cs654: digital image analysis lecture 29: color image processing
TRANSCRIPT
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CS654: Digital Image Analysis
Lecture 29: Color Image Processing
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Recap of Lecture 28
• Interactive image segmentation
• Graph based approach
• Segmentation using Eigen analysis (Normalized cut)
• Graph cut
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Outline of Lecture 29
• Color image processing
• Fundamentals of colors
• Primary and secondary colors (light and pigment)
• Color models
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Motivation
• Color is a powerful descriptor that often simplifies object identification and extraction from a scene.
• Human can discern thousands of color shades and intensities, compared to about only two dozen shades of gray.
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Illustration
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Illustration
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Color image processing
Full color images Pseudo color images
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Color Fundamentals
The experiment of Sir Isaac Newton, in 1666.
Images: Gonzalez & Woods, 3rd edition
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Color Fundamentals
White Light
Colours Absorbed
Green Light
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Human perception of colors
Image courtesy: http://www.livescience.com
Sensitivity of CONE cells
66% to red
33% to green
6% to blue
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Probable Human Eye Cones Sensitivities
Standard wavelength values for the primary colors
Image courtesy: http://www.graphics.com
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How is the neural signal physically generated?
• The retina contains millions of specialized photoreceptor cells known as rods and cones.
• Within these receptors are membranes with visual pigments
• Pigments consist of retinene joined at both ends to retinal proteins called opsins
• These three types of cone opsins account for the differences in peak wavelength absorption for each pigment.
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Retinoptic organization
Image courtesy: www.pinterest.com
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Visual brain
Characterized by a set of parallel processing perceptual systems, and a temporal hierarchy in visual perception
The eye alone does not tell the story
Image courtesy: http://neuronresearch.net
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• Basic quantities to describe the quality of light source:
Radiance: Total amount of energy that flows from the light source (in W).
Luminance: A measure of the amount of energy an observer perceives from the light source (in lm)
Brightness: A subjective descriptor that embodies the achromatic notion of intensity and is practical impossible to measure.
Color Fundamentals
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Light and Pigments
Primary colors (Light) Mixing of chromatic lights
Mixing of pigments
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Primary colors
Images: Gonzalez & Woods, 3rd edition
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Color Fundamentals (con’t)
• The characteristics generally used to distinguish one color from another are Brightness, Hue, and Saturation.
Hue: Represents dominant color as perceive by an observer.
Saturation: Relative purity or the amount of white light mixed with a hue
Hue and saturation taken together are called Chromaticity
A color may be characterized by its Brightness and Chromaticity
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Color Fundamentals (con’t)
• Tri-stimulus values: The amount of Red, Green and Blue needed to form any particular color
• Denoted by: X, Y and Z
ZYX
Xx
ZYX
Yy
ZYX
Zz
1 zyx
Tri-chromatic coefficient:
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Chromaticity Diagram
Green Point =
62% green,
25% red,
13% blue.
Images: Gonzalez & Woods, 3rd edition
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Color Fundamentals (con’t)
Color Gamut produced by RGB monitors
Color Gamut produced by high quality color printing device
Images: Gonzalez & Woods, 3rd edition
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Advertisement !!
* As per NTSC standards of what human eye can see
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Digital camera
Images: Wikipedia
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Color Models/ Color space / Color system
• Facilitate the specification of colors in some standard, generally accept way.
• RGB (red, green, blue) : monitor, camera.
• CMY(cyan,magenta,yellow),CMYK (CMY, black) model for color printing.
• HSI model, which corresponds closely with the way humans describe and interpret color.
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The RGB Color Models (con’t)
Images: Gonzalez & Woods, 3rd edition
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The RGB Color cube
Colors 216,777,16238
Images: Gonzalez & Woods, 3rd edition
Bit depth
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The CMY and CMYK Color Models
B
G
R
Y
M
C
1
1
1
• Cyan, Magenta and Yellow are the secondary colors of light
• Most devices that deposit colored pigments on paper, such as color printers and copiers, require CMY data input.
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The HSI Color Models
Images: Gonzalez & Woods, 3rd edition
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The HSI Color Models
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The HSI Color Models
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Thank youNext Lecture: Color Image Processing