(2021 Fall)

Video Signal Processing

Instructor: Prof. Hsueh-Ming Hang (杭學鳴教授)
Email: hmhang@nctu.edu.tw
Lecture: Thursday 9:10-12:00, 科研大樓334

Teaching Assistant: (None)

Course Description:
Image and video processing and coding is used in our daily life such as digital camera, TV, MP3 audio, and internet music/video (mobile devices). This course introduces the basic theory and various techniques used in video signal compression. We introduce the commonly used techniques such as Huffman coding, arithmetic coding, subband/wavelet coding, motion-compensated DCT coding, etc. This course also covers briefly popular compression standards such as JPEG, MPEG, H.264, H.265, and the latest H.266. We now also introduce the most recent learning-based (neural net) image/video compression technology, which is a rapid growing topic.

Reminder: The VSP term project report is due in the midnight January 18.

提醒大家: 期末報告繳交日為1月18日午夜。 繳交(A) (論文格式) Part I (Motion estimation)一份;Part II (paper study) 一份; (B) (投影片格式) 口頭報告Part I and Part II.

1) According to the School’s instructions, starting from Oct. 14, our class will be face-to-face (physical) at Room 334, Technology Research Building/Sixth Academic Building (科研大樓334).
2) From Oct 14, the recorded lecture videos are located at 北科i學園 (Taipei Tech i-school Plus). 自10月14日起,課堂錄影位於北科i學園。
3) Reminder: HW set #1 due date is Oct. 28 (Thursday) 9AM.

Text book:
1. Class notes
2. K. Sayood, Introduction to Data Compression, 5th ed., Morgan Kaufman, 2017.
Recommended Readings::
1. J.-R. Ohm, Multimedia Signal Coding and Transmission, Springer, 2015.
2. D A. Murat Tekalp, Digital Video Processing, 2nd Ed, Pearson College Div, 2015.
3. Salomon, and G. Motta, Handbook of Data Compression, 5th, Springer, 2010.
4. R.C. Gonzalez and R.E. Woods, Digital Image Processing, 4th, Pearson, 2018.

* Computer Assignments: 45 % (2-3 assignments)
* Final Examine: 20% (2 hours, closed book, two pages of (one-sided) A4 notes)
* Final project (Report): 35% (written report + 20-min oral)

Signals and Systems, Digital Signal Processing, Digital Image Proc.

Lecture Notes:


Homework Samples:

Recorded Lectures:
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