1

Introduction to Color Spaces

Author: Chik-Yau Foo

E-mail: r89922082@ms89.ntu.edu.tw

Mobile phone: 0920-767-580v030305

Presenter: Wei-Cheng LinE-mail: r97944028@ntu.edu.twMobile Phone: 0912-808-362

2

The EM Spectrum

103

100

10-3

10-6

10-9

10-12

106

109

1012

1015

1018

1021

Wavele

ngth

(m

)

Frequency

(H

z) Long-wave radio

Short-wave radio

TV

Microwave

Infrared

Ultraviolet

X-rays

Gamma rays

Cosmic rays

Visible spectrum

Only a small part of the EM* spectrum is visible to us. This part is known as the

visible spectrum. Wavelength in the region

of 380 nm to 750 nm.

*Electro-Magnetic

3

Light and the Human Eye When we focus on an image, light from the image

enters the eye through the cornea and the pupil.

The light is focused by the lens onto the retina.

Lens

Pupil

Cornea

Iris

Retina

Opticnerve

Fovea

4

Rods and Cones

When light reaches the retina, one of two kinds of light sensitive cells are activated.

These cells, called rods and cones, translate the image into electrical signals.

The electrical signals are transmitted through the optical nerve, and to the brain, where we will perceive the image.

light

ConeRod

Retina

5

Rods: Twilight Vision 130 million rod cells per eye.

1000 times more sensitive to light than cone cells.

Most to green light (about 550-555 nm), but with a broad range of response throughout the visible spectrum.

Produces relatively blurred images, and in shades of gray.

Pure rod vision is also called twilight vision.

Relative neural response of rods as a function of light wavelength.

400 500 600 700Wavelength (nm)

1.00

0.75

0.50

0.25

0.00

Rela

tive r

esp

onse

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Cones: Color Vision 7 million cone cells per eye.

Three types of cones* (S, M, L), each "tuned" to different maximum responses at:-

S : 430 nm (blue) (2%)

M: 535 nm (green) (33%)

L : 590 nm (red) (65%)

Produces sharp, color images.

Pure cone vision is called photopic or color vision.

Spectral absorption of light by the three cone types

400 500 600 700Wavelength (nm)

1.00

0.75

0.50

0.25

0.00

Rela

tive a

bso

rbti

on

S M L

*S = Short wavelength cone M = Medium wavelength cone L = Long wavelength cone

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Rod vision Cone vision

Photopic vs Twilight Vision There are about 20x more rods than cones in the

eyes, but rod vision is poorer than cone vision.

This is because rods are distributed all over the retina, while cones are concentrated in the fovea.

Rod vision Cone vision

130 million rods

7 million cones

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Eye Color Sensitivity Although cone response

is similar for the L, M, and S cones, the number of the different types of cones vary.

L:M:S = 40:20:1 Cone responses typically

overlap for any given stimulus, especially for the M-L cones.

The human eye is most sensitive to green light.

Spectral absorption of light by the three cone types

400 500 600 700Wavelength (nm)

1.00

0.75

0.50

0.25

0.00

Rela

tive a

bso

rbti

on

S M L

S, M, and L cone distribution in the fovea

Effective sensitivity of cones (log plot)

400 500 600 700Wavelength (nm)

1.00

0.1

0.01

0.001

0.0001

Rela

tive s

ensi

tivit

y

S

M L

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Theory of Trichromatic Vision The principle that the color

you see depends on signals from the three types of cones (L, M, S).

The principle that visible color can be mapped in terms of the three colors (R, G, B) is called trichromacy.

The three numbers used to represent the different intensities of red, green, and blue needed are called tristimulus values.

=

Tristimulus values

r g b

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Seeing Colors The colors we perceive

depends on:-Illumination

source

Illumination sourceObject

reflectancefactor

Object reflectance

Observerspectral

sensitivity

Observer response

Observerresponse

=

Tristimulus values(Viewer response)

r g b

x

x

The product of these three factors will produce the sensation of color.

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Additive Colors Start with Black – absence of any

colors. The more colors added, the brighter it gets.

Color formation by the addition of Red, Green, and Blue, the three primary colors

Examples of additive color usage:- Human eye Lighting Color monitors Color video cameras Additive color wheel

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Subtractive Colors Starts with a white background

(usually paper).

Use Cyan, Magenta, and/or Yellow dyes to subtract from light reflected by paper, to produce all colors.

Examples of Subtractive color use:- Color printers Paints

Subtractive color wheel

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Using Subtractive Colors on Film

Color absorbing pigments are layered on each other. As white light passes through each layer, different

wavelengths are absorbed. The resulting color is produced by subtracting

unwanted colors from white.

White light

Pigment layers

Reflecting layer (white paper)

M

YC

B R

G

K

W

Green Red Blue Black White

Cyan

Yellow Magenta Cyan

MagentaYellow

Black

14

Color Matching Experiment1. Observer views a split screen of

pure white (100% reflectance).

2. On one half, a test lamp casts a pure spectral color on the screen.

3. On the other, three lamps emitting variable amounts of red, green, and blue light are adjusted to match the color of the test light.

4. The amounts of red, green and blue light used to match the pure colors were recorded when an identical match was obtained.

5. The RGB tristimulus values for each distinct color was obtained this way.

Color matching experimental setup

Test Light

Tristimulus values

PrimaryMixture

15

380 480 580 680 780Wavelength (nm)

0

9

Re

lati

ve

po

we

r

The dashed line represents daylight reflected from sunflower, while the solid line represents the light emitted from the color monitor adjusted to match the color of the sunflower.

Metamerism Spectrally different lights

that simulate cones identically appear identical.

Such colors are called color metamers.

This phenomena is called metamerism.

Almost all the colors that we see on computer monitors are metamers.

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The Mechanics of Metamerism Under trichromacy, any color

stimulus can be matched by a mixture of three primary stimuli.

Metamers are colors having the same tristimulus values R, G, and B; they will match color stimulus C and will appear to be the same color.

Wavelength (nm)780380 480 580 680

0

9

Re

lati

ve

po

we

r

The two metamers look the same because they have similar tristimulus values.

