MATH3360  Mathematical Imaging  2017/18
Announcement
 There is no tutorial in the first week of class.
 HW1 has been posted. It will be due on September 22 (Friday) before 6pm. Please hand in your HW to the Math3360 HW mailbox outside the MATH general office.
 HW2 has been posted. Please email your programming solution to sylvesterqiu@gmail.com.
 HW3 has been posted. Please email your programming solution to sylvesterqiu@gmail.com.
 HW4 has been posted. Please email your programming solution to sylvesterqiu@gmail.com.
General Information
Lecturer

Prof. Ronald Lok Ming LUI
 Office: 207
 Tel: 39437975
 Email:
Teaching Assistant

Mr. Chun Pong LAU
 Office: 222B
 Email:

Mr. Di QIU
 Office: 222B
 Email:
Course Description
This course gives an introducion on mathematical models and techniques for various image processing tasks. A wide array of topics will be covered, including image restoration (denoising, deblurring), image segmentation, image compression, image registration, feature detection, multiscale image analysis and so on. Students will become familiar with essential mathematical techniques for imaging tasks, such as image processing in the spatial domain (using gradient, Laplacian, convolution) and frequency domain (using Fourier / wavelet transform). Differential equation based techniques will also be discussed.
Our goal of this course is to help students appreciate the importance of mathematics in imaging sciences. Students will have a chance to learn how existing image processing techniques are built based on mathematical theories. Upon successful completion of the course, interested students are also welcome to approach the lecturer to ask for opportunities to work on some research projects related to mathematical image processing.
Textbooks
 Will be based on the lecture notes, class notes and ppt uploaded on the course website.
Lecture Notes
 Chapter 1: Basic concepts in digital image processing
 Chapter 2: Image decomposition & image compression
 Chapter 3: Image enhancement in the frequency domain
 Chapter 4: Image enhancement in the spatial domain
 Chapter 5: Image segmentation
Class Notes
 Lecture 1 Class Note
 Lecture 1 powerpoint
 Lecture 2 Class Note
 Lecture 3 Class Note
 Lecture 4 Class Note
 Lecture 5 Class Note
 Lecture 5 powerpoint
 Lecture 6 Class Note
 Lecture 6 powerpoint
 Lecture 7 Class Note
 Lecture 7 powerpoint
 Lecture 8 Class Note
 Lecture 8 powerpoint
 Lecture 9 Class Note
 Lecture 10 Class Note
 Lecture 11 Class Note
 Lecture 11 powerpoint
 Lecture 12 powerpoint
 Lecture 13 Class Note
 Lecture 13 powerpoint
 Lecture 14 Class Note
 Lecture 14 powerpoint
 Lecture 15 Class Note
 Lecture 16 Class Note
 Lecture 16 powerpoint
 Lecture 17 Class Note
 Lecture 17 powerpoint
 Lecture 18 Class Note
 Lecture 18 powerpoint
 Lecture 19 Class Note
 Lecture 19 powerpoint
 Lecture 20 Class Note
 Lecture 21 Class Note
 Lecture 21 powerpoint
 Lecture 22 Class Note
 Lecture 23 Class Note
 Lecture 23 powerpoint
 Lecture 24 Class Note
Tutorial Notes
 Tutorial1 (Last update: 13/9/2017)
 Tutorial1 code (Last update: 13/9/2017)
 Tutorial2 (Last update: 20/9/2017)
 Tutorial2 code (Last update: 20/9/2017)
 Tutorial3 (Last update: 30/9/2017)
 Tutorial3 code (Last update: 30/9/2017)
 Tutorial4 (Last update: 4/10/2017)
 Tutorial4 code (Last update: 4/10/2017)
 Tutorial5 (Last update: 14/10/2017)
 Tutorial7 (Last update: 25/10/2017)
 Tutorial8 (Last update: 1/11/2017)
 Tutorial9 (Last update: 9/11/2017)
 Tutorial10 (Last update: 15/11/2017)
 Tutorial11 (Last update: 22/11/2017)
 Tutorial11 code (Last update: 22/11/2017)
 Tutorial12 (Last update: 29/11/2017)
Assignments
 Homework 1 (Due on Sept 22, Fri, by 6pm. Please submit your HW to the HW mailbox outside the General Office.)
 Homework 2 (Due on Oct 6, Fri, by 6pm. Please submit your HW to the HW mailbox outside the General Office.)
 Homework 2 Programming Exercise (Due on Oct 6 6pm.)
 Homework 3 (Due on Oct 20, Fri, by 6pm. Please submit your HW to the HW mailbox outside the General Office.)
 Practice Exercise I (oct16 updated), no need to hand in
 Homework 4 (Due on Nov 10, Fri, by 6pm. Please submit your HW to the HW mailbox outside the General Office.)
 Homework 4 Programming Exercise (Due on Nov 10 6pm.)
 Homework 5 (Due on Nov 24, Fri, by 6pm. Please submit your HW to the HW mailbox outside the General Office.)
 Homework 5 Programming Exercise (Due on Nov 24 6pm.)
 Practice Exercise II
 Homework 6 (Optional)
Quizzes and Exams
Solutions
 HW1 solution
 HW2 solutoin
 Selected solutions for midterm practice exercise (sol Ex 2,3,10,12,20,22,23,24,25 added)
 HW3 solution
 HW4 solution
 HW5 solutions
 Selected solutions for practice exercise II
Assessment Scheme
Homework  15%  
Midterm (2:30pm4:15pm, October 18, 2017 at LSB LT4 in class)  35%  
Final  50% 
Honesty in Academic Work
The Chinese University of Hong Kong places very high importance on honesty in academic work submitted by students, and adopts a policy of zero tolerance on cheating and plagiarism. Any related offence will lead to disciplinary action including termination of studies at the University. Although cases of cheating or plagiarism are rare at the University, everyone should make himself / herself familiar with the content of the following website:
http://www.cuhk.edu.hk/policy/academichonesty/and thereby help avoid any practice that would not be acceptable.
Assessment Policy Last updated: December 03, 2017 15:22:48