ECE 468 / CS 519
Digital Image Processing
Introduction
Prof. Sinisa Todorovic
sinisa@eecs.oregonstate.edu
1
ECE 468: Digital Image Processing
•
Instructor:
Sinisa Todorovic
sinisa@eecs.oregonstate.edu
•
Ofﬁce:
2107 Kelley Engineering Center
•
Ofﬁce Hours:
Mon 45pm, or by appointment
•
Classes:
MWF 33:50pm, KEC 1003
•
Class website:
http://web.engr.oregonstate.edu/~sinisa/courses/OSU/ECE468/ECE468.html
2
Recommended Textbook
•
“Digital Image Processing”
by R.C. Gonzalez and R.E. Woods,
3rd edition
, Pearson Prentice Hall, 2008
•
Additional readings on the class website
3
Suggested Readings
•
“Digital Image Processing Using MATLAB,”
by R.C. Gonzalez,
R.E. Woods, and S. Eddins,
2nd edition
, Pearson Prentice
Hall, 2008
4
Course Objectives
•
Cover
basic
theory and algorithms
widely
used in image processing
•
Develop handson experience in processing images
•
Familiarize with MATLAB Image Processing Toolbox
•
Develop critical thinking about the state of the art
5
Prerequisites
6
Prerequisites
•
Signals and systems: ECE 351 and ECE 352
6
Prerequisites
•
Signals and systems: ECE 351 and ECE 352
•
Linear algebra
•
Matrices, Matrix Operations
•
Determinants, Systems of Linear Equations
•
Eigenvalues, Eigenvectors
6
Prerequisites
•
Signals and systems: ECE 351 and ECE 352
•
Linear algebra
•
Matrices, Matrix Operations
•
Determinants, Systems of Linear Equations
•
Eigenvalues, Eigenvectors
•
Statistics and probability
•
Probability density function, Probability distribution
•
Mean, variance, covariance, correlation
•
Priors, Posteriors, Likelihoods
•
Gaussian distribution
6
Prerequisites
•
Signals and systems: ECE 351 and ECE 352
•
Linear algebra
•
Matrices, Matrix Operations
•
Determinants, Systems of Linear Equations
•
Eigenvalues, Eigenvectors
•
Statistics and probability
•
Probability density function, Probability distribution
•
Mean, variance, covariance, correlation
•
Priors, Posteriors, Likelihoods
•
Gaussian distribution
•
Good programming skills
6
Requirements
7
Requirements
•
Homework
•
Turnin a hard copy
•
Homework = Problem solving or Miniproject
•
Miniproject
must
be implemented in MATLAB
•
Homework
should
be an individual effort
•
Late homework will not be accepted
without prior approval
7
Requirements
•
Homework
•
Turnin a hard copy
•
Homework = Problem solving or Miniproject
•
Miniproject
must
be implemented in MATLAB
•
Homework
should
be an individual effort
•
Late homework will not be accepted
without prior approval
•
Graduate students will be given approximately 20% larger
amount of work for homework assignments
7
Requirements
8
Requirements
•
Exam 1 on
November 4, 33:50pm, KEC 1003
8
Requirements
•
Exam 1 on
November 4, 33:50pm, KEC 1003
•
Exam 2 on
December 2, 33:50pm, KEC 1003
8
Grading Policy
•
Homework = 30%
•
Exam 1 = 35%
•
Exam 2 = 35%
•
Bonus: Participation in class
9
Academic Honesty  Examples of Cheating
•
Bringing forbidden material or devices to the examination
•
Working on the exam before or after the ofﬁcial time allowed
•
Requesting a regrade of work altered after the initial grading
•
Submitting a homework that is not your own work
10
What is a Digital Image?
11
What is a Digital Image?
•
Twodimensional function
f(x,y)
or matrix
•
x, y,
f(x,y)
are discrete and ﬁnite
•
Image size =
max
x
x
max
y
 e.g. 640x480
•
Pixel intensity value
f(x,y)
∈
[0, 255]
y
x
column
row
pixel
12
Pixel Values
Source: DIP/3e
13
Images are not Collections of Random Pixels
14
A Typical Digital Image Processing System
3D world
camera
algorithms
representations
users
problem understanding
trade offs
training data
expert systems
knowledge base
processed
image
input
image
15
Sources of Energy for Image Formation
Source: DIP/3e
16
Some Applications  Medical Diagnostics
Gammaray imaging
Source: DIP/3e
Xray imaging
17
Some Applications  Magnetic Resonance Imaging
18
Some Applications  Microscopy
Visiblelight microscopy imaging
Source: DIP/3e
19
Some Applications  Industrial Inspection
20
Some Applications  Remote Sensing
Aerial images
Satellite images
21
Some Applications  Infrared Satellite Images
Source: DIP/3e
22
Some Applications  Storing Images
Blueray
DVD
Standard
DVD
23
Some Applications  Transmitting Images
Video conferencing
24
Some Applications  Image Forensics
25
Fundamental Steps in Digital Image Processing
26
Fundamental Steps in Digital Image Processing
•
Acquisition
•
Spatial and frequency transforms
•
Enhancement (subjective)
•
Restoration (objective)
•
Color processing
•
Multiresolution processing
•
Compression
•
Morphological processing
•
Segmentation
27
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