Wavelength (nm)780380 480 580 680

0

9

Re

lati

ve

po

we

r

Wavelength (nm)780380 480 580 680

0

9

Re

lati

ve

po

we

r

780

380

780

380

780

380

R S r d

G S g d

B S b d

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Gamut A gamut is the range of

colors that a device can render, or detect.

The larger the gamut, the more colors can be rendered or detected.

A large gamut implies a large color space.

00

0.2 0.4 0.6 0.8

0.2

0.4

0.6

0.8

x

y

Human vision gamut

Monitor gamut

Photographic film gamut

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Color Spaces A Color Space is a method by which colors are

specified, created, and visualized.

Colors are usually specified by using three attributes, or coordinates, which represent its position within a specific color space.

These coordinates do not tell us what the color looks like, only where it is located within a particular color space.

Color models are 3D coordinate systems, and a subspace within that system, where each color is represented by a single point.

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Color Spaces Color Spaces are often geared towards specific

applications or hardware.

Several types:-HSI (Hue, Saturation, Intensity) basedRGB (Red, Green, Blue) basedCMY(K) (Cyan, Magenta, Yellow, Black) basedCIE basedLuminance - Chrominance based

CIE: International Commission on Illumination

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RGB* One of the simplest color models.

Cartesian coordinates for each color; an axis is each assigned to the three primary colors red (R), green (G), and blue (B).

Corresponds to the principles of additive colors.

Other colors are represented as an additive mix of R, G, and B.

Ideal for use in computers.

*Red, Green, and Blue

Black(0,0,0)

Cyan(0,1,1)

Green(0,1,0)

Yellow(1,1,0)

Red(1,0,0)

Magenta(1,0,1)

Blue(0,0,1)

White(1,1,1)

RGB Color Space

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RGB Image Data

Red Channel

Green Channel

Full Color Image

Blue Channel

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CMY(K)* Main color model used in the

printing industry. Related to RGB.

Corresponds to the principle of subtractive colors, using the three secondary colors Cyan, Magenta, and Yellow.

Theoretically, a uniform mix of cyan, magenta, and yellow produces black (center of picture). In practice, the result is usually a dirty brown-gray tone. So black is often used as a fourth color.

*Cyan, Magenta, Yellow, (and blacK)

Magenta

YellowCyan

Blue Red

Green

Black

White

Producing other colors from subtractive colors.

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CMY Image Data

Full Color Image Cyan Image (1-R)

Magenta Image (1-G) Yellow Image (1-B)

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CMY – RBG Transformation

The following matrices will perform transformations between RGB and CMY color spaces.

Note that:- R = Red G = Green B = Blue C = Cyan M = Magenta Y = Yellow All values for R, G, B

and C, M, Y must firstbe normalized.

1

1

1

C R

M G

Y B

1

1

1

R C

G M

B Y

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CMY – CMYK Transformations The following matrices will perform transformations between

CMY and CMYK color spaces.

Note that:- C = Cyan M = Magenta Y = Yellow K = blacK All values for R, G, B

and C, M, Y, K must firstbe normalized.

min( , , )

( ) (1 )

( ) (1 )

( ) (1 )

K C M Y

C C K K

M M K K

Y Y K K

min(1, (1 ) )

min(1, (1 ) )

min(1, (1 ) )

C C K K

M M K K

Y Y K K

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RGB – CMYK Transformations The following matrices perform transformations between RGB

and CMYK color spaces.

Note that:- R = Red G = Green B = Blue C = Cyan M = Magenta Y = Yellow All values for R, G, B

and C, M, Y must firstbe normalized.

1 min(1, (1 ) )

1 min(1, (1 ) )

1 min(1, (1 ) )

R C K K

G M K K

B Y K K

min(1 ,1 ,1 )

(1 ) (1 )

(1 ) (1 )

(1 ) (1 )

K R G B

C R K K

M G K K

Y B K K

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RGB – Gray Scale Transformations The luminancy component, Y, of each color is summed to

create the gray scale value.

ITU-R Rec. 601-1* Gray scale:

Y = 0.299R + 0.587G + 0.114B

ITU-R Rec. 709 D65 Gray scale

Y = 0.2126R + 0.7152G + 0.0722B

ITU standard D65 Gray scale (Very close to Rec 709!)

Y = 0.222R + 0.707G + 0.071B*601-1: Based on an old television (NTSC: National Television System Committee) standard 709 : Based on High Definition TV colorimetry (Contemporary CRT phosphors) ITU : International Telecommunication Union

28

RGB and CMYK Deficiencies RGB and CMY color models

limited to brightest available primaries (R, G, and B) and secondaries (CYM).

Not intuitive. We think of light in terms of color, intensity of color, and brightness. Colors changed by changing

R, G, B ratios. Brightness changed by

changing R, G, and B, while maintaining their ratios.

Intensity changed by projecting RGB vector toward largest valued primary color (R, G, or B).

00

0.2 0.4 0.6 0.8

0.2

0.4

0.6

0.8

x

y

Monitor RGB gamut

Photographic film gamut

6 colorCMY printer

gamut

Hexachrome: Cyan, Magenta, Yellow, Black, Orange, Green

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HSI / HSL / HSV* Very similar to the way human visions see color.

Works well for natural illumination, where hue changes with brightness.

Used in machine color vision to identify the color of different objects.

Image processing applications like histogram operations, intensity transformations, and convolutions operate on only an image's intensity and are performed much easier on an image in the HSI color space.

*H=Hue, S = Saturation, I (Intensity) = B (Brightness), L = Lightness, V = Value

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HSI Color Space Hue

What we describe as the color of the object.

Hues based on RGB color space. The hue of a color is defined by

its counterclockwise angle from Red (0°); e.g. Green = 120 °, Blue = 240 °.

RGB Color Space

RGB cube viewed fromgray-scale axis

RGB cube viewed from gray-scale axis, and

rotated 30°HSI Color Wheel

Red 0º

Green 120º

Blue 240º

Saturation Degree to which hue differs from

neutral gray. 100% = Fully saturated, high

contrast between other colors. 0% = Shade of gray, low contrast. Measured radially from intensity

axis.

0% Saturation 100%

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HSI Color Space Intensity

Brightness of each Hue, defined by its height along the vertical axis.

Max saturation at 50% Intensity.

