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Digital processing of visual data - course description

General information
Course name Digital processing of visual data
Course ID 11.3-WE-INFP-DPofVD-Er
Faculty Faculty of Computer Science, Electrical Engineering and Automatics
Field of study Computer Science
Education profile academic
Level of studies Erasmus programme
Beginning semester winter term 2017/2018
Course information
Semester 5
ECTS credits to win 6
Course type optional
Teaching language english
Author of syllabus
  • dr inż. Andrzej Popławski
Classes forms
The class form Hours per semester (full-time) Hours per week (full-time) Hours per semester (part-time) Hours per week (part-time) Form of assignment
Lecture 15 1 - - Exam
Laboratory 30 2 - - Credit with grade
Project 15 1 - - Credit with grade

Aim of the course

To provide basic knowledge about data digitization. To provide understanding of the role of digital data processing techniques in technique and society development. To provide basic skills in modeling of systems for digital data processing, filtering and compression. To provide basic skills in using compression techniques of images and video sequences.

Prerequisites

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Scope

Sampling, digital-analogue conversion. Basic types of digital signals. Digital signal ambiguity.
Digital data acquisition and representation.
Visual data converters. Digital data processing system modeling. Decorrelation, quantization.
Frequency-domain analysis.
Selected discrete transformations: role, principle of operation.
Data compression, applications.
Compression lossy and lossless, the importance of compression.
Measures quality of images and video sequences.
Standards for compression of still images.
Compression standards for video sequences.

Teaching methods

Lecture, laboratory exercises, project.
 

Learning outcomes and methods of theirs verification

Outcome description Outcome symbols Methods of verification The class form

Assignment conditions

Lecture – the passing condition is to obtain a positive mark from the final test and oral presentation .
Laboratory – the passing condition is to obtain positive marks from all laboratory exercises to be planned during the semester.
Project - the passing condition is to obtain a positive mark from the final report
Calculation of the final grade: lecture 40% + laboratory 30% + project 30%

Recommended reading

  1. Lyons R.G.: Wprowadzenie do cyfrowego przetwarzania sygnałów, WKŁ, Warszawa, 2003.
  2. Zieliński T.P.: Cyfrowe przetwarzanie sygnałów. Od teorii do zastosowań, WKŁ, Warszawa, 2007.
  3. Sayood K.: Kompresja danych - wprowadzenie, READ ME, 2002.
  4. Domański M.: Obraz cyfrowy. Reprezentacja, kompresja, podstawy przetwarzania. Standardy JPEG i MPEG, Wydawnictwa Komunikacji i Łączności, Warszawa, 2010.
  5. Domański M.: Zaawansowane techniki kompresji obrazów i sekwencji wizyjnych, WPP, Poznań, 1998.
  6. Skarbek W.: Multimedia. Algorytmy i standardy kompresji, PLJ, 1998.

Further reading

  1. ISO/IEC International Standard 23008-2: 2015 (ed. 2), ITU-T Recommendation H.265: High efficiency video coding, 2015.
  2. ISO/IEC International Standard 13818: Information Technology - Generic Coding of Moving Pictures and Associated Audio Information, 1994.
  3. Ohm J. R.: Multimedia Communication Technology, Springer, 2004.

Notes

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Modified by dr inż. Andrzej Popławski (last modification: 26-05-2017 16:01)