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Digital Image Processing

Summary

The following topics are covered: Mathematical preliminaries for digital image processing, Fourier, cosine, and wavelet transforms and their applications, JPEG, MPEG, and audio compression, point and geometric operations, sampling and reconstructing images, filtering, stochastic approach to digital image processing, morphological image processing, image enhancement using deep learning. The course includes the computer labs in which the computer programs are realised corresponding to the mentioned topics.

Graduates of this course will be able to:
- Describe and explain the theoretical foundations of operations on image signal space, including Fourier, cosine, and wavelet transforms, convolution, and filtering.
- Describe and explain the principles of image and video compression.
- Apply theoretical knowledge in the creation of algorithms that solve the problem of various image modifications.
- Evaluate, discuss, select, and compare the quality and effectiveness of various algorithms for working with images.

Literature

1. Gonzalez, R., C., Woods, R., E.: Digital Image Processing, 4th Edition, Pearson, ISBN-13: 9780134734804 , 9780133356724, 2018.
2. Shih, Frank, Y.: AI Deep Learning in Image Processing, CRC Press, ISBN 9781032755304 , 2025.

Advised literature

1. Burger, W., Burge, M., J.: Principles of Digital Image Processing: Fundamental Techniques, Springer, ISBN-10: 1848001908 , ISBN-13: 978-1848001909 , 2011
2. Brahmbhatt, S.: Practical OpenCV (Technology in Action), Apress, ISBN-10: 1430260793 , ISBN-13: 978-1430260790 , 2013
3. Petrou, M., Petrou, C.: Image Processing: The Fundamentals, 2nd Edition, Wiley, ISBN 978-1-119-99439-8 , 2011


Language of instruction čeština, angličtina
Code 460-4079
Abbreviation DZO
Course title Digital Image Processing
Coordinating department Department of Computer Science
Course coordinator doc. Dr. Ing. Eduard Sojka