DZO - Digital Image Processing 2025/2026

This course presents an overview of basic methods for digital image processing. Students practice the gained knowledge on six implementation tasks, which will help them understand the concepts and use them to solve practical problems.

Students are expected to know topics from calculus, linear algebra, statistics and probability to the extent taught at CTU in Prague, FEE. Basic programming skills are also expected.

Lecturer:

• Ondřej Drbohlav (ČVUT FEL, Katedra kybernetiky, místnost KN:E-215)

Lectures: Wednesday 11:00-12:30, room T2:C3-54

2025/2026 recorded lectures playlist

Lab tutors:

• Jan Čech (JC) (ČVUT FEL, Katedra kybernetiky, místnost KN:G-2)
• Radoslav Škoviera (RŠ) (ČVUT CIIRC, místnost JP:B-611a)
• Ondřej Drbohlav (OD) (ČVUT FEL, Katedra kybernetiky, místnost KN:E-215)

Labs : Tuesday afternoon , room T2:A4-405

Each assignment is graded. It is possible to get 50 points for work during the semester. To get the assignment (zápočet), 30 points must be gained.

The exam consists of two parts, written test and short oral part. The written part consist of a number of questions and problems covering all the course topics:

• Pointwise operations (simple modifications of pixel intensity, histogram equalization and mapping)
• Fourier transform (formulation, properties, sampling theorem)
• Convolution (formulation, properties, speed-up methods, applications)
• Image deblurring (formulation, solution using Wiener filter)
• Bilateral filter (formulation, speed-up methods, applications)
• Image editing in the gradient domain (formulation, solution, applications)
• Image transformations (1, 2, 3, 4-point)
• Image registration (translation, solution methods)
• Image registration (translation, rotation, and scaling using Fourier-Mellin)
• Image segmentation (formulation, solution using maximum flow)
• Image segmentation (formulation, solution using random walker)

exam questions types

The oral part is held only in case anything in the written test needs to be clarified. The total of 50 points can be obtained for the written test. To pass the exam, a minimum of 20 points is required.

The final grade is determined by the sum of the points obtained from the labs (maximum 60) and from the exam (maximum 40):

• He J., Kim C.-S., Kuo C.-C. J.: Interactive Segmentation Techniques: Algorithms and Performance Evaluation, Springer, 2014.
• Radke R. J.: Computer Vision for Visual Effects, Cambridge University Press, 2012.
• Goshtasby A. A.: Image Registration: Principles, Tools and Methods, Springer, 2012.
• Paris S., Kornprobst P., Tumblin J., Durand F.: Bilateral Filtering: Theory and Applications, Now Publishers, 2009.
• Gonzalez R. C., Woods R. E.: Digital Image Processing (3rd Edition), Prentice Hall, 2008.
• Šonka M., Hlaváč V., Boyle R.: Image Processing, Analysis and Machine vision (3rd Edition), Thomson Learning, 2007.
• Pratt W.: Digital Image Processing (3rd Edition), John Wiley, 2004.

The use of tools like ChatGPT, Copilot, etc. is allowed and even encouraged when used for deepening the understanding of topics related to this course.

The general rule is: Use the AI tools to gain knowledge and understanding and not to delegate understanding and solving the homeworks to them.

Of course, the requirement is that you understand every bit of you code and the idea behind it.