2_06-1 - color image processing

7/31/2019 2_06-1 - Color Image Processing

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Color ima e rocessin :

fundamentals

Spring2008 ELEN4304/5365DIP 1

byGlebV.Tcheslavski:[email protected]://ee.lamar.edu/gleb/dip/index.htm

PreliminariesColor image processing is motivated by two main factors:

1. Color is a powerful descriptor simplifying object recognition.

2. We can distinquish between thousands of color shades and

intensities, compared to about 20-30 values of gray.

There are two major areas of color image processing:

1. Full-color processing images are acquired with a full-color

sensor (TV camera, color scanner);


. monochrome intensity or intensity range.

Many methods discussed for processing of monochrome images are

applicable to color images; other methods need reformulation.


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Fundamentals of colorMechanisms of color processing by human brain are not completely

understood. However, the physical nature of color can be formally

ex ressed and modeled.


1666: Sir Isaac Newton managed to pass a beam of white lightthrough a glass prism and got a rainbow on the other side where

each color blends smoothly into the next.

Fundamentals of color

Particular colors of the object as human perceive them are

determined by the nature of light reflection properties of the object. A


appears as white. A body reflecting more light in a particular range of

wavelengths and absorbing light in other bands appears as colored.

Note: creatures other than humans may (and do!) perceive colors in a

completely different way than we do


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If the light is achromatic (no colors), its only attribute is its intensity(amount). Examples of achromatic light: images produced by a b&w

, .

so far was limited to achromatic images.

Chromatic light spans the EM spectrum from approximately 400 to

700 nm. The three basic quantities used to describe a chromatic light

source are radiance (the total amount of energy from the source, W),

luminance (energy an observer perceives from the source, lm: for


examp e, an o server m g t are y perce ve any g t rom a source

radiating in an infrared region), and brightness (a subjective

descriptor practically impossible to measure since it is associated toboth the intensity and color sensation).

Fundamentals of colorColor sensitive sensors of human retina are cones. The total of 6-7

million of cones

in a human e e

can be associated

with one of three

groups: red (~575

nm) sensitive

(about 65 % of all

cones), green

1965


(~535 nm 33%),

and blue (~445 nm

2%) sensitive.

Blue cones are the

most sensitive.


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Due to the absorption characteristics of the human eye, we see colorsas variable combinations of so-calledprimary colors of light: red

(R), green (G), blue (B). The following wavelengths are designated

to them in 1931: 700 nm, 546.1 nm, and 435.8 nm.

A common misconception is that it is possible to get any desired

visible color by properly mixing the primary colors!

Note: this selection of primary colors is rather arbitrary: about every


, ,

primary.


Speaking of arbitrary selection of primary colors count number of

colors in two rainbows:

Spring2008 ELEN4304/5365DIP 8Western version

Eastern (Russian) version

and then find brown color


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Fundamentals of colorAdding primary colors of light produces

secondary colors: magenta (red + blue),cyan (green + blue), and yellow (green

+ red). Mixing the three primary colors

of light (or a secondary with its

opposite primary color) in the right

intensities produces white light. Mixing

together the three secondary colors of

light, black (no light) can be produced.


Aprimary color of pigment is a color

that subtracts (or absorbs) a primary

color of light and reflects (or transmits)the other two. Therefore, the primary

colors of pigments are CMY.


CRT or LCD monitors are good examples of mixing light colors

where three primary colors (RGB) are mixed (added) to form light

of the particular color (either via the three gloving dots of different

luminophore or via the three light beams of different color).

Color printers are examples of mixing (adding) light pigments.

Colors are usually distinguished from each other through the three

characteristics: brightness, hue, and saturation. As mentioned


, .dominant color as perceived by an observer (red, yellow, blue).

Saturation is the amount of white added to a hue (purity of the color).

For example, we need to specify saturation to characterize pink (red

+ white).


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Hue and saturation together are called chromaticity. A color may alsobe characterized by its brightness and chromaticity.

