FI:PA171 Digital Image Filtering - Course Information

PA171 Digital Image Filtering

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

Wed 10:00–11:50 C416, Wed 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

• Applied Informatics (programme FI, N-AP)
• Information Technology Security (programme FI, N-IN)
• Bioinformatics (programme FI, N-AP)
• Information Systems (programme FI, N-IN)
• Informatics (programme FI, M-IN)
• Informatics (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)
• Embedded Systems (programme FI, N-IN)
• Service Science, Management and Engineering (eng.) (programme FI, N-AP)
• Service Science, Management and Engineering (programme FI, N-AP)
• Theoretical Informatics (programme FI, N-IN)
• Upper Secondary School Teacher Training in Informatics (programme FI, M-SS)
• Upper Secondary School Teacher Training in Informatics (programme FI, M-TV)
• 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

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

• Enrolment Statistics (Spring 2011, recent)
  
• Permalink: https://is.muni.cz/course/fi/spring2011/PA171