MATH3360 - Mathematical Imaging - 2021/22
Announcement
- The final practice has been uploaded. Please try to do it before the exam.
- Please be reminded to fill in the teaching evaluation form online. It will be available from 4:30pm on November 17 till 11:59PM on November 19.
- Q3 in HW3 has been changed to an optional question.
- (2021-10-13) The local Tropical Cyclone Warning Signal No. 8 is still in force. According to the University's regulation, all UG classes during the 1:30 p.m. – 6:15 p.m. session will be suspended. As such, our Math3360 lecture this afternoon (October 13, 4:30pm-6pm) will be canceled.
- Assignment 2 has been posted
- Assignment 1 (pdf and codes) has been updated.
- The due date for Assignment 1 has been postponed to October 4 before 11:59PM.
- (2021-09-17) Submission of homework assignments
- To reduce the risk of spreading the novel coronavirus, you are not recommended to submit your homework assignment physically. As such, you will submit your assignment by uploading the scanned copy via the Blackboard system.
- Log onto https://blackboard.cuhk.edu.hk/ and click on our course 2021R1 Mathematical Imaging (MATH3360). Click on "course contents" and click on "Homework X (Due...)". Follow the instructions therein to upload your solution. An illustration can be downloaded below.
- Please scan your written solution into a single pdf file and save it with the name like: YourStudentID_HW1.pdf. There are several useful apps for you to take a picture of your solution and scan your document (such as CamScanner HD and Microsoft Lens). Combine all your Matlab codes in one folder and compress it with the name YourStudentID_Code1.zip. When you submit your homework using Blackboard, make sure you submit the two files altogether in one submission.
- Assignment 1 has been posted
- There will be no tutorial in the first week.
General Information
Lecturer
-
Ronald Lok Ming LUI
- Office: LSB 207
- Tel: 3943-7975
- Email:
Teaching Assistant
-
Qiguang Chen
- Office: LSB 222B
- Email:
-
Zhipeng Zhu
- Office: LSB 222B
- Email:
Time and Venue
- Lecture: Wed 4:30pm-6pm (Wu Ho Man Yuen Bldg 403); Thurs 1:30pm-2:15pm (MMW 702)
- Tutorial: Thurs 12:30pm-1:15pm (MMW 702)
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, multi-scale 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.
Lecture Notes
- Chapter 1: Basic concepts in Digital Image Processing
- Chapter 2: Image decomposition
- Chapter 3: Image Enhancement in the Frequency Domain
- Chapter 4: Image Enhancement in the Spatial Domain
- Chapter 5: Image Segmentation
Class Notes
- Class Note 1
- Lecture 1 powerpoint
- Class Note 2
- Lecture 2 powerpoint
- Class Note 3
- Lecture 3 powerpoint
- Class Note 4
- Class Note 5
- Lecture 5 powerpoint
- Class Note 6
- Lecture 6 powerpoint
- Class Note 7
- Class Note 8
- Class Note 9
- Lecture 9 powerpoint
- Class Note 10
- Class Note 11
- Lecture 11 powerpoint
- class Note 12
- Lecture 12 powerpoint
- Class Note 13
- Class Note 14
- Lecture 14 powerpoint
- Lecture 15 powerpoint
- Class Note 15
- Class Note 16
- Class Note 17
- Lecture 17 powerpoint
- Class Note 18
- Lecture 18 powerpoint
- Class Note 19
- Class Note 20
Tutorial Notes
- codes (tutorial 1)
- notes (tutorial 1)
- codes (tutorial 2)
- notes (tutorial 2)
- notes (tutorial 3)
- notes (tutorial 4)
- notes (tutorial 5)
- notes (tutorial 6)
- notes (tutorial 7)
- notes (tutorial 8)
- notes (tutorial 9)
Assignments
- Assignment 1
- Assignment 1 (coding)
- Assignment 2
- Assignment 2 (coding)
- Assignment 3 (revised)
- Assignment 3 (coding)
- Assignment 4 (updated)
- Final_practice
Solutions
- Solution to Chapter 1
- Solution to Chapter 2
- Solution to Chapter 3
- HW1 solutions
- HW2 solutions
- HW3 solutions
- Solution to Chapter 4
- Final practice solutions
- HW4 solutions
Assessment Scheme
Homework | 15% | |
Midterm (October 27, 4:30pm-6:30pm, in class) | 35% | |
Final (TBA) | 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 19, 2021 02:27:31