The amounts of red, green, and blue needed to form any particular

color are called thetristimulus values and are denoted asX, Y, Z.

therefore, a color is specified by itstrichromatic coefficients:

, ,X Y Z

x y zX Y Z X Y Z X Y Z

= = =+ + + + + +


We notice that 1x y z+ + =

The tristimulus values needed to produce a color of particularwavelength can be obtained from the tables.

Fundamentals of colorAnother way to specify colors is

by using the CIE (chromaticity

diagram), which shows a color

composition as a function ofx

(red) andy (green). For any

values ofx andy, the

corresponding value ofz (blue)

can be found as

=



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Fundamentals of colorThe point marked as green has

approximately 62 % green and25 % red. Therefore, it has about

13 % of blue.

The positions of different colors

(from violet at 380 nm to red at

700 nm) are indicated by the

wavelengths around the

boundary of the chromaticity


diagram. They are the pure

colors. Any pointnot on the

boundary represent somemixture of spectrum colors.


The white point in the middle of

CIE is called the point of equal

energy as equa ract ons o t e

three primary colors: CIE standard

for white light.

Any point along the boundary is

fully saturated. When leaving the

boundary, some amount of white


light is added to form the color.

The saturation at the point of

equal energy is zero.


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A straight line joining any twopoints in the diagram defines all

t e erent co or var at ons t at

can be obtained by combining

these two colors additively.

A line drawn from the point of

equal energy to any point on the

boundary defines all the shades


of that particular color.


Extending this procedure to the

three (primary) colors, we need

to orm a tr ang e, w ose apexes

are the three primary colors.

Any colorat the boundary or

inside the triangle can be

produced by various

combinations of the three initial


.Therefore, not all colors can be

obtained from three fixed

primaries.


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A typical range of colors (colorgamut) produced by RGB

mon tors.

The irregular region inside the

triangle represents the color

gamut of the high-quality color

printers. The region is irregular

since color printing involves a


combination of additive and

subtractive color mixing.


CRTmon tor



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LCDon tor(projector)


Color models

A color model (color space or color system) is a specification of a

coordinate system and a subspace within that system where each

color is represented by a single point.

Most contemporary color models are oriented either toward hardware

(color monitors and printers) or toward applications where color

manipulation is used (color graphics for animation).

The most commonly used in Image Processing practice models are


mon tors, most o cameras , an pr nters , an

HIS (closely correspond to the human visual system.


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RGB color model

The RGB (red, green, blue) color model is based on a Cartesiancoordinate system. The color subspace is a cube, in which RGB

corners; the secondary colors (cyan,

magenta, and yellow) are at three

other corners; black is at the origin;

and white is at the farthest from the

origin corner. The gray scale (points


black to white along the straight line.

Different colors are points on or inside the cube and are defined byvectors extending from the origin. All values of R, G, and B are

normalized and are assumed to be in the range [0,1].

RGB color model

Images represented in the RGB model consist of three component

images (one for each primary color) that are combined into a

compos e co or mage.

The number of bits used to represent a

pixel is called the pixel depth.

Assuming that each component image

uses 8 bits, each RGB color pixel is

said to have a depth of 24 bits. Such


co or mages are requen ycalledfull-color images.

The total number of colors in a 24-bit color image is

( )3

82 16 777 216=


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RGB color model

A convenient way toview these colors is to

Cross-sectional plane(127,G,B);

(faces of color sections

of the cube). To do this,

one color is fixed while

two other are varying.

,

In the component


images, 0 represents

black and 255 is white.

An RGB image can be viewed by feeding the component images to

a color monitor.

RGB color model

Acquiring color images can be accomplished by reversing the

procedure: the scene can be sensed through red, green, and blue

ers consequen y o recor componen mages.


The three hidden surfaces of the color cube.


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RGB color model

Some of the hardware used for color image reproduction is limitedto 256 colors. Only 216 of these colors are common to most systems

t e rest s processe erent y . ese co ors ecame t e e acto

all-systems-safe colors. Each of them is formed from three RGB

values but each value is limited to [0, 51, 102, 153, 204, 255] or in

the hexagonal system [00 33 66 99 CC FF].

