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 meter)-6
400 500 600 700
ELECTROMAGNETIC SPECTRUM
VISIBLE SPECTRUM
10-14 meters 106 meters
Wavelength (nm)
CosmicRays
GammaRays X-rays UV Infra-
RedMicro-waves TV RadioLight
© Stephen E. Palmer, 2002
The Physics of Light
.
# P
ho
ton
s
D. Normal Daylight
Wavelength (nm.)
B. Gallium Phosphide Crystal
400 500 600 700
# P
ho
ton
s
Wavelength (nm.)
A. Ruby Laser
400 500 600 700
400 500 600 700
# P
ho
ton
s
C. Tungsten Lightbulb
400 500 600 700
# P
ho
ton
s
Some examples of the spectra of light sources
© Stephen E. Palmer, 2002
The Physics of Light
Some examples of the reflectance spectra of surfaces
Wavelength (nm)
% P
hoto
ns R
efle
cted
Red
400 700
Yellow
400 700
Blue
400 700
Purple
400 700
© Stephen E. Palmer, 2002
The Psychophysical Correspondence
There is no simple functional description for the perceivedcolor of all lights under all viewing conditions, but …...
A helpful constraint: Consider only physical spectra with normal distributions
area
Wavelength (nm.)
# Photons
400 700500 600
mean
variance
© Stephen E. Palmer, 2002
The Psychophysical Correspondence
Mean Hue
yellowgreenblue
# P
hoto
ns
Wavelength
© Stephen E. Palmer, 2002
The Psychophysical Correspondence
Variance Saturation
Wavelength
high
medium
low
hi.
med.
low# P
hoto
ns
© Stephen E. Palmer, 2002
The Psychophysical Correspondence
Area Brightness#
Pho
tons
Wavelength
B. Area Lightness
bright
dark
© Stephen E. Palmer, 2002
Physiology of Color Vision
© Stephen E. Palmer, 2002
Cones cone-shaped less sensitive operate in high light color vision
Rods rod-shaped highly sensitive operate at night gray-scale vision
Two types of light-sensitive receptors
cone
rod
The Microscopic View
http://www.iit.edu/~npr/DrJennifer/visual/retina.html
Rods and Cones in the Retina
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 itselfmiddle: brightness of the
stimulibottom: 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:
© Stephen E. Palmer, 2002
Trichromatic Theory (Palmer/Young/Helmholtz)
Hermann von Helmholtz
Opponent Process Theory (Hering)
Ewald Hering
© Stephen E. Palmer, 2002
.
400 450 500 550 600 650
RE
LAT
IVE
AB
SO
RB
AN
CE
(%
)
WAVELENGTH (nm.)
100
50
440
S
530 560 nm.
M L
Three kinds of cones: Absorption spectra
Implementation of Trichromatic theory
Physiology of Color Vision
Opponent Processes: R/G = L-M G/R = M-L B/Y = S-(M+L) Y/B = (M+L)-S
© Stephen E. Palmer, 2002
Opponent-Process Cells in LGN (De Valois)
Physiology of Color Vision
0
BL
Wavelength
FiringRate
max.
R+G-G+R-
400 500 600 7000
BL
Wavelength
max.
B+Y- Y+B-FiringRate
400 500 600 700
Implementation of opponent process theory(Similar color behavior in retinal ganglion cells)
© Stephen E. Palmer, 2002
Double Opponent Cells in V1
Physiology of Color Vision
G+R-
G+R-
R+G-
R+G-
Red/Green
Y+B-
Y+B-
B+Y-
B+Y-
Blue/Yellow
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?
NormalTrichromat
Protanope Deuteranope Tritanope© Stephen E. Palmer, 2002
Theories of Color Vision
Red
+
-
0Green
Red/Green Receptors
Blue/Yellow Receptors
Black/White Receptors
Yellow
+
-
0Blue
White
+
-
0Black
Opponent Process theory (Hering): All colors are combinations of responses in three underlyingbipolar systems (Red/Green, Blue/Yellow, Black/White).
© Stephen E. Palmer, 2002
Theories of Color Vision
Dual Process Theory (Hurvich & Jameson): The colorvision system contains two stages: an initial trichromaticstage and a later opponent-process stage.
© Stephen E. Palmer, 2002
Trichromaticstage
Opponent-Process stage
Dual Process Theory
Theories of Color Vision
A Dual Process Wiring Diagram
© Stephen E. Palmer, 2002
S M L
R+ G-
+ +- -
B+ Y-+
+
- -
G+Y+
Bk+
S-M-L
++
L-M -S+M+L -S-M-L M-L
W+ Bk-
S+M+L
++ -
-
MLML
S M L
W-
B- R-
Trichromatic Stage
Opponent Process Stage
COLOR VISION: Part 4
© Stephen E. Palmer, 2002
1. Color Constancy:Surface-based processing
2. Color Naming:Category-based processing
Color Constancy
© Stephen E. Palmer, 2002
Color Constancy: the ability to perceive theinvariant color of a surface despite ecologicalVariations in the conditions of observation.