As Intensity increases or decreases from 50%, Saturation decreases.

Mimics the eye response in nature; As things become brighter they look more pastel until they become washed out.

Pure white at 100% Intensity. Hue and Saturation undefined.

Pure black at 0% Intensity. Hue and Saturation undefined.

Hue

Saturation 0%100%

Intensity 100%

0%

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HSI Image Data

Hue Channel

Saturation Channel Intensity Channel

Full Image

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HSI - RGB For a given RGB color of (R, G, B), the same color in the HSI Model

is C(x,y) = (H, S, I), where

1

2

( ) ( )2cos in [0,180 )

( ) ( )( )

R G R B

R G R B G B

where

min , ,1 3

R G BS

R G B

Saturation

for , , [0,1]3

R G BI R G B

Intensity

, if

360 , if

B GH

B G

Hue

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RGB to HSI Example Consider the RGB color defined by (215, 97,198)

R = 215, G = 97, B = 198

1

2

(215 97) (215 198) 2cos 51.68

(215 97) (215 198)(97 198)

min 215,97,198 971 3 1 3 0.843

215 97 198 215 97 198S

215 255 97 255 198 2550.67

3I

, if 360 51.68 308.64

360 , if

B GH

B G

Green(0,255,0)

Red(255,0,0)

Blue(0,0,255)

Blue240º

Green120º

Red0º

Therefore, HSI coordinates = (308.64°, 0.843, 0.67)

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HSI to RBG Dependent on which sector H lies in.

Blue240º

Green120º

Red0º

For 120º H 240 º 120

1(1 )

3

1 cos( )1

3 cos(60 )

1 ( )

H H

r S

S Hg

H

b r g

For 240º H 360 º

240

11

3

1 cos1

3 cos(60 )

1 ( )

H H

g S

S Hb

H

r g b

For 0º H 120 º

11

3

1 cos1

3 cos(60 )

1 ( )

b S

S Hr

H

g r b

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HSV Color Space Hue and Saturation similar to that

of HSI color model.

V: Value; defined as the height along the central vertical axis.

Like Intensity in HSI, color intensity increases as Value increases.

HSV: Hue, Saturation, and Value

Hue

Saturation 0%100%

Valu

e

100%

0%

37

HSV Color Space

Smax at V100

Value

Smax at I50

Intensity

Hue and Saturation similar to that of HSI color model.

V: Value; defined as the height along the central vertical axis.

Like Intensity in HSI, color intensity increases as Value increases.

As Value increases, hues become more saturated. Hues do not progress through the pastels to white, just as fluorescent images never change colors even though its intensity may increase. HSV is good for working with fluorescent colors.

HSV: Hue, Saturation, and Value

38

Intensity Operations in HSI To change the individual color

of any region in the RGB image, change the value of the corresponding region in the Hue image.

Then convert the new H image with the original S and I images to get the transformed RGB image.

Saturation and Intensity components can likewise be manipulated.

Hue

Saturation Intensity

Original Image

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Disadvantages of HSI Color ModelThere are many disadvantages to the HS color model. For example:

Cannot perform addition of colors expressed in polar coordinates. Transformations are very difficult because Hue is expressed as an angle.

For color machine vision, the hues of low-saturation may be difficult to determine accurately. Systems which must be able to differentiate all colors, saturated and unsaturated, will have significant problems using the HSI representation.

When saturation is zero, hue is undefined.

Transforming between HSI and RGB is complicated.

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1931 CIE* Standard Observer(r, g, b)

The following color matching functions were obtained.

There were problems with the r, g, b color matching functions.

Negative values meant that the color had to be added to the test light before the two halves could be balanced.

380 480 580 680 780Wavelength (nm)

Tris

timu

lus

valu

es

0.3

0.2

0.1

0.0

-0.1

0.4

r

g

b

Color-matching functions for 1931 Standard Observer, the average of 17 color-normal observers having matched each wavelength of the equal energy spectrum with primaries of 435.8nm, 546.1 nm, and 700 nm, on a bipartite 2° field, surrounded by darkness.

*Commission Internationale de L’Éclairage

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1931 CIE Standard Observer(x, y, z)

CIE adopted another set of primary stimuli, designated as X, Y, and Z.

Special properties of X, Y, Z:-

Imaginary (non-physical) primary.

All luminance information is contributed by Y.

Linearly related to R, G, B. Non-negative values for all

tristimulus values.

380 480 580 680 780Wavelength (nm)

2.0

1.5

1.0

0.5

0.0T

ristim

ulu

s va

lue

s

z

xy

1931 standard observer (2° observer).

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CIE 1931 xy Chromaticity Diagram 2D projection of 3D CIE XYZ

color space onto X+Y+Z=1 plane.

x and y calculated as follows:-

The chromaticity of a color is determined by (x,y).

Xx

X Y Z

Y

yX Y Z

1Z

z x yX Y Z

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CIE 1931 xy Chromaticity Diagram For color C, where

C 0.5 X + 0.4 Y + 0.1 Z

Color C is represented as (0.5, 0.4) on the Chromaticity diagram.

0.50.5

0.5 0.4 0.10.4

0.40.5 0.4 0.1

0.11 0.5 0.4 0.1

0.5 0.4 0.1

x

y

z

(0.5, 0.4)

44

CIE 1931 xyY Chromaticity Diagram

Each point on xy corresponds to many points in the original 3D CIE XYZ space.

Color is usually described by xyY coordinates, where Y is the luminance, or lightness component of color.

Y starts at 0 from the white spot (D65) on the xy plane, and extends perpendicularly to 100.

As the Y increases, the colors become lighter, and the range of colors, or gamut, decreases.

45

CIE XYZD65 to sRGB* The following transformations allow transformations between

CIE XYZD65 and the sRGB color models.

65

0.412453 0.357580 0.180423

0.212671 0.715160 0.072169

0.019334 0.119193 0.950227D sRGB

X R

Y G

Z B

65

3.240479 1.537150 0.498535

0.969256 1.875992 0.041556

0.055648 0.204043 1.057311sRGB D

R X

G Y

B Z

*sRGB = Standard RGB, the standard for Internet use.

