Boje i Svetlost Spektri Fundamentals

7/30/2019 Boje i Svetlost Spektri Fundamentals

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Color Image Processing

CS555 Digital Image Processing

Dr. Amar Raheja


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Elements of Colour


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Color Fundamentals

Digital Image Processing 3


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Color Fundamentals



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Color Fundamentals

6 to 7 million cones in the human eye can be divided intothree principal sensing categories, corresponding roughlyto red, green, and blue.

65%: red 33%: green 2%: blue (blue cones are themost sensitive)



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Color Fundamentals



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How we see color

It all depends on how much the differentcones are stimulated

It is possible to have two different spectrathat stimulate cones the same wayoCalled a metamer

To a person, these colors look the same, butthey are (in some sense) completelydifferent


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Some colors do not come from a

single wavelengthThere will never be a purple laserPurple comes from blue (short wavelength)

and red (long wavelength) lightoMore precisely, the sensation that we call purple

comes from the blue and red cones beingstimulated

And no others!


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Human Eye The photosensitive part

of the eye is called theretina.

The retina is largelycomposed of two typesof cells, called rodsandcones. Only the conesare responsible for colorperception.


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Cones Cones are most densely packed

within a region of the eye calledthe fovea

There are three types of cones,referred to as S, M, and L. Theyare roughly equivalent to blue,

green, and red sensors,respectively.o Their peak sensitivities are

located at approximately430nm, 560nm, and 610nm forthe "average" observer.

Spectrum is encoded into threevalues that correspond to eachtype of cone - trichromacy


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Non-uniform distribution

Blue cones are least dense in the foveao3-5%, versus about 8% elsewhere

Red cones are about 33%, fairly evenlydistributed

Green are 64% in the fovea, about 55%elsewhere


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Another way to see this


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Color constancy

As the spectrum of the illuminating lightchanges, so does the pattern of cone

stimulusoYet your red coat looks the same as you walk

outside!

oNo one has a good (computational)understanding of this problem


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How many colors can we see?

Humans can discriminate abouto200 hueso

20 saturation valueso500 brightness steps

The NBS lists 267 color namesWhat about across languages?

oSeem to be about 11 basic ones white, black, red, green, yellow, blue, brown, purple,

pink, orange, gray


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Additive versus subtractive

colorsPaint is colored because of the spectrum it

absorbs(subtracts from the incident light)

oRed paint absorbs non-red photons

oColor filters are another exampleLights have colors because of the spectrum

they emit

oTelevisions and monitors work this wayThe two obey different rules!


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Subtractive colors


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Additive colors


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Cheap versus expensive

camerasCheap color (video) cameras have a single

CCD

oMask in front of the imaging array

oReduces spatial resolutionMore expensive cameras have 3 different

video cameras

oColor output really is 3 different (independent)signals


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Colorin Cameras, Scanners and Monitors isgenerated from 3 primary colors - Red, Green and

Blue

NOTE: The 3 sensors generate 3 monochromeimages (the coloriscreated in the brain)


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In printers, the inks subtractthe lightusing three Subtractive primaries

From the graph above:o Cyan = Green + Blue = -Redo Magenta = Red + Blue = -

Green

oYellow = Red + Green = -Blueo BlacK = - (Red+Blue+Green)

= - White = BLACK

Red

Green Blue

MagentaYellow

Cyan


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Color Spacesare universally agreed

upon descriptions of color

Device

Dependent

RGBCMYK

Device

Independent

XYZCIE L*a*b*


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X and Y and Z (pronounced Cap-

X, Cap-Y, Cap-Z)

TRISTIMULUS values (XYZ) define color numerically

X = S * R *x-barY = S * R * y-bar

Z = S * R * z-bar

Source S()

Reflector R()

Color Matching Functions x-bar, ybar, zbar


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CIE Chromaticity diagramshows all the

colors we see (color gamut of eye)

