Faculty of Information Technology, BUT

Course details

Data Coding and Compression

KKO Acad. year 2006/2007 Summer semester 5 credits

Lossy and lossless data compression. Basic techniques. Transform coding, Walsh, Hadamard, Burrows-Wheeler transform. Statistical methods. Dictionary methods, LZ77, 78. Run length coding, Huffman and arithmetic coding. Other methods. MXT.


Language of instruction



Credit+Examination (written)

Time span

26 hrs lectures, 26 hrs projects

Assessment points

70 exam, 30 projects




Subject specific learning outcomes and competences

Theoretical background of advanced data processing using compression.

Generic learning outcomes and competences

Importance of advanced coding and information compression.

Learning objectives

To give the students the knowledge the methods for lossy and lossless data compression and their efficiency.

Prerequisite kwnowledge and skills

Knowledge of functioning of basic computer units.

Study literature

  • Lecture notes in e-format.

Fundamental literature

  • Salomon, D.: Data Compression. The Complete Reference, Second Edition, Springer 2000, ISBN 0-387-95045-1

Syllabus of lectures

  1. Lossy and lossless data compression.
  2. Statistical methods.
  3. Dictionary compression methods.
  4. LZ77, 78.
  5. Run length coding.
  6. Huffman coding.
  7. Arithmetic coding.
  8. Other methods.
  9. MXT. 

Syllabus - others, projects and individual work of students

Two project assignments.

Progress assessment

Two project designing.

Exam prerequisites

Two project designing.

Course inclusion in study plans

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