Digital 2D biosignal processing

The course is not on the list Without time-table
Code Completion Credits Range Language
17DBZ2D ZK 5 2P Czech
Garant předmětu:
Department of Biomedical Informatics

The basic topics of the subject are techniques of 2D bio-signal processing, discrete 2D transforms, linear filtering, image reconstruction from projection, 3D reconstruction, 2D signal analysis (distortion and noise identification, wavelet decomposition, edge detection, segmentation, texture analysis), lossless and lossy compression, quality classification, 2D bio-signal processing in medicine (US, mammography, microscopic imaging, etc.)


Basic knowledge of image processing is an advantage. (Pass the subject „Image data processing“)

Syllabus of lectures:

1) 2D discrete transformations, DFT, Hadamard 2) Diskret cosine transformation 3) Wavelet decomposition and its utilization in 2D bio-signal analysis 4) Basic geometrical transformations 5) Mathematical model of the camera 6) . Morphological image analysis, erosion, dilatation, morphological opening and closing, morphological filtering and its properties 7) Shape characteristics of objects in the image 8) Segmentation and thresholding (1). 9) Segmentation and thresholding (2). 10) FT, Cosine, Sine, Hadamard, Haar, Karhunen-Loeve transformations. 11) Image restoration techniques (1). 12) Image restoration techniques (2). 13) Inverse filtering 14) Wiener filtering.

Syllabus of tutorials:

The subject has only lectures

Study Objective:

The goal of the subject is provide knowledge of theoretically demanding methods of 2D bio-signal processing and their application or modification for particular purposes.

Study materials:


[1] Rafael C.Gonzales, Paul Wintz: Digital Image Processing, 2002.

[2] Sonka, Hlavac, Boyle: Image Processing, Analysis and Machine Vision, Thomson, 2008, ISBN: 0-495-08252-X


[3] Al Bovik: Handbook of Image & Video Processing. Academic Press, 2000.

[4] Gonzales, C.R., Woods, E.R., Eddins, L.S.: Digital Image Processing Using MATLAB. Prentice Hall, 2004.

[5] Sonka, M., Fitzpatrick, J.M.: Handbook of Medical Imaging, Volume 2. Medical Image Processing and Analysis, SPIE Press, 2000.

[6] Davies, E.R.: Machina Vision, Theory, Algorithms, Practicalities, 3rd edition, Elsevier Inc. 2005.

[7] Fontoura Costa, L., Marcondes Cesar, R.Jr.: Shape Analysis and Classification Tudory and Praktice, CRC Press, 2000.

[8] Soille, P.: Morphological Image Analysis, Principles and Applications, 2nd edition, Springer-Verlag, 2003.

Further information:
No time-table has been prepared for this course
The course is a part of the following study plans:
Data valid to 2024-06-16
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