Digital Image Processing

Course guarantor:

Lecturer:

Tutor:

Supervisor:

Department of Software Engineering

Synopsis:

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.

Requirements:

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.

Note:

Further information:

https://moodle-vyuka.cvut.cz/course/view.php?id=2233

No time-table has been prepared for this course

The course is a part of the following study plans:

• Master branch Knowledge Engineering, in Czech, 2016-2017 (elective course)
• Master branch Computer Security, in Czech, 2016-2019 (elective course)
• Master branch Computer Systems and Networks, in Czech, 2016-2019 (elective course)
• Master branch Design and Programming of Embedded Systems, in Czech, 2016-2019 (elective course)
• Master branch Web and Software Engineering, spec. Info. Systems and Management, in Czech, 2016-2019 (elective course)
• Master branch Web and Software Engineering, spec. Software Engineering, in Czech, 2016-2019 (elective course)
• Master branch Web and Software Engineering, spec. Web Engineering, in Czech, 2016-2019 (elective course)
• Master program Informatics, unspecified branch, in Czech, version 2016-2019 (elective course)
• Master branch System Programming, spec. System Programming, in Czech, 2016-2019 (elective course)
• Master branch System Programming, spec. Computer Science, in Czech, 2016-2017 (elective course)
• Master specialization Computer Science, in Czech, 2018-2019 (elective course)
• Master branch Knowledge Engineering, in Czech, 2018-2019 (elective course)