Color and Color Models Werner Purgathofer Color problem - - PDF document

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Einführung in Visual Computing

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Color and Color Models

Werner Purgathofer Color problem specification light and perception l i t colorimetry device color systems color ordering systems color symbolism

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Color - Why Do We Care? Computer Graphics is all about the generation and the manipulation of color images proper understanding and handling of color is proper understanding and handling of color is necessary at every step

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What is Light? “light” = narrow frequency band of electromagnetic spectrum red border: 380 THz ≈ 780 nm violet border: 780 THz ≈ 380 nm

M radio M radio nd TV icrowaves frared traviolet

• rays

visible

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frequency (Hz)

102 104 106 108 1010 1012 1014 1016 1018 1020

AM FM an m inf ult X-

1016 1014 1012 1010 108 106 104 102 100 10-2

wavelength (nm)

… …

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Light - An Electromagnetic Wave light is electromagnetic energy monochrome light can be described either by frequency f or wavelength  q y g c =  f (c = speed of light) shorter wavelength equals higher frequency

E t 

frequency red  700 nm violet  400 nm

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

Light – Spectrum normally, a ray of light contains many different waves with individual frequencies the associated distribution of wavelength g intensities per wavelength is referred to as the spectrum

• f a given ray
• f a given ray
• r light source

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Dominant Wavelength | Frequency white light

energy energy greenish light ED

dominant wavelength | frequency (hue color)

wave- length 700 nm 400 nm wave- length dominant wavelength EW

dominant wavelength | frequency (hue, color) brightness (area under the curve) purity

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D W D

E E E 

ED...dominant energy density EW...white light energy density

The Human Eye retina contains

rods: b/w cones: color

aqueous [Augenkammer] cornea [Hornhaut] iris [Regen- bogen-

cones: color

rods

lens visual axis

• ptical axis

bogen haut] vitreous humor [Glaskörper]

• ptic disc

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cones

fovea macula lutea [gelber Fleck] nerve retina [Netzhaut] p [Papille]

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The Human Eye 3 types of cones diff t different wavelength sensitivities:

red green

fraction of absorbed light 2% 4% 8% 16%

green blue

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1%

400 440 480 520 560 600 640 680

λ

Color Blindness red/green blindness

red & green cones too similar

fraction of absorbed light 2% 4% 8% 16%

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1%

400 440 480 520 560 600 640 680

λ

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Color Blindness red/green blindness

red & green cones too similar

blue blindness

no blue cones

• ther

fraction of absorbed light 2% 4% 8% 16%

• ther

cones missing cones too similar

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1%

400 440 480 520 560 600 640 680

λ

Color Blindness Tests

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5 = normal nothing = red/green blind 2 = red/green weak nothing = normal

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Color Blindness Tests

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8 = normal 3 = red/green weak nothing = r/g blind 8 = red/green blind 12 = blue/yellow blind 182 = normal Color Spaces (CS) Color Metric Spaces (CIE XYZ, L*a*b*)

used to measure absolute values and differences - roots in colorimetry

Device Color Spaces (RGB, CMY, CMYK)

used in conjunction with device

Color Ordering Spaces (HSV, HLS)

used to find colors according to some criterion

the distinction between them is somewhat

• bscured by the prevalence of multi-purpose

RGB in computer graphics

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What is our Goal? to be able to quantify color in a meaningful, expressive consistent and reproducible way expressive, consistent and reproducible way. problem: color is a perceived quantity, not a direct, physical observable

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Color - A Visual Sensation light nerve

• bject

light stimulus eye brain nerve signal electromagnetic rays color sensation

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realm of direct

• bservables

realm of psychology

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Colorimetry CM is the branch of color science concerned with numerically specifying the color of a physically defined visual stimulus in such physically defined visual stimulus in such manner that

stimuli with the same specification look alike under the same viewing conditions stimuli that look alike have the same ifi ti specification the numbers used are continuous functions of the physical parameters

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Colorimetry Properties Colorimetry only considers the visual discriminability of physical beams of radiation f th f C l i t l “ i for the purposes of Colorimetry a „color“ is an equivalence class of mutually indiscriminable beams colors in this sense cannot be said to be “red”, “green” or any other “color name” green or any other color name discriminability is decided before the brain

