University of Florida

Department of Electrical and Computer Engineering

EEL 6562, Section 8422 

Image Processing and Computer Vision

Fall 2007

Course Description

This course introduces fundamental concepts and techniques for image processing and computer vision.  We will address 1) how to efficiently represent and process image/video signals, and 2) how to deliver image/video signals over networks.  Topics to be covered include: image acquisition and display using digital devices, properties of human visual perception, sampling and quantization, image enhancement, image restoration, two-dimensional Fourier transforms, linear and nonlinear filtering, morphological operations, noise removal, image deblurring, edge detection, image registration and geometric transformation, image/video compression, video communication standards, video transport over the Internet and wireless networks, object recognition and image understanding. 

Course Prerequisites



Recommended Readings


Dr. Dapeng Wu
Office: NEB 431


Xiaochen Li

Course website:

Meeting Time

Monday, Wednesday, Friday, period 10 (5:10 pm - 6 pm)    

Meeting Room

NEB 101

Office Hours

Structure of the Course

The course consists of lectures, 10 homework assignments, 1 project, and 1 exam.

This course is primarily a lecture course.   I cover all important material in lectures.  Since EEL 3135 and  EEL 4516 are  prerequisites, I assume some previous knowledge about DSP, probability theory and stochastic processes, and hence I will cover some material very quickly.  Thus, depending on what and how much you recall from earlier study, varying amounts of reading in introductory books on DSP, probability theory and stochastic processes (other than the course textbook) may be necessary; these readings are up to the student.  I will only give reading assignments from the course textbook.

Attending lecture is quite important as I may cover material not available in any book easily accessible to you. I use Powerpoint presentation during lecture.  Lecture notes will be posted on the course website before the class.  The lecture is to engage the students in independent thinking, critical thinking, and creative thinking, help the students organize the knowledge around essential concepts and fundamental principles, and develop conditionalized knowledge which tells them when, where and why a certain method is applicable to solving the problem they encounter.  

I do not intend for the WWW material to be a substitute for attending lecture since engaging the students in active thinking, making logical connections between the old knowledge and the new knowledge, and providing insights are the objectives of my lecture.   The lecture notes are posted on the web so that you can miss an occasional lecture and still catch up, and it makes taking notes easier.  To reward those who attend regularly, there will be some lecture-based material in the exam which is not available via the web.

Some problems in the exam will be similar to those in the homework.   As long as you work out the homework by yourself, you will be successful in the exam.   The problems in the exam are designed to prevent the students from memorizing the homework solutions without understanding the fundamental principles, concepts, and theories.   So, to prepare the exam, the first thing is to understand the material; then use the homework problems to test your understanding.

The class project is described here.

Course Outline

Course Objectives

Upon the completion of the course, the student should be able to


Please find handouts here.

Course Policies

Useful links:


Grades Percentage Dates
Homework 40% See the course calendar
Final exam 30% Dec. 12
Project proposal 5% Oct. 24
Project report 25% Dec. 12


Class Project:

The class project will be done in a group of at most four members (that is, 1 or 2 or 3 or 4 members are allowed).   Each project requires a proposal and a final report.   The final report is expected to be in the format of a conference paper.   On Oct. 24, the project proposal (up to 2 pages) is due.  On Dec. 12, the final report (up to 10 pages) is due.   For details about the project, please read here.

Suggested topics for projects are listed here.

Course calendar can be found here.

Related courses in other schools:

George Mason University, Computer Vision

Johns Hopkins University, Image Compression and Packet Video

Polytechnic University, Video Processing

Purdue University, Digital Video Systems

Stanford University, Digital Video Processing

University of California, Berkeley, Multimedia Signal Processing, Communications and Networking

University of Maryland, College Park, Digital Image Processing

University of Maryland, College Park, Multimedia Communication & Information Security: A Signal Processing Perspective

Useful links


ATSC (Advanced Television Systems Committee) & HDTV (High Definition Television):

MPEG (Moving Picture Experts Group):


HSI color model

Compression link:






Digital Video and Multimedia Standards Pages

Digital TV and DVD

Overview of the AVI format

Signal Processing Information Base (SPIB)

Computer Vision

Public Domain Image Databases

CMU Database

Patent licensing

As with MPEG-2 Parts 1 and 2 and MPEG-4 Part 2 amongst others, the vendors of H.264/AVC products and services are expected to pay patent licensing royalties for the patented technology that their products use. The primary source of licenses for patents applying to this standard is a private organization known as MPEG-LA, LLC (which is not affiliated in any way with the MPEG standardization organization, but which also administers patent pools for MPEG-2 Part 1 Systems, MPEG-2 Part 2 Video, MPEG-4 Part 2 Video, and other technologies).

To search patents, visit free patent searching site: