Objective of the course – aims of the course unit:|
Presentation of modern advanced concepts of signal and image processing. The aim is a deep understanding of the methodology, as well as inclusion of student into discussions on the philosophy of the methods.
Objective of the course – learning outcomes and competences:|
Modern advanced methods of image processing and analysis.
Backgrounds in digital signal and image processing
Course contents (annotation):|
- Signal restoration, optimal and adaptive filtering (Jan)
- Spectral analysis of stochastic signals (Kozumplík)
- Neronal networks in signal processing and analysis (Jan)
- Time-frequency analysis (Provazník)
- Formalised restoration of image data (Jan)
- Advanced image segmentation (Jan)
- Generalised morfological transforms of image data (Jan)
- Fusion of image data (Jan)
Teaching methods and criteria:|
Teaching methods depend on the type of course unit as specified in the article 7 of BUT Rules for Studies and Examinations.
Assesment methods and criteria linked to learning outcomes:|
Final oral exam
Advanced image segmentation, fusion of image data, image restoration, image reconstruction from tomographic data.
Specification of controlled education, way of implementation and compensation for absences:|
J.Jan: Digital Signal Filtering, Analysis and Restoration. IEE London, UK, 2000, 407 pp.
J.Jan: Číslicová filtrace, analýza a restaurace signálů. VUTIUM Brno 1997, 2002, 2005, 429 str.
J.Jan: Medical Image Processing, Reconstruction and Restoration - Concepts and Methods. CRC Press - Taylor & Francis Group, USA, 2005, 760 pp.