FI:PA171 Digital Image Filtering - Course Information
PA171 Digital Image Filtering
Faculty of InformaticsSpring 2009
- 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 8:00–9:50 B411, Mon 10:00–10:50 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
- Applied Informatics (programme FI, N-AP)
- Information Technology Security (programme FI, N-IN)
- Bioinformatics (programme FI, N-AP)
- Information Systems (programme FI, N-IN)
- Parallel and Distributed Systems (programme FI, N-IN)
- Computer Graphics (programme FI, N-IN)
- Computer Networks and Communication (programme FI, N-IN)
- Computer Systems (programme FI, N-IN)
- Embedded Systems (eng.) (programme FI, N-IN)
- Theoretical Informatics (programme FI, N-IN)
- Upper Secondary School Teacher Training in Informatics (programme FI, N-SS) (2)
- Artificial Intelligence and Natural Language Processing (programme FI, N-IN)
- Image Processing (programme FI, N-AP)
- 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
- 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
- Enrolment Statistics (Spring 2009, recent)
- Permalink: https://is.muni.cz/course/fi/spring2009/PA171