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CIE XYZRec. 609-1 - RGB The following are the transformations needed to convert

between CIE XYZRec.609-1 and RGB.

601

0.609 0.174 0.200

0.299 0.578 0.114

0.000 0.066 1.116

X R

Y G

Z B

601

1.910 0.532 0.288

0.985 1.999 0.028

0.058 0.118 0.898

R X

G Y

B Z

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CIE XYZ - RGBRec. 709

Use the following matrices to transform between CIE XYZ and Rec. 709 RGB (with its D65 white).

709

709

709

3.240479 1.537150 0.498535

0.969256 1.875992 0.041556

0.055648 0.0204043 1.057311

R X

G Y

B Z

709

709

709

0.412453 0.357580 0.180423

0.212671 0.715160 0.072169

0.019334 0.119193 0.950227

X R

Y G

Z B

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XYZD65 - XYZD50 Transformations If the illuminant is changed from D50 to D65, the observed

color will also change.

The following matrices enable transformations between XYZD65 and XYZD50.

50 65

1.0479 0.0229 0.0502

0.0296 0.9904 0.0171

0.0092 0.0151 0.7519D D

X X

Y Y

Z Z

65 50

0.9555 0.0231 0.0633

0.0283 1.0100 0.0211

0.0123 0.0206 1.3303D D

X X

Y Y

Z Z

49

Inadequacies in the 1931 xy Chromaticity Diagram

Each line in the diagram represents a color difference of equal proportion.

The lines vary in length, sometimes greatly, depending on what part of the diagram they're in.

The differences in line length indicates the amount of distortion between parts of the diagram.

50

CIE 1960 u,v Chromaticity Diagram

To correct for the deformities in the 1931 xy diagram, a number of uniform chromaticity scale (UCS) diagrams were proposed.

The following formula transforms the XYZ values or x,y coordinates to a set of u,v values, which present a visually more accurate 2D model.

4 4

15 3 2 12 3

6 6

15 3 2 12 3

X xu

X Y Z x y

X yv

X Y Z x y

51

CIE 1976 u', v' Chromaticity Diagram

But the 1960 uv diagram was still unsatisfactory.

In 1975, CIE modified the u,v diagram and by supplying new (u',v') values. This was done by multiplying the v values by 1.5. Thus in the new diagram u' = u and v' = 1.5v.

The following formulas allow transformation between u’v’ and xy coordinates.

'

'

4 4

15 3 2 12 3

9 9

15 3 2 12 3

X xu

X Y Z x y

X yv

X Y Z x y

'

' '

'

' '

27

18 48 36

12

18 48 36

ux

u v

vy

u v

52

CIE 1976 u', v' Chromaticity Diagram

Each line in the diagram represents a color difference of equal proportion.

While the representation is not perfect (it can never be), the u',v' diagram offers a much better visual uniformity than the xy diagram.

53

CIE L*u*v* Color Space/ CIELUV Replaces uniform lightness

scale Y with L*, an visually linear scale.

Equations are as follows:-

where un’ and vn’ refer the the reference white light or light source.

* 13 *( ' ')nu L u u * 13 *( ' ')nv L v v

1

3* 116 16 0.008856

903.3 0.008856

n n

n n

Y YL if

Y Y

Y Yif

Y Y

54

CIE L*a*b* Color Space / CIELAB Second of two systems adopted by CIE in

1976 as models that better showed uniform color spacing in their values.

Based on the earlier (1942) color opposition system by Richard Hunter called L, a, b.

Very important for desktop color.

Basic color model in Adobe PostScript (level 2 and level 3)

Used for color management as the device independent model of the ICC* device profiles.

CIE L*a*b* color axes

*International Color Consortium

55

CIE L*a*b* (cont’d) Central vertical axis : Lightness (L*),

runs from 0 (black) to 100 (white).

a-a' axis: +a values indicate amounts of red, -a values indicate amounts of green.

b-b' axis, +b indicates amounts of yellow; -b values indicates amounts of blue. For both axes, zero is neutral gray.

Only values for two color axes (a*, b*) and the lightness or grayscale axis (L*) are required to specify a color.

CIELAB Color difference, E*ab, is between two points is given by:

+a

-a

-b

+b

100

0

L*

CIE L*a*b* color axes

(L1*, a1*, b1*)

(L2*, a2*, b2*)

2 2 2* ( *) ( *) ( *)abE L a b

56

CIELAB Image Data

Full Color Image L data

L-a channel L-b channel

57

XYZ to CIELAB Given Xn, Yn, and Zn, which are the tristimulus values for the

reference white, for a point X, Y, Z:-

* 500n n

X Ya f f

X Y

* 200n n

Y Zb f f

Y Z

1

3 if 0.00886 16

7.787 if 0.00886116

where f

1

3

If 0.008856 then * 116 16 else * 903.3n n n

Y Y YL L

Y Y Y

58

CIELAB to XYZ Reverse transformation to XYZ, given L*a*b* values.

For

3* 16

116n

LY Y

3* 16 *

116 200n

L bZ Z

3* 16 *

116 500n

L aX X

0.008856n

Y

Y

59

CIE L*C*h* (LCh) Often referred to simply as LCh. Same system is the same as the

CIELab color space, except that it describes the location of a color in space by use of polar coordinates rather than rectangular coordinates.

L* is a measure of the lightness of a sample, ranging from 0 (black) to 100 (white).

C* is a measure of chroma (saturation), and represents distance from the neutral axis.

h is a measure of hue and is represented as an angle ranging from 0° to 360.

H (Hue)

C* (Chroma) 0%100%

L* (

Lightn

ess

)

100%

0%

60

Y’U’V’1 (EBU2) Color Space

Standard color space used for analogue television transmissions in European TVs (PAL3 and SECAM4).

Y is the luminance (or luma) or black and white component

U and V represent the color differences: U = B - Y; V = R - Y

U represents the Blue - Yellow axis; V, the Red - Green axis.

