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Digital Image Processing
Ligang Liu
Zhejiang University
[email protected]
Media
A picture is worth 1000 words…
A video is worth 1000 sentences…
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Rich information from visual data
Examples of images around us
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Natural photographic images
Artistic and engineering drawings
Scientific images (satellite, medical, etc.)
Motion picture –video
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Movies, TV programs, news
Family video
Surveillance and highway camera
Why do we process images?
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Enhancement and restoration
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Transmission and storage
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images from oversea via Internet, or from a remote
planet
Information analysis and automated recognition
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remove artifacts and scratches from an old
photo/movie
improve contrast and correct blurred images
providing “human vision” to machines
Security and rights protection
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encryption and watermarking
Why Digital?
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“Exactness”
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Convenient & powerful computer-aided processing
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Perfect reproduction without degradation
Perfect duplication of processing result
Can perform rather sophisticated processing through hardware
or software
Even kindergartners can do it!
Easy storage and transmission
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1 CD can store hundreds of family photos!
Paperless transmission of high quality photos through network
within seconds
Human Vision System
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Image is to be seen.
Perceptual Based Image Processing
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Focus on perceptually significant information
Discard perceptually insignificant information
Issues:
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Biological
Psychophysical
Color
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Color is the perceptual result of light
having wavelength 400 nm to 700 nm
that is incident upon the retina.
“Power distribution exists in the physical
world, but color exists only in the eye
and the brain.”
Does “red” mean the same to different
people?
Color Spectrum
Grassman's First Law of
Additive Color Mixture
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Any color can be matched by a linear
combination of three other colors
(primaries, eg RGB), provided that none
of those three can be matched by a
combination of the other two.
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C= Rc(R ) + Gc(G) + Bc(B)
Color Spaces
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RGB
CMY
CIE XYZ
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Different Image Types
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Binary images (0 or 1)
Gray images (0~255)
Color images
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indexed color images
full color images (24 bits per pixel, 8-red,
8-green, 8-blue) )
A Binary Image
Gray Images
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8 bits per pixel
Full Color Images
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24 bits per pixel, and the three
channels R G B are three gray images
respectively
Color Components
Image Programming
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class CImage
{
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unsigned int width;
unsigned int height;
unsigned char *data;
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};
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Not difficult…
Related Fields
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Imaging
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Medical, remote sensing, weather
Computer vision
Computer graphics
Machine learning
Video processing
Related Math
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Fourier analysis
Wavelet
Probability and statistics
PDE
Linear/nonlinear optimization
Machine learning
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References
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Journals
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IEEE Transaction on Pattern Analysis and Machine
Intelligence (PAMI)
IEEE Transaction on Image Processing
IEEE Transaction on Signal Processing
IEEE Transaction on Circuits and System for Video
Technology
International Journal on Computer Vision (IJCV)
Pattern Recognition
Conferences
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Graphics Conferences (Siggraph…)
Vision conferences: ICCV, ECCV, ACCV, CVPR
Course Information
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Seminar
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Grading
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Report papers by yourselves
Seminar reports and final report
Course homepage and FTP
Objectives
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Learn something interesting
Do something interesting
Find some interesting problems
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Improve your abilities and experiences!
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Requirements
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Reporter
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Audience
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Over-prepared: read a series of important papers, PPT (texts
and images)
Professional: PPT, explaining, interaction…
List all references on the last slide
His own idea or own work
Challenging the reporter
Ask questions
Learn something new
Active and creative!
Q&A