Instructors: Martin Jagersand, Keith Yerex, Neil Birkbeck and Aloak Kapoor
Office hours: Meet Mon, Wed after class (9:50am)

1. Purpose:
   
   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, image transformations, image enhancement and restoration, image coding and compression and a sampling of applications.
   


2. Course Outline:
        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 Restoration
        Image and Movie Compression: gif, jpeg, h261, mpeg
        Overview of human vision
        Computer Vision overview
   
   
3. Text:
   R. Gonzalez and P. Woods, Digital Image Processing, Addison-Wesley, 2002.
        or (possible alternative/supplemental):
   L. Shapiro and G. Stockman Computer Vision Prentice Hall 2001
   
   
4. Homework:
   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.
   
   
5. Grading:
   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 course topics.
         "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.