Represents the XYZ color space Problem: Perceptually NON-UNIFORM


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CIEL*a*b* was motivated by a need for aperceptually uniformcolor space

L* = Lightness (Luminance)(0-100) a* = colors (Chrominance1) from Red to Green b*= (Chrominance2) colors from blue to yellow


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Color Spaces

+source (white point)

+x-bar, y-bar, z-bar

R

G

B

X

Y

Z

+math

(matrix

algebra)

CIE Lab

Device dependent Device In-dependent


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What do we know so far

Coloris a combination of Source, Subjectand Detector

Color Spacesare universally agreedupon, numerical representations of color

o Rgb AND Cmyk are device dependentcolorspaces

o RGB + source + eye = XYZ (a deviceindependent color space)

o XYZ + perceptual uniformity=LabLets manage color !!


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Representing Colour

How can a particular colour be precisely andunambiguously described?

Verbal descriptions such as Dark blue,Bright red, Slimy green are too broad

Description of its spectral density curve, byspecifying its level at a number of

wavelengths is awkward, and too specific,as many different spectral shapes producethe same perceived colour


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Numeric Colour Description

Ideally, every colour should be described uniquelyin some numeric way

How many numbers are required to define acolour?

What coding scheme can be used to map coloursinto numbers, and vice versa?

There are several different conventions for codingcolours, what are they, and how do they relate toeach other?

International standard for colour description?


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Color Fundamentals

The characteristics generally used to distinguish one colorfrom another are brightness, hue, and saturation

brightness: the achromatic notion of intensity.

hue: dominant wavelength in a mixture of light waves,represents dominant color as perceived by an observer.

saturation: relative purity or the amount of white lightmixed with its hue.



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Dominant Wavelength Theory

Capitalizes on the variety of spectra that producethe same perceived colour

Specifies a spectrum having this simple shape:

400 700

A

D

B

620


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Dominant Wavelength Theory Luminance is the total power in the light:

o L = (D - A)B + AW (W = ?) Hue is the location of the dominant wavelength, i.e. the

colour of the main pure light present (in previous e.g. its

red)

Saturation is the purity of the light, i.e. the percentage ofluminance that resides in the dominant component:

oS =

(D - A)B

LX 100%


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Dominant Wavelength cont.

The dominant wavelength, luminance andsaturation fully define a colour

When D = A, saturation is 0, and white light isseen. When A=0, a pure light is seen. Pastelcolours contain much white light, and aretherefore unsaturated.

The eye can distinguish about 200 different hues,and about 20 different saturations (depending onthe hue).


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3-dimensional colour spaces

Saturation, luminance and hue are useful conceptsfor describing colour

However, not very easy to measure these valueswhen presented with a sample colour

It does, however, illustrate the fact that colourperception is three-dimensional, i.e. that anycolour may be described uniquely by exactly three

numbers

Any colour can be represented as a point in athree-dimensional colour space.


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CIE Color Space

In order to achieve a representation which uses only positive mixing coefficients, the CIE("Commission Internationale d'Eclairage in 1931) defined three new hypothetical lightsources, x, y, and z, which yield positive matching curves:

If we are given a spectrum and wish to find the corresponding X, Y, and Z quantities, wecan do so by integrating the product of the spectral power and each of the threematching curves over all wavelengths. The weights X,Y,Z form the three-dimensional CIEXYZ space, as shown above.


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CIE Standard

Standard based on three primaries which are able toproduce ALL visible colours.

Often it is convenient to work in a 2D color space This is commonly done by projecting the 3D color space

onto the plane X+Y+Z=1, yielding a CIE chromaticitydiagram

CIE chromaticity diagram is the view you would get lookingat the plane X+Y+Z=1, straight down the blue axis

Provides a standard reference for comparing other colorsystems


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CIE Chromticity Diagram Less natural than RGB However this standard is

useful for converting betwencolour spaces of differentdevices

Projections defined as :


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CIE Chromaticity Diagram complementary colors

colors which can be mixedtogether to yield white light.For example, colors onsegment CD arecomplementary to the colorson segment CB.

dominant wavelength The spectral color which can

be mixed with white light inorder to reproduce thedesired color. color B in theabove figure is the dominantwavelength for color A.

non-spectral colors colors not having a dominant

wavelength. For example,color E in the above figure.


