PA166 Advanced Methods of Digital Image Processing

Faculty of Informatics
Spring 2009
Extent and Intensity
2/2. 4 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: k (colloquium), z (credit).
Teacher(s)
doc. RNDr. Pavel Matula, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Jiří Sochor, CSc.
Department of Visual Computing – Faculty of Informatics
Contact Person: doc. RNDr. Pavel Matula, Ph.D.
Timetable
Tue 12:00–13:50 B003, Tue 16:00–17:50 B311
Prerequisites
PV131 Digital Image Processing
Knowledge at the level of the lecture PV131 Digital Image Processing is assumed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course is focused on state-of-the-art mathematically well-founded methods of digital image analysis and processing. No prior knowledge of numerical mathematics and functional analysis is required. Necessary mathematical fundamentals will be explained during the course. Students can try the methods at class exercises.
Syllabus
  • Mathematically well-founded image analysis and image processing methods (formulated in terms of Partial Differential Equations - PDE - and variational calculus)
  • Image filtering and image restoration in terms of PDE
  • Diffusion filtering
  • Variational formulation of image segmentation (Mumford-Shah functional)
  • Morphological dilation and erosion as a solution of PDE, shock filtering
  • Active contours and surfaces
  • Level-set methods
  • Optical flow
  • Image registration
Literature
  • OSHER, Stanley and Ronald FEDKIW. Level Set Methods and Dynamic Implicit Surfaces. New York: Springer-Verlag, 2003. ISBN 0-387-95482-1. info
Assessment methods
Written as well as oral exam. Attendance at class exercises mandatory. Study materials in English. Teaching in English or Czech (in the case of all enrolled students prefer Czech).
Language of instruction
English
Further Comments
Study Materials
The course is taught annually.
The course is also listed under the following terms Spring 2005, Spring 2006, Spring 2007, Spring 2008, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024, Spring 2025.
  • Enrolment Statistics (Spring 2009, recent)
  • Permalink: https://is.muni.cz/course/fi/spring2009/PA166