General Information

Instructor: Alexander Wong E2-1303D (a28wong 'at'
TA: Abhishek Kumar E2-1303D (a42kumar 'at'
Text: Gonzalez and Woods, Digital Image Processing, 3rd edition (2nd edition acceptable as well), Prentice Hall, 2008.
Class Times: Tu Th 10:00AM-11:20AM E5 6004
Tutorials: Th 9:00AM-9:50AM E5 6004
Labs: W 1:30PM-4:20PM E2 1302B
Midterm exam:Thursday, October 27, 2011, 9:30AM-11:30AM, E5 6004
Final exam: TBA

Lecture Slides

Lecture slides will be made available throughout the duration of the course.

Homework Assignments

Homework assignments are optional and are useful for helping you understand the concepts of the course. Homework assignments will be made available throughout the duration of the course. The question numbers are based on the 3rd edition.
  • Chapter 2: 2.9, 2.11, 2.12, 2.18
  • Chapter 3: 3.3a, 3.5a, 3.6, 3.15a, 3.18a, 3.21, 3.24
  • Chapter 4: 4.5, 4.16a, 4.21, 4.28
  • Chapter 5: 5.12, 5.16, 5.18, 5.22
  • Chapter 6: 6.4, 6.8a, 6.12, 6.14, 6.18, 6.20, 6.24

Past Exams



Lab instructions will be made available before each lab.


The term project, to be done as individuals, can related to an image processing concept of their choice. The range of project topics is very broad, ranging from a survey of existing image processing techniques in a particular area of research, a comparative analysis of state-of-the-art image processing algorithms to new image processing algorithms that you develop yourself. As part of the project requirements, each individual needs to submit a term project report. Each individual is also required to present your work to the class in a 5 minute presentation. All materials, publications, and external resources used must be fully cited using IEEE reference style format. Some project ideas include:
  • Image inpainting
  • Image denoising
  • Image, texture, and video compression
  • Image super-resolution
  • Image registration
  • Content-based image retrieval
  • Image deblurring
  • Image watermarking
  • Edge detection
  • Image morphing
  • Texture representation
  • Image warping and deformation
  • Medical image reconstruction (e.g., MR reconstruction, CT reconstruction)
  • Applications of image processing (e.g., biomedical, astronomical, surveillance, etc.)
  • Color object detection and tracking