Since three numbers specify an RGB color, each safe color is

formed from three of the two-digit hexagonal numbers: the purest


red would be (FF 00 00), black is (00 00 00), and white is (FF FF

FF). The decimal equivalents are (255 0 0), (0 0 0), and (255 255

255).

RGB color model

The 216 safe colors:

the left top square is

, t e

next (FF FF CC),

etc. The second raw

is (FF CC FF), (FF

CC CC), etc.



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RGB color model


Full color cube Safe color cube (sampled)

CMY and CMYK color models

Cyan, magenta, and yellow are the secondary colors of light (or the

primary colors of pigments). Most color printing devices use CMY

mo e . e convers on rom s one y:

1

1

1

C R

M G

Y B

=

E ual amount of three i ments must roduce black. This a roach


is not very practical and leads to a muddy-looking black. To

produce a true black (predominant color in printing), a fourth color

black is added to the color model to make a CMYK model.


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HSI color model

While RGB and CMY color models are well suited for hardwareimplementations, these models do not fit well human perception of

, ,

brightness. Therefore, the hue, saturation, intensity (HSI) model

was developed, where the intensity component is independent from

color information.

The intensity axis goes

from black to white and


3

R G BI

+ +

=

HSI color modelConsidering the triangle with apexes ofBlack,

White, and any color point(Cyan, f.i.), we

notice that all oints on the trian le have the

same hue. Rotating the plane about the

intensity axis, we can obtain different hues.

360

if B GH

if B G

=

>


( ) ( ) ( )

1

2

2cos

R G R B

R G R B G B

+

= +

Where

A small number often is added to the denominator to avoid dividing by zero. Zero

angle corresponds to red here. If RGB values are normalized, hue is divided by 3600.


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HSI color model

The HSI space is represented by a vertical intensity axis and thelocus of color points that lie on planes perpendicular to this axis. As

,

either a triangular or hexagonal shape.

Primary colors are separated by

1200 while the secondary are 600

from primaries.

Therefore, the hue


of the point can be

determined by an

angle from somereference point (as

shown previously)

HSI color modelSaturation (distance from the

vertical axis) is the length of the

vector from the ori in to the oint:

[ ]3

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

= + +

The important components of the

HSI model are the vertical intensity

axis, the length of the vector to the


color point, and the angle of that

vector.

HSI planes are defined as hexagons,

triangles, or circles. The shape does

not matter!


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Converting colors from HSI to RGB

Assuming that HSI values are normalized (in the interval [0 1]),conversion to RBG depends on the H value and is different for the

0. , .

1. RG sector: 0 120H

( )cos

1cos 60

S HR I

H

= +


( )3

(1 )

G I R B

B I S

= +

=


2. GB sector: 120 240H

( )1

cos1

cos 60

R I S

S HG I

H

=

=

= +


( )3B I R G= +


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3. BR sector: 240 360H

( )

( )

3

1

cos

R I G B

G I S

S H

=

= +

=


( )1

cos 60B I

H= +


Original color cube


Its hue component:

the discontinuity

Its saturation

component

Its intensity

component


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Manipulating HSI component

imagesColor image

showinIts hue

com onentprimary and

secondary

colors

image: red

is mapped

to black

Its intensitIts


component

image

saturation

component

image

Manipulating HSI componentimages

To change the color in any region, we change the values in the

correspon ng reg on n t e ue mage; t en convert t e new

image with the unchanged SandIimages back to RGB image.

To change the saturation (purity) in any region, we follow the same

procedure except that we change the saturation image.


, .


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Manipulating HSI component

images

Modified hue

com onent

Modifiedsaturation

image: blue

and green

regions are

set to 0

componen

image: cyan

region is

reduced by

half

Modified


component

image: white

region was

reduced by

half

RGB image

2_06-1 - color image processing

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