Lecture #12engr.case.edu/merat_francis/eecs490f07/Lectures/Lecture... · 2012. 2. 16. · * Text is...
Transcript of Lecture #12engr.case.edu/merat_francis/eecs490f07/Lectures/Lecture... · 2012. 2. 16. · * Text is...
EECS490: Digital Image Processing
Lecture #12
• Image Correlation (example)
• Color basics (Chapter 6)
• The Chromaticity Diagram
• Color Images
• RGB Color Cube
• Color spaces
• Pseudocolor
• Multispectral Imaging
EECS490: Digital Image Processing
© 2002 R. C. Gonzalez & R. E. Woods
White Light
A prism splits white light into its component colors.
EECS490: Digital Image Processing
© 2002 R. C. Gonzalez & R. E. Woods
Optical Units
Radiometric units:Radiance (watts/sr/m2) — power per unit solid angle emitted by a light sourceIrradiance (watts/m2) — total power incident on a surface
Photometric units (corrected for wavelength sensitivity of the human eye):Luminous intensity (candela) - “power” emitted by a source in a given directionLuminance (candela/m2) — total light passing through a given surface or emitted from asurfaceLuminous flux (lumens) — luminous flux of light produced by a light source that emits onecandela of luminous intensity over a solid angle of one steradian
EECS490: Digital Image Processing
© 2002 R. C. Gonzalez & R. E. Woods
Human Eye
The cones provide all thecolor sensitivity and areconcentrated near themacula.
Relative color sensitivity ofthe cones.
65% of cones are red sensitive;33% are green sensitive; 2% areblue sensitive.
EECS490: Digital Image Processing
© 2002 R. C. Gonzalez & R. E. Woods
Primary/Secondary Colors
(Primary) additive colorsoperate in transmissionsuch as found in televisionsand computer monitors
(Secondary) subtractivecolors operate in reflectionsuch as found in printing
Subtractive colors operateby absorbing a primarycolor. They usually requireblack as an additional color.
For example, yellow absorbsblue and reflectsred+green=yellow
RGB
CMY
EECS490: Digital Image Processing
© 2002 R. C. Gonzalez & R. E. Woods
Why K?
Common reasons for adding a K (black) ink include:
* Text is typically printed in black and includes finedetail (such as serifs), so to reproduce text or otherfinely detailed outlines using three inks without slightblurring would require impractically accurateregistration (i.e. all three images would need to bealigned extremely precisely).
* A combination of 100% cyan, magenta, and yellowinks soaks the paper with ink, making it slower to dry,and sometimes impractically so.
* A combination of 100% cyan, magenta, and yellowinks often results in a muddy dark brown color that doesnot quite appear black. Adding black ink absorbs morelight, and yields much “blacker” blacks.
* Using black ink is less expensive than using thecorresponding amounts of colored inks.
EECS490: Digital Image Processing
© 2002 R. C. Gonzalez & R. E. Woods
CIE Chromaticity Diagram
Characteristics of color:•Brightness•Chromaticity:
• Hue - dominant colorseen by the observer
• Saturation - amount ofwhite light mixed withthe color
A chromaticity diagramplots the tristimulus valuesx,y and z of a color. This isbased upon X,Y and Z —the amounts of red, greenand blue needed torepresent a color.
x =X
X +Y + Z
y =Y
X +Y + Z
z =Z
X +Y + Zwhere x + y + z +1
The x-axis is red.
The
y-ax
is is
gree
n.
Blue is notplotted since is isequal to 1-x-y
The diagram shows all colors perceivable by the human eye.
EECS490: Digital Image Processing
© 2002 R. C. Gonzalez & R. E. Woods
CIE Chromaticity Diagram
Characteristics of color:•Brightness•Chromaticity:
• Hue - dominant colorseen by the observer
• Saturation - amount ofwhite light mixed withthe color
The point of equal energy(x=0.33,y=0.33, impliedz=0.33) defines the CIEstandard for white light
The x-axis is red.
The
y-ax
is is
gree
n.
Any point on the boundaryis fully saturated(saturation=1)
Note that we candefine many kinds ofwhite near the CIEstandard for white.These include daylight(more blue), coolwhite (more red andgreen), and warmwhite (much more red)
EECS490: Digital Image Processing
© 2002 R. C. Gonzalez & R. E. Woods
Color Temperature
The x-axis is red.
The
y-ax
is is
gree
n. Color Temperature(measured in Kelvin)describes how "warm"or how "cool" the lightsource is. It is based onthe color of light emittedby an incandescentsource. As a piece ofmetal (a theoreticalBlackbody) is heated, itchanges color fromreddish to orange toyellowish to white tobluish-white. The colorof light emitted by anincandescent objectdepends only on thetemperature. We canuse this scale todescribe the color of alight source by its "ColorTemperature."
