digital image processing color models &processing

Digital Image Processing

Color Models &Processing

Dr. Hatem Elaydi Electrical Engineering Department

Islamic University of Gaza

Fall 2015

Nov 16, 2015

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• Color interpretation

– Color spectrum vs. electromagnetic spectrum

– Why does CIE standard specify R, G, B as the primary colors? Are there actually single special band as R, G, or B?

– What is additive color system? What is subtractive color system?

– What is hue and saturation? or what is chromaticity?

– What is chromaticity diagram? tristimulus? Why can't the three primary colors generate all the visible colors specified in the diagram? Where is brown?

– Comment on the different usages of RGB, CMYK, HSI, and L*a*b* color models. What is the color gamut of color monitors, color printing devices, and L*a*b*?

• Color processing

– What is the difference between tonal and color correction?

– What is the difference between processing using RGB model vs. HSI model?

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Color spectrum

When passing through a prism, a beam of sunlight

is decomposed into a spectrum of colors: violet,

blue, green, yellow, orange, red

1666, Sir Isaac Newton

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Electromagnetic energy spectrum

Ultraviolet visible light infrared

The longer the wavelength (meter), the lower the frequency (Hz),

and the lower the energy (electron volts)

The discovery of infrared (1800, Sir Frederick William Herschel)

What is infrared? http://coolcosmos.ipac.caltech.edu/cosmic_classroom/ir_tutorial/

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A typical spectral reflectance pattern

of green vegetation

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Primary colors of human vision

Cones are divided into three sensible categories

– 65% of cones are sensitive to red light

– 33% are sensitive to green light

– 2% are sensitive to blue light

For this reason, red, green, and blue are referred to as the primary colors of human vision. CIE standard designated three specific wavelength to these three colors in 1931.

– Red (R) = 700 nm

– Green (G) = 546.1 nm

– Blue (B) = 435.8 nm

Detailed experimental

Curve available in 1965

Detailed experimental

curve available in 1965

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Color models

• RGB model

– Color monitor, color video cameras

• CMY model

– Color printers

• HIS, HSV model

– Color image manipulation

• YIQ : Color TV, Y(luminance), I(Inphase),

Q(quadrature)

CIE Standard

• CIE: International Commission on

Illumination (Comission Internationale de

l’Eclairage).

• Human perception based standard (1931),

established with color matching experiment

• Standard observer: a composite of a group

of 15 to 20 people

CIE xyY Space • Irregular 3D volume shape is

difficult to understand

• Chromaticity diagram (the same

color of the varying intensity, Y,

should all end up at the same

point)

Color Image Processing

• RGB Model

• Pixel depth – nr of bits used to represent

each pixel

– Full color image (24 bits)

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Primary colors of pigment

A primary color of pigment refers to one that absorbs the primary color of the light, but reflects the other two.

Primary color of pigments are magenta, cyan, and yellow

Secondary color of pigments are then red, green, and blue

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Additive vs. Subtractive color

system involves light emitted directly

from a source

mixes various amounts of red,

green and blue light to produce

other colors.

Combining one of these

additive primary colors with

another produces the additive

secondary colors cyan,

magenta, yellow.

Combining all three primary

colors produces white.

Subtractive color starts with an

object that reflects light and

uses colorants to subtract

portions of the white light

illuminating an object to

produce other colors.

If an object reflects all the

white light back to the viewer,

it appears white.

If an object absorbs (subtracts)

all the light illuminating it, it

appears black.

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Color characterization

Brightness: chromatic notion of intensity

Hue: dominant color perceived by an observer

Saturation: relative purity or the amount of

white mixed with a hue

R

G

B

H S

0o

120o

240o

Color Image Processing

• CMY Model

– Color Printer, Color Copier

– RGB data CMY

B

G

R

Y

M

C

1

1

1

B

G

R

Q

I

Y

311.0523.0212.0

321.0275.0596.0

114.0587.0299.0

Q

I

Y

B

G

R

705.1108.11

647.0272.01

620.0956.01

The HSI Color Model This color model is based on polar coordinates, not

Cartesian coordinates.

The HSI model uses three measures to describe colors:

– Hue: A color attribute that describes a pure color

(pure yellow, orange or red)

– Saturation: Gives a measure of how much a pure

color is diluted with white light

– Intensity: Brightness is nearly impossible to measure

because it is so subjective. Instead we use intensity.

