Electrical Engineering and Computer Science

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EECS 556: Image Processing

Instructor: Professor Jeff Fessler

Coverage
This course covers the fundamentals of imaging and image processing. Topics will include image formation, sampling, interpolation, representation, enhancement, restoration, analysis, and compression.

Projects
In lieu of a final exam, students will work in small groups on image processing projects that apply the tools learned in the course as well as using ideas from the contemporary literature.

Textbook(s)
None required. Detailed lecture notes are provided. Several references on reserve at library.

Website
http://web.eecs.umich.edu/~fessler/course/556

Syllabus
Background material

  1. 2D continuous-space signals & systems (216 in 2D) 
  2. 2D Fourier transforms 
  3. Optical imaging basics (elementary Fourier optics and lenses) 
  4. 2D sampling 
  5. 2D discrete-space signals & systems (351 in 2D)        2D DSFT 
  6. Filter design 
  7. 2D DFT / 2D FFT / 2D DCT 

Non-statistical image processing 

  1. 2D interpolation applications: image resizing, rotation, image registration  [Exam 1 about here]
  2. Basic image analysis: edge detection / corner detection
  3. Basic image enhancement: contrast enhancement / image sharpening / image denoising 

Statistical image processing 

  1. Random process image models WSS (wide-sense stationary): image denoising / Wiener filter MRF (Markov random fields): image segmentation [Exam 2 about here]
  2. Image restoration (deblurring)
  3. Sparsity models: image denoising, image deblurring, image compression
  4. Image coding / quantization / compression
EECS 556 Image Processing