Gamma for PAL is assumed to be 2.8

1 Y = Luminance, U and V are chrominance components2 European Broadcasting Union3 Phase Alternation Line video standard for Europe; U = 0.492(B-Y); V = 0.877(R-Y)4 Sequential Couleur avec Mémoire, video standard for France, the Middle East and most of Eastern Europe

Red: xR = 0.630 yR = 0.340

Green: xG = 0.310 yG = 0.595

Blue: xB = 0.155 yB = 0.070

White xW= 0.312713 yW = 0.329016

61

Y'UV Channels

Full Color Image Y

U (Blue - Yellow) V (Red - Green)

62

Nonlinear Y’U’V’Transformations

The following matrices allow transformations of nonlinear signals between Y’U’V’ and R’G’B.

' 0.299 0.587 0.114 '

' 0.147 0.289 0.436 '

' 0.615 0.515 0.100 '

Y R

U G

V B

' 1.000 0.000 1.140 '

' 1.000 0.396 0.581 '

' 1.000 2.029 0.000 '

R Y

G U

B V

63

Linear Y’U’V’ Transformations The following matrices allow transformations of linear signals

between YUV RGB and XYZ.

1.000 0.000 0.140

1.000 0.396 0.581

1.000 2.029 0.000

R Y

G U

B V

0.431 0.342 0.178

0.222 0.707 0.071

0.020 0.130 0.939

X R

Y G

Z B

64

Y’I’Q’1 Color Space

Used in NTSC2 color broadcasting in USA; compatible with black and white television, which only uses Y.

U and V defines colors clearly, but do not align with desired human perceptual sensitivities.

Y [0..1] is the luminance (or luma) component.

I [-0.523 .. 0.523] represents the Orange-Blue axis.

Q [-0.596 .. 0.596] represents the Purple-Green axis.

1Y’I’Q’ = Luminance, In-phase, and Quadrature phase.2National Television Standards Committee video standard for North America

Red: xR = 0.67yR = 0.33

Green: xG = 0.21 yG = 0.71

Blue: xB = 0.14yB = 0.08

White xW= 0.310063 yW = 0.316158

65

YIQ Channels

Full Color Image Y Channel

Q (Purple - Green)I (Orange - Blue)

66

Y’I’Q’ – R’G’B’ Use the following matrices to transform linear signals between

Y’I’Q’ and gamma-corrected RGB values.

' 1.000 0.956 0.621 '

' 1.000 0.272 0.647 '

' 1.000 1.105 1.702 '

R Y

G I

B Q

' 0.299 0.587 0.114 '

' 0.596 0.275 0.321 '

' 0.212 0.523 0.311 '

Y R

I G

Q B

67

YIQ - YUV YIQ - YUV transformation is simply a color rotation of 33º. The following matrices can be used to transform between

NTSC based YIQ and PAL based YUV.

1.000 0.000 0.000

0.000 0.2676 0.7361

0.000 0.3869 0.4596

YIQ YUVY Y

I U

Q V

1.000 0.000 0.000

0.000 1.270 1.8050

0.000 0.9489 0.6561

YUV YIQY Y

U I

V Q

68

Y’CbCr* Color Space

Y’ is luminance, Cb is the chromaticity component for blue, and Cr is the chromaticity component for red.

Very closely related to the YUV, it is a scaled and shifted YUV.

Cb = (B - Y) / 1.772 + 0.5 Cr = (R - Y) / 1.402 + 0.5

Chrominance values Cb and Cr are [ 0..1 ].

Deals only with digital representation of R’G’B’ signals in Y’CbCr

form.

Color format for JPEG1 and MPEG2.

Independent of scanning standard and system primaries, therefore:- No chromaticity coordinates. No CIE XYZ matrices. No assumptions about white point. No assumptions about CRT gamma.

1JPEG = Joint Photography Experts Group2MPEG = Motion Pictures Experts Group

69

Y'CbCr - RGB[0..+1]

Use the following matrices to convert between YCbCr and RGB ranging from [0 .. +1]

'601 16 65.481 128.553 24.996 '

128 37.797 74.203 112.000 '

128 112.000 93.786 18.214 'B

R

Y R

C G

C B

'601' 0.00456621 0 0.00625893 16

' 0.00456621 0.00153632 0.00318811 128

' 0.00456621 0.00791071 0 128B

R

R Y

G C

B C

70

ITU-R.601 YCbCr - R’G’B’219 ITU-R.601 defines 16 =< Y >= 235, and 16 =< Cb and Cr >= 240,

with 128 corresponding to 0. These BT.601 equations are used by many video ICs to convert

between digital R’G’B’ and BT.601 YCbCr data.

0.301 0.586 0.113 ' 0

0.172 0.340 0.512 ' 128

0.512 0.430 0.082 ' 128b

r

Y R

C G

C B

ITU-R.601 = International Telecommunication Union – Radio communications Recommendation 601RGB219 = A restricted color space used to match YUV standard transmission values

' 1.000 0.000 1.371 16

' 1.000 0.336 0.698 128

' 1.000 1.732 0.000 128b

r

R Y

G C

B C

The R’G’B’ values produced have a nominal range of 16 - 235.

71

ITU-R.601 YCbCr - R’G’B’0-255 If 24 bit R’G’B’ data needs to have a range of 0-255, the following

equation should be used. The R’, G’, and B’ values must be saturated at the 0 and 255

values.

0.257 0.504 0.098 ' 16

0.148 0.291 0.439 ' 128

0.439 0.368 0.071 ' 128b

r

Y R

C G

C B

' 1.164 0.000 1.596 16

' 1.164 0.392 0.813 128

' 1.164 2.017 0.000 128b

r

R Y

G C

B C

72

YCbCr 4:4:4 Full resolution YCbCr 4:4:4 is in

uncompressed data format. Each pixel has all Y, Cb and

Cr values.

Chrominance data can be subsampled without significant degradation in image quality.

YCbCr 4:4:4

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

73

YCbCr 4:4:4

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCbCr 4:2:2 Obtained by a 2:1 horizontal

subsampling of YCbCr 4:4:4 values.

Often used digital cameras, and many video ICs.

Restore original colors by interpolating missing Cb and Cr values from the values present.

YCb Cr

Y

YCb Cr

Y

YCb Cr

Y

YCb Cr

Y

YCb Cr

Y

YCb Cr

Y

YCb Cr

Y

YCb Cr

Y

YCbCr 4:2:2

74

YCbCr 4:2:0 YCbCr 4:2:0 obtained by a

2:1 horizontal and vertical subsampling of YCbCr 4:4:4 values.