EECS490: Digital Image Processing
© 2002 R. C. Gonzalez & R. E. Woods
CIE Chromaticity Diagram
Color printers are capableof far less color renditionthan a color monitor. Thetwo regions define typicallimits of printers andmonitors. Note that a monitor
(triangle) is incapable ofdisplaying colortemperatures below about1900˚K. A printer is evenworse.
EECS490: Digital Image Processing
• Are constructed from threeoverlaid intensity maps.
• Each map represents theintensity of a different“primary” color.
• The actual hues of theprimaries do not matter aslong as they are distinct.
• The primaries are 3 vectors(or axes) that form a“basis” of the color space.
1999-2007 by Richard Alan Peters II
Color Images
EECS490: Digital Image Processing
Each color corresponds to a point in a 3D vector space
1999-2007 by Richard Alan Peters II
Pixels — Coordinates or Vectors?
EECS490: Digital Image Processing
for standard digital images
• primary image colors red, green, and blue
– correspond to R,G, and B axes in color space.
• 8-bits of intensity resolution per color
– correspond to integers 0 through 255 on axes.
• no negative values
– color “space” is a cube in the first octant of 3-space.
• color space is discrete
– 2563 possible colors = 16,777,216 elements in cube.
1999-2007 by Richard Alan Peters II
Color Space
EECS490: Digital Image Processing
© 2002 R. C. Gonzalez & R. E. Woods
RGB Color Cube
The colors along thediagonal have equal amountsof red, green, and bluewhich defines gray. Buttheir intensity given byI=(R+G+B)/3 varies from 0(black) to 1 (white) alongthe cube’s diagonal.
EECS490: Digital Image Processing
© 2002 R. C. Gonzalez & R. E. Woods
RGB Color Cube
Typically each color isdefined by three 8-bitnumbers for 24-bit color.Some computer programsalso support 48-bit color.
The top surface can be written as (R,G,255)
The bottom surface can be written as (R,G,0)
EECS490: Digital Image Processing
1999-2007 by Richard Alan Peters II
Color Cube: Faces (outer)
The primary colors are at three vertices.The secondary colors are at threedifferent vertices
EECS490: Digital Image Processing
1999-2007 by Richard Alan Peters II
Color Cube: Faces (inner andouter)
Cutting open the cube shows black at the origin.
Black and white form the remaining two vertices.
EECS490: Digital Image Processing
RGB axes CMY axes
1999-2007 by Richard Alan Peters II
Different Axis Sets in Color Space
EECS490: Digital Image Processing
The same color has different RGB and CMY coordinates.
1999-2007 by Richard Alan Peters II
Color With Respect To Different Axes
which may be related to each other.
EECS490: Digital Image Processing
© 2002 R. C. Gonzalez & R. E. Woods
Color Monitors
(0,G,B) (R,0,B) (R,G,0)
The monitor adds primary colors.
EECS490: Digital Image Processing
© 2002 R. C. Gonzalez & R. E. Woods
“safe” Colors
Many systemsrestrict themselves to256 Internet “safe”colors for simplicityand ease ofgeneration.
Decreasing blue
Dec
reas
ing
gree
n
$00$33$66
$99$CC$FF
Red coordinate values
There are six safe grays.
$FF $00
$FF
$00
EECS490: Digital Image Processing
© 2002 R. C. Gonzalez & R. E. Woods
“safe” colors
The Internet “safe” RGB color cube. All surface colors are “safe”.
Color printers and copiers convertRGB to CMY. To get a good black oncolor printers a separate “black” isused.
C
M
Y
=
1
1
1
R
G
B
EECS490: Digital Image Processing
R G B
L a* b*
are represented by three bands (not uniquely)
e.g., R, G, & B; L, a*, & b*; or HSI
Red
Green
Blue
Luminance
a*-chroma
b*-chroma
Color Images
La*b* is a CIE color space designed to approximate human vision. L approximates thehuman perception of brightness. a* and b* are color opponents. There is no direct, simpleconversion from RGB to La*b* since it requires a reference white (specifically a diffuseCIE D65 light source). 1999-2007 by Richard Alan Peters II
The RGB color space results from simple ways to separate and combine color.
EECS490: Digital Image Processing
Lu
min
an
ce
hu
esa
tura
tion
photo receptorsbrain
The eye has 3 types of photoreceptors: sensitive to red, green, or blue light.
The brain transforms RGB into separatebrightness and color channels (e.g., HSI).
RGB to HSI: A PerceptualTransformation
HSV Hue-Saturation-Value (also called HSB) is a perceptual system also called the Munsell colorsystem. I ranges from black to a saturated color or white. There is a separate hue and Saturation.
HSL Hue-Saturation Luminance (also called HLS or HSI) defines luminance as the “lightness”. L rangesfrom black to white. The half-way point is always a 50% gray.
