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Lecture Notes HomeWorks
Discussions
Instructor: B. S.
Manjunath, manj@ece.ucsb.edu,
Rm 3157, Engineering I. Tel: 805.893.7112.
Teaching Assistants: Jelena Tesic (jelena@ece.ucsb.edu)
and Marco Zuliani (zuliani@ece.ucsb.edu)
Lectures: Tuesdays and Thursdays, 1230-1345 hrs., NORTH HALL #1105.
Office Hours
Manjunath: Tuesdays 2PM-3PM and Wednesdays
1-2PM, or by appointment (please call x7112).
TA: Wednesdays 2-3PM, Thursdays 2-4PM, Fridays 3-4PM.
Note that the TAs will be present in the ECE Computer Lab on Thursdays
and Fridays.
Discussion Session: The first
discussion session will be held at WEBB 1100 at 12noon on Friday,
January 10th.
Text Book: Digital
Image Processing by Gonzalez and Woods. The book's web site contains
pointers to additional resources and you are encouraged to take a look.
Also, you may want to take a look at last
year's course web page for more information.
About the course: ECE 178 is an introductory course in
image processing. In this course, you will learn about
digital images and how you can manipulate them.
Open to students in Engineering. You should have good
background in basic calculus. Preliminary topics such as basics of
linear systems, linear and circular convolution, and 2-D Fourier
transform will be introduced during the first two weeks. You are
expected to learn and use MATLAB and the Image Processing Toolbox for
your programming assignments. No prior knowledge of MATLAB is
required.
Grading Ploicy: 20% HWs, 20% Mid-term
examinations, 20% course project and 40% for the final examination.
First mid-term examination will be in class on Feb 4th. All home-works
are required (a non-submission will affect your grade non-linearly). The
home works are due by 11:59 PM on the day they are due (typically, on a
Friday). Those that are received within 48 hours of the due date will
get 50% of the points. After 48 hours, they will not receive any credit.
NOTE: Print version with six slides per page are
available as well. Print the "handouts".
Week 1 - Introduction
- Lecture 1
(handout) (01/08/2002): course
objectives; introduction.
- Lecture 2 (handout)
(01/9/2002): will continue the introduction, starting with a quick
overview of MATLAB for image processing. We will conclude this
lecture with a brief review of sampling and quantization (section
2.4) and relationship between pixels (section 2.5).
- Homework #1 is due January 17. Read Chapters 1 and 2. This
requires MATLAB programming, so start early!
- Using MATLAB for image processing.
- Mathworks has a nice web page on the image
processing toolbox. See also their demo
page on some interesting demonstrations of using the IP toolkit. In
particular, check out the deblurring and registration demos that I
showed in class.
Week 2 - Linear Shift-Invariant Systems: an overview
- READING: Review
chapters . This review chapter provides some of the background
material that you might find useful this quarter. In particular, I
recommend reviewing chapter 3 that discusses linear systems.
- Lecture 3 (handout)
gives an overview of continuous time linear time invariant systems.
- Lecture 4 (handout):
We will conclude this discussion with an introduction to the 2-D
linear systems (discrete) and some
examples.
Week 3 - Image Sampling and Quantization
Week 4 - 5
- Lecture 7 (handout).
2-D Discrete Fourier Transform. Your text has a brief introduction to Fourier transform in Chapter
4.
- Lecture 8: DFT discussion continued.
- Lecture 9: Midterm I
- Lecture 10 (handout)
DFT discussion continued. A quick overview of wavelet transforms.
More information on the wavelet transforms can be found in Chapter 7
of your text. Reading of this chapter would be helpful to get
started with your project.
Week 6 & 7- Image Enhancement
- READING: Chapter 3 and Chapter 4 (all sections
except Section 4.6)
- Lecture 11: Spatial Domain Enhancement
- Lecture 12: Spatial Domain Enhancement
- Lecture 13: Spatial Methods continues
- Lecture 14: Part 4 (handout)Frequency
domain enhancement
Week 8-END: Image Coding and Compression
- Lecture 15 (handout):
Image Compression; also an introduction to the ECE/CS 181b course on
computer vision.
- Lecture 16: Midterm II
(covering DFT and Image Enhancement)
- Lecture 17: Image Compression (contd.)
- Lecture 18
(handout): Image
Compression part II (predictive and transform coding).
- Lecture 20 (handout):
Review
Discussion
Session Handouts
Jan 10, 2003: Matlab handout
Feb 20, 2003: Matlab sample
2-D wavelet transform
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