CTU FEE Moodle
Digital Image
B232 - Summer 23/24
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Digital Image - BE4M33DZO
| Credits | 6 |
| Semesters | Winter |
| Completion | Assessment + Examination |
| Language of teaching | English |
| Extent of teaching | 2P+2C |
Annotation
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.
Study targets
No data.
Course outlines
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
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
Exercises outlines
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
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
Literature
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.
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.
Requirements
It is expected that the student is familiar with calculus, linear algebra, probability and statistics to the depth taught at FEL CVUT.