ECE 613 - Image Processing and Visual Communications


Professor Zhou Wang
Office: E5-5113, telephone extension 35301

More information is available at Professor Wang's website and the course website.


Lectures: Fridays 8:30am-11:20am, 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 and perceptual image modeling and processing; and compression, streaming, robustness, scalability and security issues in visual communications.

Course Outline

  1. 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.

  2. 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.

  3. Statistical and perceptual image modeling and processing

    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.

  4. Visual communications: compression, streaming, robustness, scalability and security

    Video compression and standards; video streaming; 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:

  1. Handbook of Image and Video Processing, Bovik Ed., 2nd Edition, Academic Press, 2005.
  2. Digital Image Processing, Gonzalez and Woods, 2nd Edition, 2001.
  3. Digital Image Processing with MATLAB, Gonzalez, Woods & Eddins, Prentice Hall, 2004.
  4. Digital Video Processing, Tekalp, Prentice-Hall, 1995.
  5. Digital Video Image Quality and Perceptual Coding, Wu & Rao Eds., CRC Press, 2005.
  6. Modern Image Quality Assessment, Wang & Bovik, Morgan & Claypool, 2006.
  7. 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.


Every student will work on and present two self-selected projects:

  1. A review project that surveys and comments on a specific topic;
  2. 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.


Review project: 20%

Research project: 30%

Final exam: 50%