ECE 710 Topic 13 - Fall 2013

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

  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 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.
  4. 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:

  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.

Projects

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.

Grading

Review project: 20%
Research project: 30%
Final exam: 50%