Digital Image

Corequisite:

The course cannot be taken simultaneously with:

Digital image (AE4M33DZO)
Digital image (A4M33DZO)
Digital image (B4M33DZO)
Advanced Interactive Image Manipulation (B4M39AIM)

The course is a substitute for:

Digital image (AE4M33DZO)
Digital image (A4M33DZO)
Digital image (B4M33DZO)

Garant předmětu:

Daniel Sýkora

Lecturer:

Daniel Sýkora

Tutor:

Jan Čech, Ondřej Drbohlav, Vojtěch Pánek, Daniel Sýkora, Radoslav Škoviera

Supervisor:

Department of Cybernetics

Synopsis:

This course presents an overview of basic methods for digital image processing. It deals with practical techniques that have an interesting theoretical basis but are not difficult to implement. Seemingly abstract concepts from mathematical analysis, probability theory, or optimization come to life through visually engaging applications. The course focuses on fundamental principles (signal sampling and reconstruction, monadic operations, histogram, Fourier transform, convolution, linear and non-linear filtering) and more advanced editing techniques, including image stitching, deformation, registration, and segmentation. Students will practice the selected topics through six implementation tasks, which will help them learn the theoretical knowledge from the lectures and use it to solve practical problems.

Requirements:

It is expected that the student is familiar with calculus, linear algebra, probability and statistics to the depth taught at FEL CVUT.

Syllabus of lectures:

1. Monadic Operations

2. Fourier Transform

3. Convolution

4. Linear Filtering

5. Non-linear Filtering

6. Image Editing

7. Image Deformation 1

8. Image Deformation 2

9. Image Registration 1

10. Image Registration 2

11. Image Registration 3

12. Image Segmentation 1

13. Image Segmentation 2

14. Reserved

Syllabus of tutorials:

1. Introduction to Matlab

2. Monadic Operations 1

3. Monadic Operations 2

4. Fourier Transform 1

5. Fourier Transform 2

6. Linear and Non-linear Filtering 1

7. Linear and Non-linear Filtering 2

8. Image Editing 1

9. Image Editing 2

10. Image Registration 1

11. Image Registration 2

12. Image Segmentation 1

13. Image Segmentation 2

14. Credits

Study Objective:

Study materials:

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

2. Goshtasby A. A.: Image Registration: Principles, Tools and Methods, Springer, 2012.

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

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

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

6. Radke R. J.: Computer Vision for Visual Effects, Cambridge University Press, 2012.

7. Svoboda, T., Kybic, J., Hlaváč, V.: Image Processing, Analysis and Machine Vision. The MATLAB companion, Thomson Learning, Toronto, Canada, 2007.

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

Note:

Further information:

https://cw.fel.cvut.cz/wiki/courses/BE4M33DZO

Time-table for winter semester 2022/2023:

	06:00–08:0008:00–10:0010:00–12:0012:00–14:0014:00–16:0016:00–18:0018:00–20:0020:00–22:0022:00–24:00
Mon
Tue	roomKN:E-132 Pánek V. Sýkora D. 18:00–19:30 (lecture parallel1 parallel nr.101) Karlovo nám. Laboratoř PC
Wed	roomKN:E-301 Sýkora D. 09:15–10:45 (lecture parallel1) Karlovo nám. Šrámkova posluchárna K9
Thu
Fri

Time-table for summer semester 2022/2023:

Time-table is not available yet

The course is a part of the following study plans:

• Open Informatics - Computer Vision and Image Processing (compulsory course of the specialization)
• Open Informatics - Bioinformatics (compulsory course of the specialization)