Image and video processing techniques Field of study: Computer Science
Programme code: W4-S2INA19.2021

Module name: Image and video processing techniques
Module code: W4-INA-S2-20-F-TPOiV
Programme code: W4-S2INA19.2021
Semester:
  • summer semester 2022/2023
  • winter semester 2022/2023
  • summer semester 2021/2022
Language of instruction: English
Form of verification: course work
ECTS credits: 4
Description:
The purpose of the module is to introduce the students to modern image and video processing techniques and compression standards.
Prerequisites:
(no information given)
Key reading:
J.C.Russ, F.B. Neal, Image Processing Handbook, CRC Press, 2016 A. Bovik, The Essential Guide to Video Processing, Academic Press, 2009, A. Majumdar, Compressed Sensing for Engineers, CRC Press, 2020 A. Kaehler, G. Bradski, Learning OpenCV3, O'Reilly, 2017
Learning outcome of the module Codes of the learning outcomes of the programme to which the learning outcome of the module is related [level of competence: scale 1-5]
The student knows image and video processing. [M_001]
 K_W01 [1/5] K_W02 [1/5]
The student can implement selected algorithms in image and video processing. [M_002]
 K_U01 [1/5] K_U02 [1/5] K_U03 [1/5] K_U04 [1/5] K_U06 [1/5] K_U09 [1/5]
The student can assess and compare the effectiveness of various algorithms for a problem. [M_003]
 K_U01 [2/5] K_U06 [2/5] K_K01 [1/5]
Type Description Codes of the learning outcomes of the module to which assessment is related
Written exam [W_001]
The test is a means of knowledge verification based on the content presented in the lecture. The exam comprises open-ended theoretical questions.
 M_001 M_003
Classes credit [W_002]
The students present the implementation of the algorithms from the classes and the one individual implementation.
 M_002 M_003
Form of teaching Student's own work Assessment of the learning outcomes
Type Description (including teaching methods) Number of hours Description Number of hours
lecture [Z_001]
Transferring the content of education in verbal (or e-learning) form using audiovisual and other teaching aids.
 15
The students prepare for the exam.
 15 Written exam [W_001]
laboratory classes [Z_002]
The classes prepare the students to individual implementation of selected algorithms.
 30
The students implement selected algorithms in the programming language of choice.
 60 Classes credit [W_002]
Attachments
Module description (PDF)
Information concerning module syllabuses might be changed during studies.
Syllabuses (USOSweb)
Semester Module Language of instruction
(no information given)