YCbCr (or, often called “YUV”) values are often subsampled to 4:2:0 before JPEG compression.

Restore original colors by interpolating missing Cb and Cr values from available values.

YCbCr 4:4:4

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

Y

Y Y

YCb Cr

Y

Y Y

YCb Cr

Y

Y Y

YCb Cr

Y

Y Y

YCbCr 4:2:0

75

YCbCr 4:4:4

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCbCr 4:1:1 YCbCr 4:1:1 obtained by a

4:1 horizontal subsampling of YCbCr 4:4:4 values.

VHS* quality color.

Y YCb Cr

Y YCb Cr

Y YCb Cr

Y YCb Cr

Y Y

Y Y

Y Y

Y Y

YCbCr 4:1:1

VHS: Video Home System

76

YCbCr 4:2:2 - RGB1. Convert YCbCr 4:2:2 to YCbCr 4:4:4, through

interpolation.

YCb Cr

Y

YCb Cr

Y

YCb Cr

Y

YCb Cr

Y

YCb Cr

Y

YCb Cr

Y

YCb Cr

Y

YCb Cr

Y

YCbCr 4:2:2

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCb Cr

YCbCr 4:4:4

Interpolation of Cb and Cr

values

77

YCbCr 4:2:2 - RGB

' 0.299 0.587 0.114 '

0.169 0.331 0.500 '

0.500 0.419 0.081 'b

r

Y R

C G

C B

' 1.000 0.000 1.403 '

' 1.000 0.344 0.714

' 1.000 1.773 0.000b

r

R Y

G C

B C

1. Convert YCbCr 4:2:2 to YCbCr 4:4:4, through interpolation.

2. Convert YCbCr 4:4:4 to nonlinear R’G’B’.

78

YCbCr 4:2:2 - RGB

'255 255

4.5

'255 255

4.5

'255 255

4.5

RR

GG

BB

1. Convert YCbCr 4:2:2 to YCbCr 4:4:4, through interpolation.

2. Convert YCbCr 4:4:4 to nonlinear R’G’B’.

3. If necessary, convert nonlinear R’G’B’ to linear RGB by removing gamma information.

For (R’, G’, B’) < 21 For (R’, G’, B’) 212.2

2.2

2.2

' 0.0992552551.099

' 0.0992552551.099

' 0.0992552551.099

RR

RG

RB

79

SMPTE*-C RGB Color Space

Current color standard for broadcasting in America, replacing older NTSC standard.

Reason for standard change: original set of (YIQ) primaries being slowly changed to YUV primaries.

CRT gamma assumed to be 2.2 with NTSC, 2.8 with PAL.

*Society of Motion Picture and Television Engineers

Red: xR = 0.630 yR = 0.340

Green: xG = 0.310 yG = 0.595

Blue: xB = 0.155 yB = 0.070

White xW= 0.312713 yW = 0.329016

80

Linear SMPTE-C RGB Transformations

The following matrices allow transformations of linear signals between SMPTE-C RGB and XYZ.

0.3935 0.3653 0.1916

0.2124 0.7011 0.0866

0.0187 0.1119 0.9852SMPTE C

X R

Y G

Z B

3.5058 1.7397 0.5440

1.0690 1.9778 0.0352

0.0563 0.1970 1.0501SMPTE C

R X

G Y

B Z

81

Nonlinear SMPTE-C RGB Transformation

The transformation matrices for non-linear signals are the same as that of the older YIQ (NTSC) standard.

' 1.000 0.956 0.621 '

' 1.000 0.272 0.647 '

' 1.000 1.105 1.702 '

R Y

G I

B Q

' 0.299 0.587 0.114 '

' 0.596 0.275 0.321 '

' 0.212 0.523 0.311 '

Y R

I G

Q B

82

ITU.BT-709 in Y'CbCr

Recent standard, defined only as an interim standard for HDTV studio production.

Defined by the CCIR (now the ITU-R) in 1988, but is not yet recommended for use in broadcasting.

The primaries are the R and B from the EBU, and a G which is midway between SMPTE-C and EBU.

CRT gamma is assumed to be 2.2.

Red: xR = 0.64yR = 0.33

Green: xG = 0.30 yG = 0.60

Blue: xB = 0.15yB = 0.06

White (D65): xW= 0.312713 yW = 0.329016

ITU: International Telecommunication UnionCCIR: Comite Consultatif International des Radiocommunications

83

Linear XYZ Rec.709 – RGBD65

The following matrices allow transformation between linear signals of Rec.709 XYZ values and RGBD65.

709 65

709 65

709 65

0.412 0.358 0.180

0.213 0.715 0.072

0.019 0.119 0.950

D

D

D

X R

Y G

Z B

65 709

65 709

65 709

3.241 1.537 0.499

0.969 1.876 0.042

0.056 0.204 1.057

D

D

D

R X

G Y

B Z

84

RGBEBU – RGB709 The following matrices allow transformation between linear Rec.

709 RGB signals and EBU* RGB signals.

709

709

709

0.9578 0.0422 0.0000

0.0000 1.0000 0.0000

0.0000 0.0118 0.9882

EBU

EBU

EBU

R R

G G

B B

709

709

709

1.0440 0.0440 0.0000

0.0000 1.0000 0.0000

0.0000 0.0119 1.0119

EBU

EBU

EBU

R R

G G

B B

European Broadcasting Union

85

Nonlinear Y’CbCr 709– R’G’B’ The following matrices allow transformation between nonlinear Rec.709

Y’CbCr signals and R’G’B’. Scaling optimized for digital video.

' 1.0000 0.0000 1.5701 '

' 1.0000 0.1870 0.4664

' 1.000 1.8556 0.0000b

r

R Y

G C

B C

' 0.2215 0.7154 0.0721 '

0.1145 0.3855 0.5000 '

0.5016 0.4556 0.0459 'b

r

Y R

C G

C B

86

SMPTE-240M Y’PbPr (HDTV*)

This one of the developments of NTSC component coding, in which the B primary and white point were changed. With this space color, all three components Y’, Pb, and Pr are linked to luminance.

Standard for coding High Definition TV broadcasts in the USA.

