ECE 638: Principles of
Digital Color Imaging Systems
Jan P. Allebach
School of Electrical and Computer Engineering
allebach@purdue.edu
What is a digital color imaging system?
What else besides printers?
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Digital cameras
Flatbed scanners
Mobile phones
Flat panel displays
How do we organize all this?
Image
capture
devices
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Cameras
Scanners
Image
output
devices
Interconnection
space and
processing
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Personal
computers
Internet
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Displays
Printers
What do we need to study in order to
understand digital color imaging systems?
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Color science
Image capture
Image display
Image printing
Image processing
Image quality models and assessment
Color science topics
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What is color?
Trichromatic model for
human vision
Opponent channel models
for human vision
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Standard color spaces
Models for color imaging
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devices
– Device gamma
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Color imaging systems
calibration
Transformation between
color spaces
– White point
– Color space interpolation
– Gamut mapping
Color appearance
models
Color management
practices
Image capture topics
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Sensors
– Technologies
– Characteristics and models
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Scanners
– Architecture
– Illuminations
– Scan bar motion
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Spatial analysis of scanning and sampling
Calibration of image capture devices
Descreening
Page classification
Image display topics
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Display technologies
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Cathode ray tube
Liquid crystal
Plasma panel
E-paper
Calibration of image display devices
Spatial analysis of image display
Color image quantization
Image printing topics
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Printing technologies
– Silver halide-based systems
– Ink-based systems
• Plate-based systems
• Inkjet systems
– Toner-based systems
• Dry electrophotography
• Wet electrophotography
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Colorant-media-light
interaction
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Color trapping
Digital halftoning
Calibration of printing
systems
Image quality models and assessment
topics
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Image quality terminology
Basic psychophysical methods
Image artifact assessment
Image quality metrics
Image quality rulers
What is color?
Let’s see what Microsoft has to say about
color
Click on “More Font Colors…”
HSV
HSL
Crayon Picker
CMYK Picker
What did we learn?
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Lots of different ways to talk about color
Ordering and naming systems
– Crayon picker
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Coordinate systems
– HSV
– HLS
– CMYK
Many questions remain…
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How were these attributes chosen?
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Hue
Saturation
Lightness
Value
Which CMYK are we talking about?
– Rendering device
– Capture device
CMYK
Cyan (C)
Magenta (M) Yellow (Y)
Black (K)
Which CMYK? – effect of rendering
device
Monitor
HP DJ 970Cse
Mac Driver
HP DJ 970Cse
IPP Driver
Which CMYK? – effect of capture device
Olympus C3000
Digital Camera
Heidelberg Scanner
Different color representations
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Are they all equivalent?
How do we get from one to the other?
Can we get from one to the other?
Even if we can, what do all these numbers mean?
Example: capture to capture
Given RGB values from one capture device, can we
predict RGB values for a second capture device?
Olympus C3000
Digital Camera
Scanner
RGB values
(23, 136, 180)
RGB values
(?, ?, ?)
(203, 11, 52)
(?, ?, ?)
(219, 186, 33)
(?, ?, ?)
(7, 7, 7)
(?, ?,?)
Discussion topic
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What is the basis for the equations that underlie color
transformations?
So what is color?
Color is a sensation experienced by a human
being in response to a visual stimulus.
What are the key parts of this definition?
Color is a sensation experienced by a human
being in response to a visual stimulus.
Sensation – human being
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Need to understand something about the human visual
system
– physiology
– perception
– psychophysics
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Relevant courses
– EE 595T Psychophysics (Profs. Hong Tan and Zygmunt Pizlo)
– PSY606V Vision Seminar (Prof. Zygmunt Pizlo)
Visual stimulus
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Need to understand interaction of
illuminant and object
Illuminant
Viewer
Object
Why should we care about color?
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Important aspect of everyday experience
New imaging and information technologies provide
unprecedented ability to manipulate and use color
– Capture devices
• digital cameras
• scanners
– Output devices
• CRT and LCD displays
• Inkjet and laser printers
– Intermediaries
• PCs
• applications
• internet and web
Why should we care…
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Color provides valuable information about the world
around us
Application areas
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manufacturing
medicine
agriculture
environmental
Contexts
– image analysis for inspection
– machine vision for robotics
– remote sensing