Type of Credit: Elective
Credit(s)
Number Registered
With popularity of smartphones where the camera technology has advances tremendously in recent years, everyone can take photos anywhere anytime. According to the statistics, 350 million photos are uploaded on Facebook every day in 2018. All the images/videos presented to you have gone through Image Signal Processing pipeline, which involves various image/video processing technologies, such as, noise removal, image sharpening, gamma correction, image/video compression, image/video restoration, etc.
能力項目說明
Students will learn about various image/video processing technologies in the course so as to understand more about imaging technologies. In addition, students will get familiar with studying and writing papers in related fields.
Week 1
Subject：Introduction & syllabus
Covering topics: Introduction to digital image processing.
Reading: Chapter 1 in the textbook
Teaching/HW: Explain the syllabus and introduce image processing
Hours spent for preview and review: 1 hour each
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Week 2
Subject：Background and math tools in digital image processing
Covering topics: Mathematical concepts
Reading: Chapter 2.6
Teaching/HW: Teach students related math concepts used in digital image processing
Hours spent for preview and review: 2 hour each
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Week 3
Subject：Human visual system, color models
Covering topics: Elements of visual perception, color models
Reading: Chapter 2, 6.1, 6.2
Teaching/HW: How the human visual system works? Illurstrate different color models. Homework 1 will be released. Turn in HW within two weeks after it is released. No late submission is allowed.
Hours spent for preview and review: 2 hour each
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Week 4 & 5
Subject：Processing of binary/gray images
Covering topics: Morphological Image Processing
Reading: Chapter 9
Teaching/HW: Illurstrate morphological operators and their applications.
Hours spent for preview and review: 2 hour each
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Week 6, 7, & 8
Subject：Contrast enhancement
Covering topics: Histogram equalization, specification, and stretching.
Reading: Chapter 3
Teaching/HW: Illurstrate various techniques for contrast enhancement. Homework 2 will be released. Turn in HW within two weeks after it is released. No late submission is allowed.
Hours spent for preview and review: 2 hour each
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Week 9 & 10
Subject：Edge detection and sharpening
Covering topics: Zero-crossing, various edge-detection operators
Reading: Chapter 6.6, 10.2
Teaching/HW: Illurstrate various edge dectors, and how to sharpen images based on edges. Homework 3 will be released. Turn in HW within two weeks after it is released. No late submission is allowed.
Hours spent for preview and review: 2 hour each
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Week 11 & 12
Subject：Noise removal
Covering topics: Noise models, noise reduction, image smoothing
Reading: Chapter 5
Teaching/HW: Introduce noise models, smoothing filters, and how to use them. Students needs to turn in the final project proposal by the end of Week 12.
Hours spent for preview and review: 2 hour each
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Week 13, 14 & 15
Subject：Image/video compression
Covering topics: Introduction to image and video compression
Reading: Chapter 8
Teaching/HW: Compression concepts and designs
Hours spent for preview and review: 2 hour each
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Week 16 & 17
Subject：Image restoration
Covering topics: Image degradations, and how to try to restore such images
Reading: Chapter 5
Teaching/HW: Teach students different image restoration techniques
Hours spent for preview and review: 2 hour each
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Week 18
Subject：Final presentation
Teaching/HW: Present final projects
Hours spent for preview and review: 2 hour each
1. Homework (45%) – three homework assignments
2. Final Presentation (55%) – Choose one recently published paper (from IEEE/ACM journals or Top-tier Conferences) and study it. At the end of the semester, present the paper you chose. A bonus (up to 10%) will be given if experimental results are tested by running the code (obtained from the authors or implemented by yourselves) and/or an "better" method is proposed.
Textbook: Digital Image Processing by Gonzalez and Woods. 4th edition, Pearson, 2017
References:
1. Digital Image Processing Using Matlab, 2nd edition, 2009
2. Introduction to Digital Image Processing, William K. Pratt, 1st edition, CRC Press, 2013
3. Computer Vision: Algorithms and Applications, Springer-Verlag, 2011
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