1999-2007 by Richard Alan Peters II
How do humans perceive color?
EECS490: Digital Image Processing
© 2002 R. C. Gonzalez & R. E. Woods
HSI Color Space
NOTE:GW uses the HSI color space
1. The black-whiteline defines the I-axis for the HSIcolor space.
2. Each plane ⊥ tothe I-axis containsall colors of thesame saturation,i.e., with the sameamount of white.
3. The plane ⊥ toboth the I-axis andthe saturationplane will contain allcolors of the samehue.
EECS490: Digital Image Processing
© 2002 R. C. Gonzalez & R. E. Woods
HSI Color Space
Looking into the RGB color cube alongthe I-axis. White is closest to you inthis orientation. Dashed lines are theback of the cube.
The saturationplane asbounded by theRGB cube is ahexagon.
The hexagonalsaturation plane isusually more simplymodeled as atriangle or circle.
S (radius) and H (angle) are usually expressed in polar coordinates with red=0˚.
EECS490: Digital Image Processing
© 2002 R. C. Gonzalez & R. E. Woods
HSI Color Space
The triangularand circularapproximationsto the RGBcube plotted in3-D.
EECS490: Digital Image Processing
© 2002 R. C. Gonzalez & R. E. Woods
White Light
Red
Increasing saturationtowards edges.
Intensity ishighest at white;lowest at themost highlysaturated colors.
EECS490: Digital Image Processing
RGB to HSI Conversion
I =1
3R +G + B( )
S = 13
R +G + Bmin R,G,B( )
H =if B G
360 if B > G
= cos 1
12
R G( ) + R B( )
R G( )2+ R B( ) G B( )
EECS490: Digital Image Processing
HSI to RGB Conversion
B = I 1 S( )
R = I 1+S cosH
cos 60˚ H( )
G = 3I R + B( )
EECS490: Digital Image Processing
© 2002 R. C. Gonzalez & R. E. Woods
RGB ↔ HSI
H component (angles):B/W are zero hueRed is 0˚ or black
S component [0:255]:These colors are fullysaturated (they are all onsurface of RGB cube)
I component:Average intensities
Primary/secondarycolors
Gray axis has zero hue and zero saturation.
EECS490: Digital Image Processing
© 2002 R. C. Gonzalez & R. E. Woods
HSI Color Processing
S component:Reduce cyan saturationby 50%
I component:Reduce intensity ofwhite by 50%
Transform back to RGB:B & G become redCyan looks washed outWhite is now 50% gray
H component:Change blue and green tozero,i.e., this makesthem red.
EECS490: Digital Image Processing
© 2002 R. C. Gonzalez & R. E. Woods
Pseudocolor
If gray>li then color A
If gray<li then color B
Assign colors to grayscale values usingsome criterion. This technique is useda lot in data visualization.
EECS490: Digital Image Processing
© 2002 R. C. Gonzalez & R. E. Woods
Pseudocolor
Intensity slicing can also be described asan intensity transformation similar tothose found in Chapter 2.
EECS490: Digital Image Processing
© 2002 R. C. Gonzalez & R. E. Woods
Pseucocolor
In this example we map gray scales tomultiple colors (eight in this case).
EECS490: Digital Image Processing
© 2002 R. C. Gonzalez & R. E. Woods
Pseudocolor
If gray=255 then yellowelse blue.
Cracks in a weld allowhigh-intensity x-rayexposure.
EECS490: Digital Image Processing
© 2002 R. C. Gonzalez & R. E. Woods
Pseudocolor
Difficult to see the patterns ina gray-scale image. Colorallows easier visualization.
EECS490: Digital Image Processing
© 2002 R. C. Gonzalez & R. E. Woods
Color Transformations
We can perform simultaneous color transformations andcombine the result on an RGB monitor.
EECS490: Digital Image Processing
© 2002 R. C. Gonzalez & R. E. Woods
Color Transformations
These are periodictransformations designedto map intensities intospecific colors.
Transform 6.25(a) Transform 6.25(b)
EECS490: Digital Image Processing
© 2002 R. C. Gonzalez & R. E. Woods
Color Transformations
EECS490: Digital Image Processing
© 2002 R. C. Gonzalez & R. E. Woods
Color Transformations
More sophisticated color transformationscan be used to, for example, combinegrayscale images from different sensors.
EECS490: Digital Image Processing
© 2002 R. C. Gonzalez & R. E. Woods
Multi-Spectral Imaging
R G
B IR
RGB
RGIR
EECS490: Digital Image Processing
© 2002 R. C. Gonzalez & R. E. Woods
Multi-Spectral Imaging
Color encoding of a varietyof different sensor inputs.
Red material was recentlyejected from a volcano.
Older ejected material(sulfur) is yellow.