• Colorimetry is not psychology

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• bservers had to match monochromatic

test lights by combining 3 fixed primaries Color Matching Experiments

green test

test R+G+B

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goal: find the unique RGB coordinates for each stimulus

1 1 1

Color Matching Experiments

• bservers had to match monochromatic

test lights by combining 3 fixed primaries

R = 700.0 nm G = 546.1 nm B = 435.8 nm

viewer controls independently variable primary

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viewing screen test source masking screen p y sources

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Tristimulus Values the values RQ, GQ and BQ

• f a stimulus Q that fulfill

green test test R+G+B

are called the tristimulus values of Q i h f h i i l

Q  RQ  R  GQ  G  BQ  B

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in the case of a monochromatic stimulus Q, the values R, G and B are called the spectral tristimulus values Color Matching Procedure (1) test field = 700 nm-red with radiance Pref

• bserver adjusts luminance of R (G=0, B=0)

(2) test light wavelength is decreased in (2) test light wavelength is decreased in constant steps (radiance Pref stays the same)

• bserver adjusts R, G, B

(3) repeat for entire visible range

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visible range

400 450 500 550 600 650 700 nm 350

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Color Matching Result !?

100

no match possible !?!?

400 450 500 550 600 650 700 nm 350

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400 450 500 550 600 650 700 nm 350

• bservers want to „subtract“

red light from the match side...!? for some colors observers want to reduce red light to negative values…!? but there is no negative light…! Color Matching Experiment Problem g g

green test

test +G+B

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1

t R+

1 1

?

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“Negative” Light in a Color Matching Exp. if a match using only positive RGB values proved impossible, observers could simulate a subtraction of red from the match side by subtraction of red from the match side by adding it to the test side

green test

st + R G+B

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tes G

1 1 1 1 100

CIE RGB Color Matching Functions

r(λ) b(λ)

?

g(λ)

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350 400 450 500 550 600 650 700 nm 435.8 nm 546.1 nm 700.0 nm

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CIE XYZ problem solution: XYZ color system tristimulus system derived from RGB b d 3 i i i i based on 3 imaginary primaries all 3 primaries are imaginary colors

• nly positive XYZ

values can occur! Y values can occur! 1931 by CIE (Commission Internationale de l’Eclairage)

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X Z RGB vs. XYZ negative component disappears y() is the achromatic luminance sensitivity

r(λ) g(λ) b(λ) x(λ) y(λ) z(λ)

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RGB system XYZ system

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350 400 450 500 550 600 650 700 nm 350 400 450 500 550 600 650 700 nm

amounts of RGB primaries needed to display spectral colors amounts of CIE primaries needed to display spectral colors

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CIE Color Model Formulas XYZ color model C() = XX + YY + ZZ (X, Y, Z are primaries) normalized chromaticity values x y normalized chromaticity values x, y ( z = 1 – x – y ) Z Y X X x    Z Y X Y y   

1

Y complete description

• f color: x, y, Y

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1 1

X Z CIE Chromaticity Diagram identifying complementary colors

spectral colors

determining dominant wavelength, purity comparing color gamuts

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spectral color positions are along the boundary curve

purple line

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Properties of CIE Diagram (2)

representing p g complementary colors on the chromaticity diagram

C1 C

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C2 Properties of CIE Diagram (3)

determining dominant wavelength and purity with the

Cs

and purity with the chromaticity diagram C1 → Cs C2 → Cp?

C1 C Csp

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2 p

→ complement Csp

C2 Cp

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Color Spaces (CS) Color Metric Spaces (CIE XYZ, L*a*b)

used to measure absolute values and differences - roots in colorimetry y

Device Color Spaces (RGB, CMY, CMYK)

used in conjunction with device

Color Ordering Spaces (HSV, HLS)

used to find colors according to some criterion

the distinction between them is somewhat

• bscured by the prevalence of multi-purpose

RGB in computer graphics

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RGB Color Model primary colors red, green, blue

white yellow (1,1,0) green (0,1,0) cyan

additive color model (for monitors)

white (1,1,1) red (1,0,0) cyan (0,1,1) blue (0,0,1) black (0,0,0)