Intensity is the same achromatic notion that we have

seen in grey level images

Color Image Processing

The HSI Color Model Because the only important things are the angle and

the length of the saturation vector this plane is also

often represented as a circle or a triangle

HSV Hexcone

• Intuitive interface to color

RGB -> HSI -> RGB

RGB

Image

Saturation

Hue

Intensity

RGB -> HSI -> RGB

Hue

Intensity

Saturation

RGB

Image

Color Image Processing

• RGB to HSI Conversion

1,,,0 where),(3

1 BGRIBGRI

002

1 if },))(()(

)]()[(2

1

{cos bgBGBRGR

BRGR

H

00 if ,360 bgHH

}),,(min{3

1 BGRBGR

S

IBbIGg / ,/ where 00

Color Image Processing

• HSI to RGB Conversion

BRG

H

HSR

SB

1

])60cos(

cos1[

3

1

)1(3

1

1200 assume H

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HSI-to-RGB conversion …

For 120o <= H < 240o

For 240o <= H < 360o

( )( )

( ) GRIBSIRH

HSIG --=-=ú

û

ùêë

é

-

-+= ,1,

180cos

120cos1

( )( )

( ) BGIRSIGH

HSIB --=-=ú

û

ùêë

é

-

-+= ,1,

300cos

240cos1

Chromatic images

• Colour

– Represented by vector not scalar

• Red, Green, Blue (RGB)

• Hue, Saturation, Value (HSV)

• luminance, chrominance (Yuv , Luv)

Red

Green

Hue degrees:

Red, 0 deg

Green 120 deg

Blue 240 deg

Green

V=0

S=0

Lab: Photoshop

• Photoshop uses this model to get

more control over color

• It’s named CIE Lab model (refined

from the original CIE model

• Liminance: L

• Chrominance: a – ranges from green

to red and b ranges from blue to

yellow

Luv and UVW • A color model for which, a unit change in luminance and

chrominance are uniformly perceptible U = 13 W* (u - uo ); V = 13 W* (v - vo); W = 25 ( 100 Y ) 1/3 - 17

where Y , u and v can be calculated from :

X = O.607 Rn + 0.174 Gn + 0.200Bn

Y = 0.299 Rn + 0.587 Gn + 0.114Bn

Z = 0.066 Gn + 1.116 Bn

x = X / ( X + Y + Z )

y = Y / ( X + Y + Z )

z = Z / ( X + Y + Z )

u = 4x / ( -2x + 12y + 3 )

v = 6y / ( -2x + 12y + 3 )

• Luv is derived from UVW and Lab, with all components guaranteed to be positive

Yuv and YCrCb: digital video • Initially, for PAL analog video, it is now also used in CCIR

601 standard for digital video

• Y (luminance) is the CIE Y primary. Y = 0.299R + 0.587G + 0.114B

• Chrominance is defined as the difference between a color and a reference white at the same luminance. It can be represented by U and V -- the color differences. U = B – Y; V = R - Y

• YCrCb is a scaled and shifted version of YUV and used in JPEG and MPEG (all components are positive)

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

Examples (RGB, HSV, Luv)

Gamma correction

• Without gamma correction, how will

(0,255,127) look like?

• Normally gamma is within 1.7 and 2.8

• Who is responsible for Gamma correction?

• SGI does it for you

• PC/Mac etc, you should do it yourself

No gamma correction

Gamma corrected to 1.7

Pseudo color Image Processing

Pseudo color (also called false color) image

processing consists of assigning colors to

grey values based on a specific criterion

The principle use of pseudo color image

processing is for human visualization

– Humans can discern between thousands

of color shades and intensities,

compared to only about two dozen or so

shades of grey

Pseudo Color Image Processing –

Intensity Slicing

Intensity slicing and color coding is one of the

simplest kinds of pseudo color image processing

First we consider an image as a 3D function mapping

spatial coordinates to intensities (that we can consider

heights)

Now consider placing planes at certain levels parallel

to the coordinate plane

If a value is one side of such a plane it is rendered in

one color, and a different color if on the other side

Color Image Processing

Color Image Processing

Color Image Processing

Color Image Processing

Color Image Processing

Color Image Processing