ECE 710 Topic 13 - Image Processing and Visual Communications
Instructor
Professor Zhou Wang
Schedule
Lectures: Mondays 11:30pm-2:20pm, Room EIT 3151, Office hours: To be determined
Course Description
This course covers the fundamental concepts and methods, as well as state-of-the-art theories and technologies, in the field of image processing and visual communications. Topics include fundamental digital image and video processing methods; image analysis and understanding; statistical image modeling and perception; and robustness, scalability and security issues in visual communications.
Course Outline
-
Digital
image
and
video
processing
Intensity transformations for image enhancement; spatial domain linear filtering; frequency domain linear filtering; nonlinear image filtering; image sampling and interpolation; motion and digital video processing. -
Image
analysis
and
understanding
Edge detection; image segmentation; energy preserving and energy compaction; principle component analysis and independent component analysis; sparse representations; wavelet and multiresolution image analysis; non-linear image analysis. -
Statistical
image
modeling
and
perception
Spatial domain image statistics; Fourier domain statistical image models; wavelet domain statistical image models; Markov random field models; computational models of the human visual system; perceptual image quality assessment and processing. -
Visual
communications:
robustness,
scalability
and
security
Error resilience coding and error concealment for robust visual communications; multiple descriptive coding; scalable image and video coding and communications; security issues in multimedia communications; image and video watermarking and data hiding.
Textbooks and References
No required textbook. Electronic copies of lecture notes/slides will be provided. Additional reference books and materials include:
- Handbook of Image and Video Processing, Bovik Ed., 2nd Edition, Academic Press, 2005.
- Digital Image Processing, Gonzalez and Woods, 2nd Edition, 2001.
- Digital Image Processing with MATLAB, Gonzalez, Woods & Eddins, Prentice Hall, 2004.
- Digital Video Processing, Tekalp, Prentice-Hall, 1995.
- Digital Video Image Quality and Perceptual Coding, Wu & Rao Eds., CRC Press, 2005.
- Modern Image Quality Assessment, Wang & Bovik, Morgan & Claypool, 2006.
- Wang & Bovik, “Mean squared error: Love it or leave it? – A new look at signal fidelity measures”, IEEE Signal Processing Magazine, vol. 26, no. 1, pp. 98-177, Jan. 2009.
Projects
Every student will work on and present two self-selected projects:
- A review project that surveys and comments on a specific topic;
- A research project that attempts some new investigations in a specific direction.
The students can work on individual project (preferred) or form teams of 2 to 3 students for larger projects, but the tasks of each team member must be clearly defined, and each team member must submit individual project reports.
Grading
Review
project:
20%
Research
project:
30%
Final
exam:
50%