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Color Gamuts Color gamuts are represented

on the chromaticity diagram as

straight line segments orpolygons

Three primaries (from thevertices of the orange triangle)

can only generate colors on theedges or inside the bounding

edges of the triangle.

Hence, no set of 3 primaries canbe additively combined to

generate all perceived colors

o Because no triangle within thediagram can encompass all

colors

Color gamuts traditionally usedto compare video monitors andhard-copy devices


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Tri-stimulus theory

Any colour can be constructed as a linear combination ofthree primary colours, e.g.

C = n1R + n2G + n3B (n1, n2, n3 scalars) (doesnt have to be red, green and blue, can be any three

primaries)

e.g. RGB(0,1,0) would be pure green, CMY(.2,.3,.5) wouldbe a yellow

Problem! To produce all perceivable colours, some of theabove scalars must be negative. This makes no physicalsense. Light cannot be removed that isnt there.


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The RGB Colour Cube On a display with 3 colour phosphors/lamps/LEDs, the possible

magnitudes of each colour vary from 0 to 1.

Thus the space of possible colours in R, G, B space is a unit cube The RGB colour cube is a well known vector space defining all possible

colour combinations based on the RGB basis vectors

E.g. (0, 0, 0) Black, (1, 0, 0) Red, (0, 1, 0) Green, (0, 0, 1) Blue, (1,1, 0) Yellow, (1, 0, 1) Magenta, (0, 1, 1) Cyan, (1, 1, 1) White


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CIE Chromaticity Diagram

It shows colorcompositionas a functionof x (red) andy (green)



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RGB Color Model



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RGB Color Model


Pixel depth

The total number ofcolors in a 24-bit RGB

image is (28)3 =16,777,216


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Safe RGB colors (orsafe Web colors) are

reproduced faithfully,reasonably

independently ofviewer hardware

capabilities


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The CMY and CMYK Color Models


1

1

1

C R

M G

Y B

=

Equal amounts of the pigment primaries, cyan, magenta, andyellow should produce black. In practice, combining thesecolors for printing produces a muddy-looking black.

To produce true black, the predominant color in printing, thefourth color, black, is added, giving rise to the CMYK colormodel.


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http://en.wikipedia.org/wiki/CMYK

CMY vs. CMYK


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HSI Color Model


brightness: the achromatic notion ofintensity.

hue: dominant wavelength in a mixture of light waves, represents dominant color

as perceived by an observer.

saturation: relative purity or the amount of white light mixed with its hue.


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HSI Color Model



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HSI Color Model



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HSI Color Model



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Converting Colors from RGB to HSI

Given an image in RGB color format, the H component ofeach RGB pixel is obtained using the equation


if B G

360 if B>GH

=

[ ]

( )

1

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1( ) ( )

2

cos ( )( )

R G R B

R G R B G B

+

=

+


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Given an image in RGB color format, the saturationcomponent is given by


[ ]3

1 min( , , )( )S R G BR G B=

+ +


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Given an image in RGB color format, the intensitycomponent is given by


( )1

3I R G B= + +


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Converting Colors from HSI to RGB

RG sector


(1 )

cos1

cos(60 )

and

3 ( )

B I S

S HR I

H

G I R B

=

= +

= +

o

(0 120 )H


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RG sector


120

(1 )

cos1

cos(60 )

and

3 ( )

H H

R I S

S HG I

H

B I R G

=

=

= +

= +

o

o

(120 240 )H


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RG sector


240

(1 )

cos1

cos(60 )

and

3 ( )

H H

G I S

S HB I

H

R I G B

=

=

= +

= +

o

o

(240 360 )H o o


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