Instructors: Martin Jagersand, Keith Yerex, Neil Birkbeck and Aloak Kapoor
Office hours: Meet Mon, Wed after class (9:50am)
To introduce students to the fundamentals of image processing
and to give them an opportunity to utilize the techniques on
real images. The topics include image fundamentals, camera models,
transformations, image enhancement and restoration, image coding
and compression and a sampling of applications.
Introduction: cameras, image representation and display
Point/pixel-based processing and enhancement
Camera and imaging geometry;
Image Transforms: Fourier, cosine and KL transforms;
Transform-based processing and enhancement.
Filtering, thresholding and edge detection.
Image and Movie Compression: gif, jpeg, h261, mpeg
Overview of human vision
Computer Vision overview
R. Gonzalez and P. Woods, Digital Image Processing,
or (possible alternative/supplemental):
L. Shapiro and G. Stockman Computer Vision Prentice Hall 2001
Lab/homework assignments will be given on the WEB two weeks
before the due date, and will be collected in class on the due
date. No late submissions. Assignments are individual.
University plagiarism policies apply.
Assignments: 45%, (three assignments)
Exams: midterm 20%, final 35%
A grade of
"satisfactory" requires understanding of about 3/4 of
the course topics.
"Good" requires understanding of all the
"Excellent" requires trancending merely reproducing
taught topics, and showing an ability e.g. to synthesise solutions by
combining a knowledge and insights from several course topics.