Another inverse problem: Physics of light emission and surface reflection underdetermine perception of surface color
Color Constancy
© Stephen E. Palmer, 2002
ReflectanceSpectrum
(Rw)
LuminanceSpectrum
(Lw)
X =
(# Photons Emitted) X (# Photons Reflected)(% Photons Reflected) =
IlluminationSpectrum
(Iw)
% Photons
400 700
Rw
400 700
Daylight# Photons
Iw
# Photons
400 700
Lw
Color Constancy
© Stephen E. Palmer, 2002
400 700 400 700 400 700
X =DaylightA
400 700 400 700 400 700
X =
TungstenBulb
B
400 700 400 700 400 700
X =
Wavelength (nm.)
HeliumNeonLaser
C
ReflectanceSpectrum
(Rw)
LuminanceSpectrum
(Lw)
X =
(# Photons Emitted) X (# Photons Reflected)(% Photons Reflected) =
IlluminationSpectrum
(Iw)
Color Constancy
© Stephen E. Palmer, 2002
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
Color Constancy
© Stephen E. Palmer, 2002
Luminance ratio is invariant over illumination:
100
90
10
INDOORS
10,000
9,000
1,000
OUTDOORS
Luminance Ratio = 9:1 Luminance Ratio = 9:1
Color Constancy
© Stephen E. Palmer, 2002
What about absolute lightness?
How do we know what is white?
(How big is the anchor???)
The anchoring problem:
Anchoring heuristic: The lightest region is taken as white
Color Naming
© Stephen E. Palmer, 2002
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”
Color Naming
© Stephen E. Palmer, 2002
BCTs in English
RedGreenBlueYellowBlackWhite
GrayBrownPurpleOrange*Pink
Color Naming
© Stephen E. Palmer, 2002
Five more BCTs in a study of 98 languages
Light-BlueWarmCoolLight-WarmDark-Cool
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
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
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
W Bk Bk Bk
R Y+Bk (Brown) Y+Bk (Brown)
Y R+W (Pink)
Bk or G or Bu R + Bu (Purple)
R+Y (Orange)
B+W (Grey)
Color Naming
© Stephen E. Palmer, 2002
Typical “developmental” sequence of BCTs
Light-warm
Dark-cool
(2 Terms)
White
Warm
Dark-cool
(3 Terms)
Black
Cool
White
Warm
(4 Terms)
Red
Yellow
White
Black
Cool
(5 Terms)
White
Red
Yellow
Black
Green
Blue
(6 Terms)
Color Naming
© Stephen E. Palmer, 2002
Studied color categories in two ways
Boundaries
Best examples
(Berlin & Kay)
Color Naming
© Stephen E. Palmer, 2002
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.
(Rosch)
Color Naming
Deg
ree
of M
embe
rshi
p
FUZZY SETS AND FUZZY LOGIC (Zadeh)
0
1.0
0
"Green"
very
not-at-all
a little bit
sorta
Hue
extremely
Degree ofMembership
Fuzzy set theory (Zadeh)
A fuzzy logical model of color naming (Kay & Mc Daniel)
© Stephen E. Palmer, 2002
Color Naming
© Stephen E. Palmer, 2002
0
1
Degree ofMembership
Hue
Blue Green Yellow Red
focal blue
focalgreen
focalyellow
focal red
BlueGreen
Yellow
Red
Hue
0
1
Degree ofMembership
“Primary” color categories
Color Naming
© Stephen E. Palmer, 2002
“Primary” color categories
RedGreenBlueYellowBlackWhite
Color Naming
© Stephen E. Palmer, 2002
“Derived” color categories.
Hue
0
1 Yellow Red
Y R
U
Degree ofMembership
Hue
Hue
Orange
0
1
Degree ofMembership
Fuzzylogical“ANDf”
Color Naming
© Stephen E. Palmer, 2002
“Derived” color categories
Orange = Red ANDf YellowPurple = Red ANDf BlueGray = Black ANDf WhitePink = Red ANDf WhiteBrown = Yellow ANDf Black(Goluboi = Blue ANDf White)
Color Naming
© Stephen E. Palmer, 2002
“Composite” color categories
Fuzzylogical“ORf”
Hue
0
1 Yellow Red
Y RU Degree ofMembership
Hue
Warm = Red Orf YellowCool = Blue Orf GreenLight-warm = White Orf WarmDark-cool = Black Orf Cool
Color Naming
FUZZY LOGICAL MODEL OF COLOR NAMING (Kay & McDaniel)
RedGreenBlue
YellowBlackWhite
OrangePurpleBrownPinkGray
[Light-blue]
[Warm][Cool]
[Light-warm][Dark-cool]
PRIMARY DERIVED COMPOSITE
Only 16 Basic Color Terms in Hundreds of Languages:
1.0
0
1.0
00
Yellow Orange = Yellow ANDf Red Warm = Yellow ORf RED
De
gre
e o
f M
em
be
rsh
ip
(Fuzzy ANDf) (Fuzzy ORf)(Fuzzy sets)
© Stephen E. Palmer, 2002