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At the beginning the subject describes a principle of imaging systems using transfer functions. Image sensor can be seen also as an imaging system and this subject includes description of various types of image sensors. A signal generated by sensor could be processed by several statistical methods. Interest of this subject lies in the area of wavelet transform utilization and multidimensional signal modeling. Hence, there will be mentioned several denoising methods based on thresholding of wavelet coefficients and image compression algorithms will be chosen. Above mentioned algorithms and principles will be practised on real image data in MATLAB.
Last update: TAJ445 (14.12.2013)
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Students will be able to:
Describe electro-optical system, image sensors (CCD, CMOS) Fundamentals of continuous and discrete wavelet transform, image reconstruction methods (Inverse filter, Wiener filter, CLS filtr) De-noising methods, image and signal modeling, noise modeling, Bayesian estimators, image compression methods Measure modulation transfer function, realize system noise analysis Detection of image component, basic image recognition, image quality measurement Last update: Švihlík Jan (31.07.2013)
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R: Gonzalez C., Woods R., Digital Image Processing. Third edition. New Jersey, 2007, 013168728X R: Mallat S., A Wavelet Tour of Signal Processing, Academic Press, 1999, 9780123743701 R: Newland D., An Introduction to Random Vibrations, Spectral and Wavelet Analysis, Dover Publ., 2005, 0486442748 R: Woods J., Multidimensional Signal, Image and Video Processing and Coding, Elsevier, 2006, 0120885166 R: Bogges A., Narcowich F.J., First Course in Wavelets with Fourier Analysis, Prentice Hall, 2001, 0130228095 R: Mandal M.K., Multimedia Signals and Systems, Springer, 2003, 9781402072703 Last update: Švihlík Jan (31.07.2013)
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1 Introduction to signal processing 2 Transfer functions of imaging systems (PSF, OTF, MTF) 3 Image reconstruction methods (Inverse filter, Wiener filter, CLS filtr) 4 Continuous and discrete wavelet transform, generation of wavelet functions, recurrent formula 5 Image decomposition and reconstruction, pyramidal structure 6 De-noising methods (filtration, wavelet coefficients thresholding) 7 Image and signal modeling, noise modeling, Bayesian estimators 8 Image compression methods 9 Principles of complex wavelet transform, basic properties 10 Multidimensional signal analysis 11 Image quality measurement 12 Image component detection, principles of recognition, video processing 13 Image acquisition, algorithmic tools (Image Acquisition Tbx) 14 Speech Processing Last update: TAJ445 (30.09.2013)
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http://www.signalprocessingsociety.org/publications/periodicals/image-processing/ http://spie.org/x868.xml http://spie.org/x867.xml Last update: Švihlík Jan (31.07.2013)
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Mathematics I, Signal processing Last update: Švihlík Jan (31.07.2013)
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| Teaching methods | ||||
| Activity | Credits | Hours | ||
| Účast v laboratořích (na exkurzi nebo praxi) | 0.5 | 14 | ||
| Účast na přednáškách | 1 | 28 | ||
| Práce na individuálním projektu | 0.5 | 14 | ||
| Příprava na zkoušku a její absolvování | 0.6 | 16 | ||
| 3 / 3 | 72 / 84 | |||
| Coursework assessment | |
| Form | Significance |
| Regular attendance | 40 |
| Report from individual projects | 20 |
| Continuous assessment of study performance and course -credit tests | 40 |