This introductory course in image processing should give the student a working knowledge of the most commonly used methods and procedures for image enhancement and restoration. The emphasis of the course is on practical results: given an image and a goal for its processing (e.g., feature enhancement, color correction, sharpening, warping, etc.) the student should be able to select and implement an appropriate procedure to achieve that goal. Good practical results often depend on an understanding of the mathematics behind the procedures as well as the ability to write software to implement the mathematics. Thus, there are significant mathematical and computational components to the course. In the past, most students have spent most of their time associated with this course writing and debugging computer programs.
Recommended but not required: An introductory course in digital signal processing (sophomore level) and proficiency in writing computer programs in C, C , MATLAB, or Mathematica. MATLAB is used in the class and the labs.
Richard Alan Peter II, Ph.D. (ECE Department)
Dr. Alan Peters is an Associate Professor of Electrical Engineering in the Department of Electrical Engineering and Computer Science. He is a member of the Center for Intelligent Systems where he directs research on the humanoid robot, ISAC, and on various mobile robots at the Cognitive Robotics Laboratory.