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C( C() = R ) = RR + G + GG + B + BB

magenta (1,0,1)

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RGB Color Model Images

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3 views of the RGB color cube Gamuts of RGB Monitors monitor gamuts can be very different no monitor can no monitor can display all colors

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CMY Color Model primary colors cyan, magenta, yellow

red (0 1 1) magenta (0,1,0) blue (1,1,0) black

yellow subtractive color model (for hardcopy devices)

C=G+B, using C

yellow (0,0,1) (0,1,1) cyan (1,0,0) black (1,1,1) white (0,0,0)

“subtracts” R

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                                B G R Y M C 1 1 1

green (1,0,1)

CMY Color Model Images

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3 views of the CMY color cube

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Gamuts of CMY(K) Printers printer gamuts can be very different no printer can no printer can display all colors

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Color Spaces (CS) Color Metric Spaces (CIE XYZ, L*a*b)

used to measure absolute values and differences - roots in colorimetry

Device Color Spaces (RGB, CMY, CMYK)

used in conjunction with device

Color Ordering Spaces (HSV, HLS)

used to find colors according to some criterion

the distinction between them is somewhat

• bscured by the prevalence of multi-purpose

RGB in computer graphics

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Colour Ordering Systems (COS) primary aim: enable the user to intuitively choose colour values according to colour values according to certain criteria choice can yield single

• r multiple colour values

examples: HSV, HLS, Munsell, NCS, RAL Design, Coloroid used in bottom-up parts of a design process sometimes physical samples are provided

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HSV Color Model more intuitive color specification derived from the RGB color model:

when the RGB color cube is viewed along the diagonal from white to black, the color cube

• utline is a hexagon

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RGB Color Cube Color Hexagon

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HSV Color Model Hexcone color components:

hue (H) ( )  [0°, 360°] saturation (S)  [0, 1] value (V)  [0 1]  [0, 1]

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HSV hexcone

HSV Color Model Hexcone color components:

hue (H) ( )  [0°, 360°] saturation (S)  [0, 1] value (V)  [0 1]  [0, 1]

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HSV hexcone

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HSV Color Definition color definition

select hue, S=1, V=1 add black pigments, p g , i.e., decrease V add white pigments, i.e., decrease S

ti f th HSV

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Shades S

cross section of the HSV hexcone showing regions for shades, tints, and tones

HLS Color Model color components:

hue (H) ( )  [0°, 360°] lightness (L)  [0, 1] saturation (S)  [0 1]

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HLS double cone

 [0, 1]

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Color Model Summary Colorimetry:

CIE XYZ: contains all visible colours

Device Color Systems:

RGB: additive device color space (monitors) CMY(K): subtractive device color space (printers) YIQ: television (NTSC) (Y=luminance I=R Y Q=B Y) (Y=luminance, I=R-Y, Q=B-Y)

Color Ordering Systems:

HSV, HLS: for user interfaces

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Color Symbolism: Some Aspects 6 to 11 basic colors categories, hierarchies d d t t t / li ti dependent on context / application large variation in use

what is red? what is blue? what is white? ! what is white? !

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Color in Religion Islam: green Buddhism: yellow orange yellow, orange, red & purple Hinduism:

• range, blue

& blue-violet Christs: liturgical colors without theological connex

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Political Symbol Colors parties revolutions / movements fl flags

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at home

water pipes electrical wires

Color Labeling

electrical wires waste separation

traffic

traffic signs traffic lights traffic lights parking concepts public transport

...

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Color Labeling technology

resistors thermochrome colors thermochrome colors

nature

courtship [Balz] warning colors protective mimicry protective mimicry

[Tarnfarben]

…

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Color Effect: BLUE distance faithfulness, loyality d i desire phantasy male devine peace cold …

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Color Effect: RED blood energy love female rich, noble labor movement warm corrections …

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Color Effect: GREEN profit young love h hope prematurity, unripe poison nature l neutral environment protection …

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Color Effect: YELLOW sun

• ptimism

li ht t enlightenment jealousy [Neid] stinginess [Geiz] warning color warm …

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Color Effect: BLACK end, death sadness ti ti negative emotions bad luck elegance emptiness ld cold …

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Einführung in Visual Computing

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Color and Color Models

The End