why we don’t know how many colors there are
DESCRIPTION
There have been many attempts to answer the question of how many distinct colors there are, with widely varying answers. Here we present an analysis of what it would take to arrive at a reliable answer and show how currently available models fail to make predictions under the wide range of conditions that needs to be considered. Gamut volumes are reported for a number of light sources and viewing modes and the conclusion is drawn that the only reliable data we have comes from psychophysical work. The color gamut of the LUTCHI data in CIECAM02 is therefore shown as an alternative to the gamut of all possible colors.TRANSCRIPT
CGIV 2012
Why we don’t know
how many colors there are
Ján Morovič, Vien Cheung* & Peter Morovič Hewlett-Packard Company
*University of Leeds
Presented by Dr. Vien Cheung at CGIV ‘12, Amseterdam on 7th May 2012
How many colors are there?
3 infinity
16.8 million 28 × 28 × 28 = ~
How many colors are there?
o usefulness in engineering decision processes
o interesting!
o but ... what is color? and what does ‘all possible colors’ mean?
What does ‘all possible colors’ mean?
16 million
CIE system
| 2-10 million
| visual system
physical colors | perceptual colors
Color illusions
o the notion of color is essentially a property of an object does not explain color illusions
Color ‘illusions’
[255 0 0]
physical colors > perceptual colors
physical colors < colors depend upon context
Related studies
2010
1980
1999
2001
2004 2005
2008
1920 o all possible surface colors Schrodinger
Maric-France & Foster
McCann
o color spaces | gamut computations
o viewing condition Morovič et al.
o natural surface
Pointer
Inui et al.
o illumination | adapted white
Heckaman et al.
o natural scenes
Linhares et al.
Our work
o computationally predicting all possible colors
o counting all possible colors ‘by hand’
o discuss the limitations of gamut computation and appearance prediction
Counting colors ‘by hand’
o this exercise can tell us how many colors there are on a gray background, when viewed under a certain light source, etc.!
Counting colors ‘by hand’
Computational prediction
o CIECAM02
o an ecosystem enabling varying color experiences
o color appearance attributes effect on predicting gamut
o explore the effect of various model parameters
Computational prediction
Computational prediction
Light source D50 F11
Surround average dim dark average
Background 20% 20% 20% 20%
Luminance of adapting field
~60 cd/m2 ~60 cd/m2 ~60 cd/m2 ~60 cd/m2
Gamut volume 3.8 MJab 3.5 MJab 3.0 MJab 4.2 MJab
o D50 + F11 = 4.4 MJab
o D50 + F11 + A (3.5 MJab) = 4.5 MJab
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.80
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
CIE x
CIE
y
0.2
0.4
0.60.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
5
6
7
8
9
10
11lo
g10
Jab
gam
ut v
olum
e
CIE y
CIE x
Computational prediction
o expanding to standard iluminants to freely varying their SPD
o 242 synthetic light sources
Computational prediction
o CIECAM02 dramatically predicts color gamut with 1011 volumes in Jab space
o i.e. 100,000 times of all possible surface colors under D50
o however, this increment does not agree with experience and is a psychophysical data-based model
o the difficulty of viewing all possible visual ecosystems remains
Computational prediction
o a revised prediction uses 173 measured light sources
400 450 500 550 600 650 7000
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
wavelength (nm)
rela
tive
spec
tral p
ower
0.1 0.2 0.3 0.4 0.5 0.6 0.70
0.1
0.2
0.3
0.4
0.5
CIE x
CIE
y
0.2
0.4
0.60.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
5
6
7
8
9
10
11
log1
0 Ja
b ga
mut
vol
ume
CIE y
CIE x
o a total gamut volume of 6.6 MJab
o i.e. the surface, which under D50 (3.8 MJab), result in ~2× that range of colors viewed under a variety of light sources
Computational prediction
−200 −150 −100 −50 0 50 100 150 200−200
−150
−100
−50
0
50
100
150
200
CIE a*
CIE
b*
−200 −150 −100 −50 0 50 100 150 200−200
−150
−100
−50
0
50
100
150
200
CIE a*
CIE
b*
−200−150
−100−50
050
100150
200
−200−150
−100−50
050
100150
2000
20
40
60
80
100
120
CIE a*
CIE b*
CIE
L*
−200−150
−100−50
050
100150
200
−200−150
−100−50
050
100150
2000
20
40
60
80
100
120
CIE a*
CIE b*
CIE
L*
D50 | 173 measured light sources
Computational prediction
CAM
o Note that CIECAM02 does not include many complexities of colour vision such as contrast effects
o using CAM to indicate all possible colors should consider the color gamuts of colour appearance they are derived from
o CIECAM02 (LUTCHI data) – 1.7 MJab
Conclusions
o based upon the available data to-date there are at least ~1.7 million colors
o to go beyond this type of number would require:
o a color appearance model closely mimics the human visual system o extend psychophysical basis