Instructor: Guido Gerig , home : http://www.sci.utah.edu/~gerig/
TA: Miaomiao
Zhang , picture
Time: Mon,Wed 10:45PM -
12:05PM
Place: MEB 3105
Text:
Digital Image Processing, 3rd Edition , Rafael C. Gonzalez and Richard
E. Woods, Prentice Hall, ISBN 013168728X, click
here for more
Another good reference text: Digital Image Processing, Kenneth R.
Castleman, Prentice Hall
This
is an introductory course in processing grey-scale and color images --- taught
at the graduate level. This course will cover both mathematical fundamentals
and implementation. It will introduce students to the basic principles of
processing digital signals and how those principles apply to images. These
fundamentals will include sampling theory, transforms, and filtering. The
course will also cover a series of basic image-processing problems including
enhancement, reconstruction, segmentation, feature detection, and compression.
Assignments will include several projects with software implementations and
analysis of real data.
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Date
|
Lecture
Number |
Topic
|
8/23
|
L1-2
|
Intro
to Probability and Images: Images, Points, Functions |
8/30
|
L3-4
|
Histogram
Analysis, and Mapping |
9/06
|
-- |
Labor
Day holiday |
9/08 |
L5 |
Histogram
Equalization |
9/13
|
L6-7 |
Filtering
with Neighborhoods: Linear Filtering |
9/20
|
L8-9 |
Fourier
Transforms and Filtering |
9/27
|
L10-11
|
Filtering
with Neighborhoods ctd.: Nonlinear Filtering |
10/04
|
L12-13 |
Geometric
Transformations and Warping |
10/11
|
--
|
*Fall
Break 10/11 to 10/16* |
10/18
|
L14-15
|
Geometric
Transformations and Warping: RBFs |
10/25
|
Midterm
Exam on 10/25 |
Covering
all material discussed so far |
10/27 |
L16 |
Image
Mosaicing/Stitching |
11/1
|
L17-18
|
Canny
Optimal Edge and Line Detector |
11/8
|
L19-20
|
Grouping
of pixels to structures: Hough Transform |
11/15
|
L21-22
|
Hough
Transform for Arbitrary Shapes |
11/22
|
L23-24
|
Deformable
model segmentation (Snakes) |
11/29
|
L25-26
|
Mathematical
morphology (binary) |
12/06
|
L27
|
Mathematical
morphology (graylevel) |
12/13
|
FINAL
PROJECT Due |
Midnight
(REPLACES FINAL EXAM) |
Students
are expected to work on their own, as instructed by
the Professor. Students may discuss projects with other individuals
either in the class or outside the class, but they may not receive code or
results electronically from any source that is not documented in their report.
Students must write their own code, conduct their own experiments, write their
own reports, and take their own tests. Any use of sources (for projects or
tests) that are not specifically given to the student by the Professor or TA,
must be discussed with the Professor or TA or documented in the report. Any
student who is found to be violating this policy will be given a failing grade
for the course and will be reported to the authorities as described in the
University's Student
Code.
The
University of Utah seeks to provide equal access to its programs, services and
activities for people with disabilities. If you will need accommodations in the
class, reasonable prior notice needs to be given to the Center for Disability
Services, 162 Olpin Union Building, 581-5020 (V/TDD).
CDS will work with you and the instructor to make arrangements for
accommodations. All written information in this course can be made available in
alternative format with prior notification to the Center for Disability
Services.
Projects
will be done by individuals on topics assigned approximately every 3
weeks by the professor (i.e. there will be approximately 4-5 projects).
Projects will require submission of the project code and findings in an html
format (in a directory readable by a web browser). Project programming will be
done in either MATLAB (the basic package --- no extra
toolkits) or C++ using the Vispack
library for image I/O and basic image operations.
Weighted contribution of
projects and exams to final grade: