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Color and Color Space

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Color and Color Space
Presenter: Cheng-Jin Kuo
Advisor: Jian-Jiun Ding, Ph. D.
Professor
Digital Image & Signal Processing Lab
Graduate Institute of Communication Engineering
National Taiwan University, Taipei, Taiwan, ROC
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Outline
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Introduction
Additive Color Mixing
Subtractive Color Mixing
Newton Color Circle & Maxwell Triangle
System of Color Measurement
Color Space
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1.Introduction
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Three Characteristics of Color:
hue
brightness: the luminance of the object
saturation: the blue sky
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1.Introduction
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Wavelength of the light
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2.Additive Color Mixing
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The mixing of “light”
Primary: Red, Green, Blue
The complementary color
“White” means
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2.Subtractive Color Mixing
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The mixing of “pigment”
Primary: Cyan, Magenta, Yellow
The complementary color
Why black?
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2.Subtractive Color Mixing
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Why?
Pigments absorb light
Thinking:
the Color Filters
Question:
Yellow + Cyan=?
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3.Newton Color Circle
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Newton Color Circle
A tool to predict
color mixing
hue :
saturation :
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3.Newton Color Circle
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Full saturated
Question:
How do we make
a color having the
same saturation
as Cyan does?
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4.Maxwell Triangle
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Connecting the GB
The negative
component of Red?
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4.Maxwell Triangle
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Spectral Locus
Spectral Color
Full saturated color
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5.The CIE System
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CIE 1931 XYZ system
One of the color spaces
The first mathematical defined color
space
Three parameter:
X, Y, Z
or Y (brightness), x, y (chroma)
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5.The CIE System
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CIE Chromaticity
Diagram
Spectral Locus
Parameter x, y
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5.The CIE System
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How do we get the parameters
from a specified color or object?
The spectral power distribution of
the illuminant: S ( пЃ¬ )
spectral reflectance factor of the
R (пЃ¬ )
object :
Matching function: x ( пЃ¬ ) y ( пЃ¬ ) z ( пЃ¬ )
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5.The CIE System
u
X  k  x (  )S (  ) R (  )
l
u
Y  k  y (  )S (  ) R (  )
l
u
Z  k  z (  )S (  ) R (  )
l
k пЂЅ
100
u

l
y (пЃ¬ ) S (пЃ¬ )
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5.The CIE System
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Y: the brightness
The chroma parameter x, y :
xпЂЅ
yпЂЅ
X
X пЂ«Y пЂ« Z
Y
X пЂ«Y пЂ« Z
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6.Color Measurement System
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Why do we order colors?
Color Order system
Trichromatic theory by Hermann von
Helmholtz
The concept of color space
So what are the three parameters?
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6.Color Measurement System
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Color order systems:
Munsell Color System
Natural Color System(NCS)
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7.Munsell Color System
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One of the Oldest color order systems
The three main parameters:
Munsell Hue (H) :
five primary:5R, 5Y, 5G, 5B, 5P
Munsell Value (V) :
the brightness scale from 0(black)~10
Munsell Chroma (C) :
from /0~/14
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7.Munsell Color System
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The examples of
color expression:
5GY 8/2 :
Hue:5GY
Value:8
Chroma:2
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8.Natural Color System (NCS)
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Six important value:
r, y, g, b, s (black), w (white)
Summing up the six values always get 100
Hue (Р¤) :
Y90R : r=90%, y=10%
Blackness (s)
Chromaticness (c)
C=r + y + g + b
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8.Natural Color System (NCS)
Y Y10R Y20R
G50Y
Y50R
Y90R
G
R
B50G
R50B
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8.Natural Color System (NCS)
If the color data is:
10% whiteness
30% blackness
30% yellowness
30% redness
пѓ� S=30, c=r+y=60
Р¤=Y50R
пѓ 3060-Y50R
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9.Color Space
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Color Space:
RGB
YCbCr (YPbPr)
YUV
YIQ
CMYK
A comparison of them
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9.Color Space
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What is color space?
