From NYU Video Lab

HomePage: EL-GY 6123 Image and Video Processing

Course Description:
This course introduces fundamentals of image and video processing, including color image capture and representation; contrast enhancement; spatial domain filtering; two-dimensional (2D) Fourier transform and frequency domain interpretation of linear convolution; image sampling and resizing; multi-resolution image representation using pyramid and wavelet transforms; feature point detection and global alignment between images based on feature correspondence; geometric transformation, image registration; video motion characterization and estimation; video stabilization and panoramic view generation; image and video segmentation; selected advanced image processing techniques; basic compression techniques and standards (JPEG image compression standard; wavelet transform and JPEG2000 standard; video compression using adaptive spatial and temporal prediction; video coding standards (MPEGx/H26x); Stereo and multi- view image and video processing (depth from disparity, disparity estimation, video synthesis, compression). Students will learn to implement selected algorithms in Python. A term project will be required.

Graduate status. EL-GY 6113 and EL-GY 6303 preferred but not required. Undergraduate students must have completed EE-UY 3054 Signals and systems and EE-UY 2233 Probability.

Professor Yao Wang, MTC2 Room 9.122, (646)-997-3469, Email: yaowang at nyu dot edu. Homepage

Teaching Assistants:
Chenge Li (MTC2 Room 9.123, cl2840 at nyu dot edu) and Amirhossein Khalilian-Gourtani (MTC2 Room 9.130B, akg404 at nyu dot edu)

Course Schedule:
Friday 12:25 AM-2:55PM, Room RH215.

Office Hour:
Yao Wang: Wed. 4- 5:30PM and Fri. 10:30-12:00 or appointment by email.
TAs: Chenge Li: Tue. 4:00-5:00 PM and Fri. 3:00-4:00 PM or appointment by email
Amirhossein Khalilian-Gourtani: Mon: 10:00 am - 11:30 am and Thur: 4:30 pm - 6:30 pm or by appointment

Text Book/References:

  1. Richard Szeliski, Computer Vision: Algorithms and Applications. (Available online:"Link") (Cover most of the material, except sparsity-based image processing and image and video coding)
  2. (Optional) Y. Wang, J. Ostermann, and Y.Q.Zhang, Video Processing and Communications. Prentice Hall, 2002. "Link" (Reference for image and video coding, motion estimation, and stereo)
  3. (Optional) R. C. Gonzalez and R. E. Woods, Digital Image Processing, Prentice Hall, (3rd Edition) 2008. ISBN number 9780131687288. "Link" (Good reference for basic image processing, wavelet transforms and image coding).

Grading Policy:
Exam: 40%, Final Project: 30%, Programming assignments: 20%, Written assignments: 10%.

Homework Policy:
Written HW will be assigned after each lecture and due at the beginning of the following lecture time. Programming assignment will be due as posted. Late submission of written assignment and programming assignment will not be accepted unless under extraordinary circumstances and must be approved in advance by the instructor. Students can work in teams, but you must submit you own solutions. For programming assignment, please include your code (with documentation) and results (plots etc.) and discussions.

Project Guideline: Link

Suggested Project List: Link (Updated 02/06/2018)

Sample Data:
Sample Images
Middelbury Stereo Image Database

Links to Resources (lecture notes and sample exams) in Previous Offerings:

Other Useful Links

* Example codes and images used in the above guide: Link

Tentative Course Schedule

Sample Exams:

Sample Images:

Policy on Academic Dishonesty:
The School of Engineering encourages academic excellence in an environment that promotes honesty, integrity, and fairness. Please see the policy on academic dishonesty: Link

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