MMAT5390 - Mathematical Image Processing - 2019/20

Announcement

• (9/27) To access the files, the username is "mmat5390", and the password is still the same.
• (10/9) Dear all, if you would like to submit your HW via email, you are strongly advised to directly send it to the TA. That would simplify a lot.
• (10/21) Your HW1 is graded and returned to the assignment box for your retrieval, if you handed in a hard copy. For those who submitted via email, TA should have sent you your score in his reply. If you did submit through email but did not receive TA's reply by now, attach your old email and send it to TA again.
• (10/22) Due to class suspension on Oct 9, we have postponed our midterm exam to Nov 6. The coverage will be from Lecture 1 to Lecture 7.
• (10/30) Your HW2 is returned. Same as before: if you sent your HW2 to me via email and you have not receive your score, forward that email to the TA again.
• (11/21) Class Notes 9 to 12 have been uploaded. Chapter 5 of the lecture note has also been uploaded. Although classes have been suspended, you are recommended to read and learn these interesting mathematical models for image processing.
• (11/25) Due to the severe damage of facilities on campus, Term 1 of 2019/20 has been abruptly shortened. For MMAT5390, the grades will be determined according to the results from the completed continuous assessment, including mid-term examination and homework assignment. More specifically, your final grade will be determined based on the following assessment: - Homework Assignment: 30% - Midterm examination: 70%

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General Information

Lecturer

• Ronald Lok Ming LUI
  • Office: LSB 207
  • Tel: 3943-7975
  • Email:

Teaching Assistant

• Ho LAW
  • Office: LSB 222B
  • Tel: 3943-7963
  • Email:

Time and Venue

• Lecture: Wed 18:30 - 21:15, YIA LT3

Course Description

This course gives an introduction on mathematical models and techniques for various image processing tasks. Our focus will be on the mathematical aspects of different imaging problems. A wide array of topics will be covered, including image restoration (denoising, deblurring), image segmentation, image compression, image registration, multi-scale image analysis and so on.

Lecture Notes

• Chapter 1
• Chapter 2
• Chapter 3
• Chapter 4
• Chapter 5

Class Notes

• Lecture 1 Class Note
• Lecture 1 Powerpoint
• Lecture 2 Class Note
• Lecture 2 Powerpoint
• Lecture 3 Class Note
• Lecture 3 Powerpoint
• Lecture 4 Class Note
• Lecture 4 Powerpoint
• 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
• More explanation on low/high frequency components in DFT
• Lecture 9 Class Note
• Lecture 9 Powerpoint
• Lecture 10 Class Note
• Lecture 10 Powerpoint
• Lecture 11 Class Note
• Lecture 11 Powerpoint
• Lecture 12 Class Note
• Lecture 12 Powerpoint

Assignments

• Assignment 1
• Assignment 2(Amended on 10/12)
• Assignment 3

Quizzes and Exams

• Practice Midterm(Amended on 11/2)
• Practice Midterm Solution(Amended on 11/4)

Solutions

• Assignment 1 solution
• Assignment 2 solution

Assessment Scheme

Homework		30%
Midterm (Nov 6, 6:30pm - 8pm)		30%
Final		40%

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.

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Assessment Policy

Last updated: November 26, 2019 15:32:38