EE168 Course description
Digital
pictures today are all around us, on the web, on DVDs, and on digital satellite
systems, for example. In this course we
will investigate the creation and manipulation of digital images by
computer. The course will consist of
theoretical material introducing the mathematics of images and imaging, as well
as computer laboratory exercises designed to introduce methods of realworld
data manipulation. The format will consist of lectures on Mondays and Wednesdays, with Fridays devoted to lab exercises. The lab exercises will
introduce various image processing topics, which will be examined in more
detail in the homework assignments. Topics will include representation of twodimensional data, time and
frequency domain representations, filtering and enhancement, the Fourier
transform, convolution, interpolation, color images, and techniques for
animation. Lecture notes will be handed
out routinely, and special handouts will also be distributed from time to time.
Reading assignments will be given from the recommended text or from other sources, most of
which will be on reserve at Terman Engineering Library. Homework assignments
will generally be given out on Thursdays and collected on Thursdays, with the
results handed back during the following week. Cooperation on homework is
encouraged, but you are expected to keep the work on an approximately equal
basis. There will be one midterm exam plus a final term project. Grades will be
based on homework, the midterm exam, and the project, with weightings of
approximately 40% on the final project, 25% on the midterm, 30% on homework,
and up to 5% extra credit problems.
We will implement many of the concepts presented in the course in a series ofcomputer exercises designed to acquaint you with computer manipulation of
actual image data. The Stanford Center for Image
Engineering (SCIEN) Lab in 021 Packard is available to you, and both the TA and
professor will be available in or near the Lab on Thursdays to help with the
exercises. Additional problems will be
given as homework. The resources
required for the homework problems will be within the capability of the class
computer accounts in the Leland system, but you are free to implement them on
any machine on which you are comfortable. Most of the exercises can be done
using Matlab, although many examples will be given using C and Fortran language
routines. Again, you are permitted to implement the exercises using any
language or system you wish it is the result that counts.
A
rough schedule of the course is as follows, with more details in the course
syllabus web page. We first introduce the ideas concerning how we define
images and imaging. The next several weeks will cover how we apply systems
theory, such as transforms and impulse functions, to twodimensional imaging
systems. This will be accompanied by several computer implementation exercises
designed to introduce you to the real world of data, where things are often not
as tidy as they may be in more theoretical circumstances. Topics such as
sampling and interpolation, important in all data manipulation, follow. We will
also introduce principles of color and color manipulation for special image
effects. After the midterm, we will
begin to apply the theoretical constructs from the first half of the course to
a series of examples. Some examples
will be illustrations of various methods to display 2D or 3D information,
such as perspective viewing and the generation of anaglyphs (those redgreen
images creating stereo effects if you wear the funny glasses.) We will
culminate by addressing computer animations, where we will design and create a
series of digital images that will comprise a digital movie. The digital movies that you create, along
with a written report, will serve as the final project.
The final project will be a team effortconsisting of the design and animation of a digital movie incorporating the
techniques introduced in the class. You will be free to choose your own
subject; several examples will be provided that you may use.
Textbook info
Recommended, but not required: Computer Vision and Image Processing, by Scott Umbaugh, PrenticeHall, Inc., Upper Saddle River, New Jersey, 1998.
Note: this book is out of print, and we will distribute useful excerpts from it as required. If you wish to pick up your own copy from a secondary source, it is a decent introduction to image processing.
Prerequisites
None. This is an introduction to the subject of digital image processing, and should be
approachable by most undergraduates. The labwork does entail programming in
Matlab, however. No experience with Matlab is required, as initially we will give you most of the commands necessary to implement the exercises.
Course structure
The course will meet two
times a week, generally once in Hewlett 103 on Tuesdays,
and on Thursdays in the SCIEN Lab located in the basement of Packard,
room 021. There will be reading assignments from the text plus handouts in
class. Some reading will be of documents available primarily over the World
Wide Web.
