PA171 Digital Image Filtering

Faculty of Informatics
Spring 2010
Extent and Intensity
2/1. 3 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
doc. RNDr. David Svoboda, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Jiří Sochor, CSc.
Department of Visual Computing – Faculty of Informatics
Contact Person: doc. RNDr. David Svoboda, Ph.D.
Timetable
Mon 12:00–13:50 C416, Mon 16:00–16:50 B311
Prerequisites
PV131 Digital Image Processing
Knowledge of written English and calculus is required.
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 aim of this lecture is to introduce all the basic image transforms used in digital image processing. It covers the operations changing the image content or transforming the original data into different representation. At the end of this course, students should be able to: understand the basic principles of the image transforms; know the selected transforms; implement the selected transforms; apply the selected transforms.
Syllabus
  • Thresholding (various methods of histogram analysis)
  • Linear and nonlinear filtering
  • Edge detection (Canny, Deriche, etc.)
  • Discrete transforms (Fourier, FFT, Hough, Hadamard, Discrete Cosine, Wavelets, Radon, etc.)
  • Deconvolution
  • Image compression, loss/lossless compression, colour indexing, entropy, JPEG, MPEG, the use in image formats
  • Texture filtering
Literature
  • GONZALEZ, Rafael C. and Richard E. WOODS. Digital image processing [2nd ed.]. 2nd ed. Upper Saddle River: Prentice Hall, 2002, xx, 793 s. ISBN 0-201-18075-8. info
  • BRACEWELL, Ronald N. The Fourier transform and its applications. 3rd ed. Boston: McGraw Hill, 2000, xx, 616. ISBN 0073039381. URL info
  • PRATT, William K. Digital image processing. 3rd ed. New York: John Wiley & Sons, 2001, xix, 735. ISBN 0471374075. info
Teaching methods
obtaining knowledge during lectures, obtaining skills by working with PC
Assessment methods
Lectures in Czech (optionally in English), study materials in English. Exercises in computer labs. Final exam in written and oral form.
Language of instruction
English
Further Comments
Study Materials
The course is taught annually.
Teacher's information
http://cbia.fi.muni.cz/teaching-activities.html
The course is also listed under the following terms Spring 2007, Spring 2008, Spring 2009, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Autumn 2019, Autumn 2021, Autumn 2022, Autumn 2023.
  • Enrolment Statistics (Spring 2010, recent)
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