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Course detail

Advanced methods of processing and analysis of images

Course unit code: FEKT-DBM1A
Academic year: 2017/2018
Type of course unit: optional specialized
Level of course unit: Doctoral (3rd cycle)
Year of study: 1
Semester: winter
Number of ECTS credits:
Learning outcomes of the course unit:
Modern advanced methods of image processing and analysis.
Mode of delivery:
90 % face-to-face, 10 % distance learning
Prerequisites:
Backgrounds in digital signal and image processing
Co-requisites:
Not applicable.
Recommended optional programme components:
Not applicable.
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)
Recommended or required reading:
J.Jan: Medical Image Processing, Reconstruction and Restoration. CRC 2006
Planned learning activities and teaching methods:
Teaching methods depend on the type of course unit as specified in the article 7 of BUT Rules for Studies and Examinations. Techning methods include lectures and self study.
Assesment methods and criteria linked to learning outcomes:
Final oral exam
Language of instruction:
English
Work placements:
Not applicable.
Course curriculum:
Advanced image segmentation, fusion of image data, image restoration, image reconstruction from tomographic data.
Aims:
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.
Specification of controlled education, way of implementation and compensation for absences:
none

Type of course unit:

Seminar: 39 hours, optionally
Teacher / Lecturer: prof. Ing. Jiří Jan, CSc.

The study programmes with the given course