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Data Compression Algorithms - NSWI072

Title:	Algoritmy komprese dat
Guaranteed by:	Department of Software and Computer Science Education (32-KSVI)
Faculty:	Faculty of Mathematics and Physics
Actual:	from 2022
Semester:	winter
E-Credits:	3
Hours per week, examination:	winter s.:2/0, Ex [HT]
Capacity:	unlimited
Min. number of students:	unlimited
4EU+:	no
Virtual mobility / capacity:	no
State of the course:	taught
Language:	Czech, English
Teaching methods:	full-time
Teaching methods:	full-time
Additional information:	http://ksvi.mff.cuni.cz/~dvorak/vyuka/NSWI072/

Guarantor:	doc. RNDr. Tomáš Dvořák, CSc.
Class:	Informatika Mgr. - volitelný
Classification:	Informatics > Software Engineering, Theoretical Computer Science

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Annotation -

Last update: DVORAK (19.05.2004)

This course surveys techniques used for both lossless and lossy data compression.

Course completion requirements -

Last update: doc. RNDr. Tomáš Dvořák, CSc. (13.10.2017)

The course is concluded with an oral exam. Questions posed in the exam explore the topics included in the syllabus to the extent that these topics are covered in lectures.

Literature -

Last update: doc. RNDr. Tomáš Dvořák, CSc. (24.09.2023)

G. A. Harris, P. D. Johnson, D. R. Hankerson, Introduction to Information Theory and Data Compression, 2nd ed., Chapman & Hall/CRC, New York, 2019.

A. Moffat, A. Turpin, Compression and Coding Algorithms, Kluwer Academic Publishers, Boston, 2002.

D. Salomon, G. Motta, D. Bryant, Handbook of Data Compression, 5th edition, Springer-Verlag, 2010.

K. Sayood, Introduction to Data Compression, 5th ed., Morgan Kauffmann Publishers, San Francisco, 2017.

Syllabus -

Last update: doc. RNDr. Tomáš Dvořák, CSc. (01.05.2015)

Lossless data compression

• statistical methods: Huffman coding, arithmetic coding, adaptive algorithms, finite context methods

• information theory and theoretical limits of lossless compression

• dictionary methods of classes LZ77 and LZ78, application gzip, GIF and PNG standards

• Burrows-Wheeler transform, application bzip2

Lossy data compression

• scalar quiantization

• differential coding, methods DPCM and ADPCM

• transform conding, JPEG standard

• subband coding, MP3 standard

• video compression, MPEG standard

Entry requirements -

Last update: T_KSVI (04.05.2015)

Knowledge at the level of the subject Probability and Statistics.