LE415: Digital Image Processing


Course Information

Description: Historical development of image processing. Image data structures. Image Preprocessing. Image enhance ment. Image classification. Image postprocessing. Image compression and restoration. Figure modeling. Computer animation. Contour mesh conversion. Applications of image processing. Introduction to computer vision.

Course staff and contact information:

Problem sets: You need to do problem sets to reinforce what you learn in lecture. Copying other people's work is strictly prohibited.

Grading: Your grade in this course will be based principly on attendance, problem sets and exams as follows.

Attendance 10%
Problem sets 30%
Midterm exam 30%
Final exam 30%

Software: You will need MATLAB to implement some examples in class and to do your homework. If you are not familiar with MATLAB, please refer to the MATLAB and Image Processing primer provided at www.fundipbook.com

Image Viewer: free software www.xnview.com

Textbooks & Materials:

  1. Rafael C. Gonzalez and Richard E. Woods, Digital Image Processing, 3rd ed, Pearson Prentice Hall, 2010.
  2. Chris Solomon and Toby Breckon, Fundamentals of Digital Image Processing: a Practical Approach with Examples in MATLAB, John Wiley & Sons, 2011 (optional).


  Topic Reading Lecture Notes Problem Set Solution
  Syllabus   pdf
I Introduction G&W ch. 1 slides
II Digital Image Fundamentals G&W ch. 2 slides    
III MATLAB Tutorial   slides    
IV Spatial Enhancement G&W ch. 3 slides1
HW1 Sol1
V Frequency-domain Processing G&W ch. 4 slides HW2 Sol2
VI Image Restoration G&W ch. 5.1-5.9 slides HW3 Sol3
VII Image Compression G&W ch. 8.1-8.2 slides    
VIII Morphological Processing G&W ch. 9.1-9.5 slides HW4 Sol4
IX Image Segmentation G&W ch. 10.1-10.4 slides1
HW5 Sol5
X Color Image Processing G&W ch. 6 slides
XI Object Recognition G&W ch. 12 slides