A 3D model used to define a specified
color
The difference between color spaces:
The choice of axes
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9.Color Space – RGB
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RGB:
The simplest color space
Axes: Red, green, blue
Advantages: simple
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9.Color Space – YCbCr &YPbPr
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YCbCr & YPbPr
Used for: digital video encoding, digital
camera
Axes:
Y: luma
Cb: blue chroma
Cr: red chroma
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9.Color Space – YCbCr &YPbPr
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Conversion from RGB:
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Y=0.299(R-G) + G + 0.114(B-G)
Cb=0.564(B-Y)
Cr=0.713(R-Y)
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The Matrix form:
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0.587
0.114 пѓ¶ пѓ¦ R пѓ¶
пѓ¦ Y пѓ¶ пѓ¦ 0.299
пѓ§ пѓ· пѓ§
пѓ·пѓ§ пѓ·
Cb пЂЅ пЂ­ 0.168636 0.232932 пЂ­ 0.064296 G
пѓ§ пѓ· пѓ§
пѓ·пѓ§ пѓ·
пѓ§ Cr пѓ· пѓ§ 0.499813 пЂ­ 0.418531 пЂ­ 0.081282 пѓ· пѓ§ B пѓ·
пѓЁ пѓё пѓЁ
пѓёпѓЁ пѓё
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9.Color Space – YCbCr &YPbPr
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Why do we use the luma & chroma
channel?
Advantage:
Bandwidth efficiency
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9.Color Space – YUV
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YUV
Used for: video encoding for some
standard such as NTSC, PAL, SECAM
Axes:
Y: luma
U: blue chroma
V: red chroma
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9.Color Space – YUV
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Conversion from RGB:
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Y=0.299R+0.587G+0.114B
U=0.436(B-Y)/(1-0.114)
V=0.615(R-Y)/(1-0.299)
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The Matrix form:
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пѓ¦Y
пѓ§
U
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пѓ§V
пѓЁ
0.587
0.114 пѓ¶ пѓ¦ R пѓ¶
пѓ¶ пѓ¦ 0.299
пѓ· пѓ§
пѓ·пѓ§ пѓ·
пЂЅ пЂ­ 0.14713 пЂ­ 0.28886
0.436
G
пѓ· пѓ§
пѓ·пѓ§ пѓ·
пѓ· пѓ§ 0.615
пѓ·пѓ§ B пѓ·
пЂ­
0.51499
пЂ­
0.10001
пѓё пѓЁ
пѓёпѓЁ пѓё
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9.Color Space – YIQ
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YIQ
Used for: video encoding for some standard
such as NTSC
Axes:
Y: luma
I: blue chroma
Q: red chroma
I-Q channels are rotated from the U-V
channels in YUV
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9.Color Space – YIQ
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Conversion from RGB:
пѓ¦ Y пѓ¶ пѓ¦ 0.299
пѓ§ пѓ· пѓ§
I пЂЅ 0.595716
пѓ§ пѓ· пѓ§
пѓ§ Q пѓ· пѓ§ 0.211456
пѓЁ пѓё пѓЁ
пѓ¶пѓ¦ R пѓ¶
пѓ·пѓ§ пѓ·
пЂ­ 0.274453 пЂ­ 0.321263 G
пѓ·пѓ§ пѓ·
пЂ­ 0.522591 0.311135 пѓ·пѓё пѓ§пѓЁ B пѓ·пѓё
0.587
0.114
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9.Color Space – CMYK
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Used for: printer printing
Use the subtractive color mixing
Axes:
Cyan
Magenta
Yellow
K: black
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9.Color Space – CMYK
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Conversion from RGB:
C = 255 -Y - 1.4021(Cr-128)
M = 255 - Y + 0.3441(Cb-128) + 0.7142(Cr-128)
Y = 255 - Y - 1.7718(Cb -128)
K = min (C, M, Y)
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9.Color Space – Comparison
Color
space
Color
mixing
Primary
parameters
Used for
Pros and
cons
RGB
Additive
Red,
Green, Blue
CMYK
Subtractive
Cyan, Magenta,
Yellow, Black
Printer
Works in pigment
mixing
YCbCr
YPbPr
additive
Y(luminance),
Cb(blue chroma),
Cr(red chroma)
Video encoding,
digital camera
Bandwidth efficient
YUV
additive
Y(luminance),
U(blue chroma),
V(red chroma)
Video encoding
for NTSC, PAL,
SECAM
Bandwidth efficient
YIQ
additive
Y(luminance),
I(rotated from U),
Q(rotated from V)
Video encoding
for NTSC
Bandwidth efficient
Easy but wasting
bandwidth
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References
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[1] R. G. Kuehni, Color Space and Its Divisions, Wiley
Inter-Science, 2002
[2] P. Green, L.MacDonald, Colour Engineering, Wiley,
2002
[3] R. W. G. Hunt, Measuring Colour, Ellis Horwood,
1995
[4] H. J. Durrett, Color and The Computer, Academic,
1987
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