR VISION: Part 4
1. Color Constancy:
Surface-based processing
2. Color Naming:
Category-based processing
© Stephen E. Palmer, 2002
Color Constancy
Color Constancy: the ability to perceive the
invariant color of a surface despite ecological
Variations in the conditions of observation.
Another inverse problem:
Physics of light emission and surface reflection
underdetermine perception of surface color
© Stephen E. Palmer, 2002
Color Constancy
# Photons
Iw
# Photons
400
Illumination
Spectrum
(Iw)
Reflectance
Spectrum
(Rw)
% Photons
400
700
X
700
Rw
Lw
400
Daylight
=
700
Luminance
Spectrum
(Lw)
(# Photons Emitted) X (% Photons Reflected) = (# Photons Reflected)
© Stephen E. Palmer, 2002
Color Constancy
Illumination
Spectrum
(Iw)
X
Reflectance
Spectrum
(Rw)
=
Luminance
Spectrum
(Lw)
(# Photons Emitted) X (% Photons Reflected) = (# Photons Reflected)
A
B
C
Daylight
X
400
Tungsten
Bulb
700
400
700
Helium
Neon
Laser
400
=
400
X
X
700
700
400
700
400
700
=
400
700
=
400
700
Wavelength (nm.)
400
700
© Stephen E. Palmer, 2002
Color Constancy
Two approaches to lightness constancy
Unconscious Inference (Helmholtz)
Luminance = Intensity * Reflectance
If you know L and I, you can solve for R!
Invariant Relations (Hering)
Luminance ratios are invariant with illumination
© Stephen E. Palmer, 2002
Color Constancy
Luminance ratio is invariant over illumination:
100
10,000
9,000
90
1,000
10
INDOORS
Luminance Ratio = 9:1
OUTDOORS
Luminance Ratio = 9:1
© Stephen E. Palmer, 2002
Color Constancy
The anchoring problem:
What about absolute lightness?
How do we know what is white?
(How big is the anchor???)
© Stephen E. Palmer, 2002
Anchoring heuristic: The lightest region is taken as white
Color Naming
Basic Color Terms (Berlin & Kay)
Criteria:
1. Single words -- not “light-blue” or “blue-green”
2. Frequently used -- not “mauve” or “cyan”
3. Refer primarily to colors -- not “lime” or “gold”
4. Apply to any object -- not “roan” or “blond”
© Stephen E. Palmer, 2002
Color Naming
BCTs in English
Red
Green
Blue
Yellow
Black
White
Gray
Brown
Purple
Orange*
Pink
© Stephen E. Palmer, 2002
Color Naming
Five more BCTs in a study of 98 languages
Light-Blue
Warm
Cool
Light-Warm
Dark-Cool
© Stephen E. Palmer, 2002
The WCS Color Chips
• Basic color terms:
–
–
–
–
Single word (not blue-green)
Frequently used (not mauve)
Refers primarily to colors (not lime)
Applies to any object (not blonde)
FYI:
English has 11
basic color terms
Results of Kay’s Color Study
Stage I
II
IIIa / IIIb
IV
V
VI
VII
W or R or Y
W
W
W
W
W
W
Bk or G or Bu
R or Y
R or Y
R
R
R
R
Bk or G or Bu
G or Bu
Y
Y
Y
Y
Bk
G or Bu
G
G
G
Bk
Bu
Bu
Bu
Bk
Bk
Bk
Y+Bk (Brown)
Y+Bk (Brown)
W
R
Y
R+W (Pink)
Bk or G or Bu
R + Bu (Purple)
R+Y (Orange)
B+W (Grey)
If you group languages into the number of basic color
terms they have, as the number of color terms
increases, additional terms specify focal colors
Color Naming
Typical “developmental” sequence of BCTs
( 2 Terms)
( 3 Terms)
Whit e
( 4 Terms) ( 5 Terms)
Whit e
Light -w arm
Warm
Dark-cool
Whit e
Whit e
Red
Red
Yello w
Yellow
Black
Black
Warm
Black
( 6 Terms)
Dark-cool
Green
Cool
Cool
Blue
© Stephen E. Palmer, 2002
Color Naming
(Berlin & Kay)
Studied color categories in two ways
Boundaries
Best examples
© Stephen E. Palmer, 2002
Color Naming
(Rosch)
MEMORY :
Focal colors are remembered better than nonfocal colors.
LEARNING:
New color categories centered on focal colors are learned faster.
Categorization:
Focal colors are categorized more quickly than nonfocal colors.
© Stephen E. Palmer, 2002
Color Naming
SETS
FUZZY
LOGIC(Kay
(Zadeh)
A fuzzy logicalFUZZY
model
ofAND
color
naming
& Mc Daniel)
Fuzzy set theory (Zadeh)
Degree of Membership
"Green"
1.0
extremely
very
Degree of
Membership
sorta
a little bit
0
not-at-all
0
Hue
© Stephen E. Palmer, 2002
Color Naming
“Primary” color categories
focal
blue
focal
green
focal
yellow
focal
red
Blue
Green
Yellow
Red
1
Degree of
Membership
0
Hue
1
Degree of
Membership
0
Green
Blue
Yellow
Red
Hue
© Stephen E. Palmer, 2002
Color Naming
“Primary” color categories
Red
Green
Blue
Yellow
Black
White
© Stephen E. Palmer, 2002
Color Naming
“Derived” color categories
.
Yellow
Red
Hue
Y
Degree of
Membership
Fuzzy
logical
“ANDf”
U
1
R
0
1
Orange
Hue
Degree of
Membership
0
Hue
© Stephen E. Palmer, 2002
Color Naming
“Derived” color categories
Orange = Red ANDf Yellow
Purple = Red ANDf Blue
Gray = Black ANDf White
Pink = Red ANDf White
Brown = Yellow ANDf Black
(Goluboi = Blue ANDf White)
© Stephen E. Palmer, 2002
Color Naming
“Composite” color categories
Fuzzy
logical
“ORf”
Warm = Red Orf Yellow
Cool = Blue Orf Green
Light-warm = White Orf Warm
Dark-cool = Black Orf Cool
© Stephen E. Palmer, 2002
Color Naming
FUZZY LOGICAL MODEL OF COLOR NAMING (Kay & McDaniel)
Only 16 Basic Color Terms in Hundreds of Languages:
Red
Green
Blue
Yellow
Black
W hite
Orange
Purple
Brown
Pink
Gray
[Light-blue]
PRIMARY
(Fuzzy sets)
Degree of Membership
0
COMPOSITE
(Fuzzy OR f )
1.0
1.0
0
DERIVED
(Fuzzy AND f )
[Warm]
[Cool]
[Light-warm]
[Dark-cool]
0
Yellow
Orange = Yellow AND f Red
Warm = Yellow OR f RED
© Stephen E. Palmer, 2002