Digital Image Processing

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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 interactive editing of digital images and video. It mainly deals with practical algorithms that are both easy to implement and have an interesting theoretical basis. Visually attractive applications provide better understanding of basic theoretical background that is also valuable outside the domain of digital image processing. This course will introduce algorithms solving the following practical applications: edge-aware editing, tone mapping, HDR compression, de-blurring in frequency domain, abstraction, hybrid images, gradient domain editing, seamless image stitching and cloning, digital photo-montage, color-to-gray conversion, context enhancement, interactive as-rigid-as-possible image deformation, free-form image registration, texture synthesis, interactive segmentation, colorization, painting, adding depth, alpha matting.


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. Monadic Operations

2. Fourier Transform

3. Convolution

4. Non-linear Filtering

5. Image Editing

6. Image Segmentation

Study Objective:
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:
Time-table for winter semester 2022/2023:
Time-table is not available yet
Time-table for summer semester 2022/2023:
Time-table is not available yet
The course is a part of the following study plans:
Data valid to 2022-12-09
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