The CRT gamma law is assumed to be 2.2.

*High Definition TeleVision

Red: xR = 0.67yR = 0.33

Green: xG = 0.21 yG = 0.71

Blue: xB = 0.15yB = 0.06

White xW= 0.312713 yW = 0.329016

87

RGB240M - RGB709

The following transforms between SMPTE* 240M (SMPTE RP 145 or Y'PbPr) RGB to Rec. 709 RGB.

*Society of Motion Picture and Television Engineers 240M = Recommended Standard for USA’s HDTV

240 709

1.065364 0.055391 0.009974

0.019635 1.036361 0.016725

0.001632 0.004414 0.993954M

R R

G G

B B

709 240

0.939555 0.050173 0.010272

0.017775 0.965795 0.016430

0.001622 0.004371 1.005993M

R R

G G

B B

88

RGB240M - RGBEBU

The following transforms from SMPTE 240M (SMPTE RP 145, or YPbPr) RGB into to Rec. 709 RGB.

240

240

240

1.3481 0.3481 0.0000

0.0257 1.0257 0.0000

0.0254 0.0568 1.0822

EBU

EBU

EBU

R R

G G

B B

240

240

240

0.7466 0.2534 0.0000

0.0187 0.9813 0.0000

0.0185 0.0575 0.9240

EBU

EBU

EBU

R R

G G

B B

89

Linear SMPTE-240M XYZ - RGB The following matrices allow linear transformations

between SMPTE-240M XYZ and RGB.

0.567 0.190 0.193

0.279 0.643 0.077

0.000 0.073 1.016

X R

Y G

Z B

2.041 0.564 0.345

0.893 1.816 0.032

0.064 0.130 0.982

R X

G Y

B Z

90

Nonlinear SMPTE-240M Y’PbPr Transformations

The following matrices allow nonlinear transformations between Y’PbPr and R’G’B’.

Scaling suited for component analogue video.

' 0.2122 0.7013 0.0865 '

0.1162 0.3838 0.5000 '

0.5000 0.4451 0.0549 '

Y R

Pb G

Pr B

' 1.000 0.000 1.5756 '

' 1.000 0.2253 0.5000

' 1.000 1.8270 0.0000

R Y

G Pb

B Pr

91

Xerox Corporation Y’E’S’1

Standard proposed by Xerox Corporation.

YES has three components:

Y, or luminancy,

E, or chrominancy of the red-green axis, and

S, chrominancy of the yellow-blue axis.

The following examples assume a CRT gamma of 2.2.

1YES = Luminance, E = red-green chromaticity, S = blue-yellow chromaticity

92

Y’E’S’ to XYZD50 Transformation If you start with non-linear Y’E’S’ values, apply a gamma correction

to convert to linear YES values first:-

Next, apply the following transformation to the linear YES.

2.2

2.2

2.2

'

'

'

YY

E E

SS

50

0.964 0.528 0.157

1.000 0.000 0.000

0.825 0.269 1.289D

X Y

Y E

Z S

93

XYZD50 to YES Transformation First, apply the following transformation matrix to obtain linear

YES from XYZD50.

For non-linear Y’E’S’ values, apply a gamma correction.

1

2.2

1

2.2

1

2.2

'

'

'

YY

E E

SS

50

0.000 1.000 0.000

1.783 1.899 0.218

0.374 0.245 0.734D

Y X

E Y

S Z

94

YES to XYZD65 Transformation As before, if you start with non-linear Y’E’S’ values, apply a

gamma correction to convert to linear YES values first:-

Next, apply the following transformation to the linear YES.

2.2

2.2

2.2

'

'

'

YY

E E

SS

65

0.782 0.466 0.138

1.000 0.000 0.000

0.671 0.237 1.133D

X Y

Y E

Z S

95

XYZD65 to YES Transformation First, apply the following transformation matrix to obtain linear

YES from XYZD50.

If required, apply a gamma correction to obtain Y’E’S’.

1

2.2

1

2.2

1

2.2

'

'

'

YY

E E

SS

65

0.000 1.000 0.000

2.019 1.743 0.246

0.423 0.227 0.831D

Y X

E Y

S Z

96

Kodak Photo CD YCC (YC1C2) Color Space

Based on Rec. 709 and 601-1, the YCC color space has color gamut defined by the Rec. 709 primaries and a luminance - chrominance representation of color like ITU 601-1's YCbCr.

YCC provides a color gamut that is greater than that which can currently be displayed, and is therefore suitable not only for both additive and subtractive (RGB and CMY(K)) reproduction.

Extended color gamut obtainable by the PhotoCD system is achieved by allowing both positive and negative values for each primary, allowing YCC to store more colors than current display devices, such as CRT monitors and dye-sublimation printers, can produce.

97

Transformations to Encode Kodak YC1C2 Data

First, apply a gamma correction:

Next, transform the R’G’B’ data into YC1C2 data.

Scaling is optimized for films.

0.45

0.45

0.45

' 1.099 0.099

' 1.099 0.099

' 1.099 0.099

R R

G G

B B

' 4.5

' 4.5

' 4.5

R R

G G

B B

1

2

0.299 0.587 0.114 '

1 0.299 0.587 0.886 '

2 0.701 0.587 0.114 '

Luma Y R

Chroma C G

Chroma C B

For R709, G709, B709 0.018 For R709, G709, B709 0.018

98

Transformations to Encode YC1C2 Data (cont’d)

Finally, store the floating point values as 8-bit integers.

The unbalanced scale difference between Chroma1 and Chroma2 is designed, according to Kodak, to follow the typical distribution of colors in real scenes.

1

2

8 _ _ 255 1.402

8 _ _ 1 111.40 156

8 _ _ 2 135.64 136

bit Luma Y

bit Chroma C

bit Chroma C

99

Transforming YC1C2 Data to 24-bit RGB

Kodak YCC can store more information than current display devices can cope with (it allows negative RGB values), so the transforms from YCC to RGB are not simply the inverse of RGB to YCC, they depend on the target display system.

First, recover normal Luma (Y) and Chroma (C1 and C2) data.

