Digital Image Processing


This course on digital image processing covers

  • Discrete-time signals and digital images
  • Fourier analysis using the fast Fourier transform
  • Image Processing in the frequency domain
  • Denoising and resampling
  • Digital image fundamentals
  • Image enhancement in the spatial and frequency domain
  • Image quality assessment and restoration
  • Image compression

Exercises include programming using MATLAB.


None, if taken as a master course.
If taken as an advanced course in the bachelor program:

  • basic math courses offered in our bachelor programs
  • algorithms and data structures
  • introduction to computer science including programming

Previous participation in a digital signal processing course would be helpful, but is not required. We will review DSP materials as necessary.

Course Literature

  • Rafael Gonzalez, Richard Woods, Digital Image Processing, 4th Edition, Pearson. (Second Edition available online).
  • Rafael Gonzalez, Richard Woods, Steven Eddins, Digital Image Processing using MATLAB 2e, 2009. 
  • Alan Oppenheim, Ronald Schafer, John Buck, Discrete-time Signal Processing, Prentice-Hall, 2010.
  • Alan Oppenheim, Ronald Schafer, John Buck, Zeitdiskrete Signalverarbeitung, 2. Auflage, Pearson Studium, 2004.
  • Vinay Ingle, John Proakis, Digital Signal Processing using MATLAB, Third Edition, Cengage Learning, 2012. (Available online).

Literature on Complex Calculus