Digital Image Processing
Content
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.
Prerequisites
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).