Digital Image Processing

The course is not on the list Without time-table
Code Completion Credits Range Language
NI-DZO Z,ZK 4 2P+1C Czech
Daniel Sýkora (guarantor)
Daniel Sýkora (guarantor)
Department of Software Engineering

This course presents a comprehensive overview of modern methods for processing digital images and video. It mainly deals with practical algorithms used in professional image processing tools that are both easy to implement and have an interesting theoretical basis. Seemingly boring theorems from calculus, discrete mathematics, statistics and computer science come to life in visually attractive applications.


Elements of Calculus (BIE-ZMA)

Linear Algebra (BIE-LIN)

Probability and Statistics (BIE-PST)

Programming and Algorithmics 2 (BIE-PA2)

Graph Algorithms and Complexity Theory (BIE-GRA)

Syllabus of lectures:

1. Monadic Operations

2. Fourier Transform

3. Convolution

4. Linear Filtering

5. Non-linear Filtering

6. Image Editing

7. Image Deformation

8. Image Registration 1

9. Image Registration 2

10. Image Registration 3

11. Image Segmentation 1

12. Image Segmentation 2

13. Reserved

Syllabus of tutorials:

1. Introduction to assignments

2. Selection of assignment

3. Reading paper

4. Impelmentation

5. Testing

6. Presentation & submission of reports

Study Objective:

The aim of the course is introduce a subset of digital image processing techniques that find direct application in practice. It also provides insight into their theoretical background, allowing to understand basic mathematical principles, that give inspiration to solution of more general problems.

Study materials:

[1] He J., Kim C.-S., Kuo C.-C. J.: Interactive Segmentation Techniques: Algorithms and Performance Evaluation, Springer, 2014.

[2] Radke R. J.: Computer Vision for Visual Effects, Cambridge University Press, 2012.

[3] Goshtasby A. A.: Image Registration: Principles, Tools and Methods, Springer, 2012.

[4] Paris S., Kornprobst P., Tumblin J., Durand F.: Bilateral Filtering: Theory and Applications, Now Publishers, 2009.

[5] Gonzalez R. C., Woods R. E.: Digital Image Processing (3rd Edition), Prentice Hall, 2008.

[6] Šonka M., Hlaváč V., Boyle R.: Image Processing, Analysis and Machine vision (3rd Edition), Thomson Learning, 2007.

[7] Pratt W.: Digital Image Processing (3rd Edition), John Wiley, 2004.

Further information:
No time-table has been prepared for this course
The course is a part of the following study plans:
Data valid to 2020-10-27
For updated information see http://bilakniha.cvut.cz/en/predmet6174506.html