Second, if the display primaries match Rec. 709 primaries in their chromaticity, then

2

1 2

1

'

' 0.194 0.509

'

R Y C

G Y C C

B Y C

1

2

8 _ _ 1.3584

1 2.2179 (8 _ _ 1 - 156)

2 1.8215 (8 _ _ 2 - 137)

Luma Y bit Luma

Chroma C bit Chroma

Chroma C bit Chroma

100

YC1C2 – RGB Signal Voltages

First, recover normal Luma (Y) and Chroma (C1 and C2).

Then, calculate the RGB display voltages as follows;

'

' 1

' 2

1.000 0.000 1.0001

1.000 0.194 0.509353.2

1.000 1.000 0.000

R

G

B

V Y

V C

V C

1

2

8 _ _ 1.3584

1 2.2179 (8 _ _ 1 - 156)

2 1.8215 (8 _ _ 2 - 137)

Luma Y bit Luma

Chroma C bit Chroma

Chroma C bit Chroma

101

PhotoYCC - YCbCr

1

2

0.713

0.775 56.855

0.746 41.521

YCC YCbCr

b

r

Y Y

C C

C C

Transform YCbCr data into PhotoYCC color space as follows:-

The image produced may not match an image that was one encoded directly in PhotoYCC color space.

1

2

1.402

1.291 73.400

1.340 55.638

YCbCr YCC

b

r

Y Y

C C

C C

Transform PhotoYCC color space into YCbCr values as follows:-

As the PhotoYCC color space is larger than the YCbCr color space, the produced image may be poorer than the original.

102

sRGB specs

sRGB Viewing Environment Summary

Condition sRGB

Display Luminance level 80 cd/m2

Display White Point x = 0.3127, y = 0.3290 (D65)

Display model offset (R, G and B) 0.0

Display input/output characteristic 2.2

Reference ambient illuminance level 64 lux

Reference Ambient White Point x = 0.3457, y = 0.3585 (D50)

Reference Veiling Glare 0.2 cd m-2

CIE chromaticities for ITU-R BT.709 reference primaries and CIE standard illuminant  

Red Green Blue D65 White Point x 0.6400 0.3000 0.1500 0.3127 y 0.3300 0.6000 0.0600 0.3290 z 0.0300 0.1000 0.7900 0.3583

103

Glossary of Color Models

Color Space

Primaries White pt Gamma Rx Ry Gx Gy Bx By Wx Wy Std name

Apple RGB Trinitron D65 1.8 0.63 0.34 0.28 0.6 0.16 0.07 0.31271 0.32902 Trinitron

SMPTE-CSMPTE-C

(CCIR 601-1)D65 2.2 0.63 0.34 0.31 0.6 0.16 0.07 0.31271 0.32902 ?

sRGBHDTV

(CCIR 709)D65 2.2 0.64 0.33 0.3 0.6 0.15 0.06 0.31271 0.32902 CCIR 709

Pal/Secam EBU/ITU D65 2.2 0.64 0.33 0.29 0.6 0.15 0.06 0.31271 0.32902 CIE_XYZitu

Color Match RGB

P22-EBU D50 1.8 0.63 0.34 0.3 0.61 0.16 0.08 0.3457 0.3585 P22-EBU

Adobe RGBAdobe RGB

(1998)D65 2.2 0.64 0.33 0.21 0.71 0.15 0.06 0.31271 0.32902

Adobe RGB (1998)

NTSC (1953) NTSC (1953) Std Illmnt C 2.2 0.67 0.33 0.21 0.71 0.14 0.08 0.31006 0.31616 CCIR 601-1

CIE RGB CIE RGB Std Illmnt E 2.2 0.74 0.27 0.27 0.72 0.17 0.01 0.3333 0.3333 CIE RGB

CCIR: Comite Consultatif International des Radiocommunications

brightness    - the human sensation by which an area exhibits more or less light.lightness     - the sensation of an area's brightness relative to a reference white in the scene. luma          - Luminance component corrected by a gamma function and often noted Y'.chroma        - the colorfulness of an area relative to the brightness of a reference white.saturation    - the colorfulness of an area relative to its brightness.

104

Glossary of Illuminants and Their Reference Whites

Illuminant wx wy

A 0.488 0.407

B 0.348 0.352

C 0.310 0.316

D5500 0.332 0.348

D6500 0.313 0.329

D7500 0.299 0.315

E 0.333 0.333

105

2D Color Spaces

RGB Color Space

HLS Color Space

SMPTE Color Space

NTSC Color Space

ITU Color Space

Rec.709 Color SpaceHSV Color Space

106

References BARCO Introduction to Color Theory, Monitor Calibration and

Color Management, http://www.barco.com/display_systems/support/colorthe/colorthe.htm

R. S. Berns, Principles of Color Technology (3rd Ed)., 2000

S. M. Boker, The Representation of Color Metrics and Mappings in Perceptual Color Space, http://kiptron.psyc.virginia.edu/steve_boker/ColorVision2/ColorVision2.html

D. Bourgin, Color spaces FAQ, http://www.inforamp.net/~poynton/notes/Timo/colorspace-faq, 1996,

R. Buckley, Xerox Corp., G. Bretta, Hewlett-Packard Laboratories, Color Imaging on the Internet, http://www.inventoland.net/imaging/cii/nip01.pdf, 2001

Color Representation, http://203.162.7.85/unescocourse/computervision/comp_frm.htm

107

References (cont’d) A. Ford and A. Roberts, Color Space Conversions,

www.inforamp.net/~poynton/PDFs/coloureq.pdf, 1998

Gonzales, Woods, Digital Image Processing, 2000

A. Kankaanpaa, Color Formats, www.physics.utu.fi/ett/kurssi/sfys3066/arto_tiivis.pdf, 2000.

M. Nielsen and M. Stokes, Hewlett-Packard Company, The Creation of the sRGB ICC Profile, http://www.srgb.com/c55.pdf

C. Poynton, Frequently Asked Questions about Color, http://www.inforamp.net/~poynton/ColorFAQ.html, 1999

C. Poynton, Frequently Asked Questions about Gamma, http://www.inforamp.net/~poynton/GammaFAQ.html, 1999

G. Starkweather, Colorspace interchange using sRGB, http://www.microsoft.com/hwdev/tech/color/sRGB.asp, 2001

108

The End

- Question and Answer Session -