Course details

Data Coding and Compression

KKO Acad. year 2017/2018 Summer semester 5 credits

Current academic year

Introduction to data compression theory. Lossy and lossless data compression, adaptive methods, statistical - Huffman and arithmetic coding, dictionary methods LZ77, 78, transform coding, Burrows-Wheeler transform. Hardware support for data compression.

Guarantor

Drábek Vladimír, doc. Ing., CSc.

Language of instruction

Czech

Completion

Credit+Examination (written)

Time span

  • 26 hrs lectures
  • 26 hrs projects

Assessment points

  • 70 pts final exam (written part)
  • 30 pts projects

Department

Department of Computer Systems (UPSY)

Subject specific learning outcomes and competences

Theoretical background of advanced data processing using compression.

Importance of advanced data compression.

Learning objectives

To give the students the knowledge of basic compression techniques, the methods for lossy and lossless data compression their efficiency, statistical and dictionary methods, hardware support for data compression.

Prerequisite knowledge and skills

Knowledge of functioning of basic computer units.

Study literature

  • Přednáškové materiály a studijní opory v elektronické formě.

Fundamental literature

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

Syllabus of lectures

  • Introduction to compression theory.
  • Basic compression methods.
  • Statistical and dictionary methods.
  • Huffman coding.
  • Adaptive Huffman coding.
  • Arithmetic coding. Text compression.
  • Lossy and lossless data compression.
  • Dictionary methods, LZ77, 78.
  • Variants of LZW.
  • Transform coding, Burrows-Wheeler transform.
  • Other methods.
  • Hardware support for data compression, MXT.

Progress assessment

Project designing and presentation.

Controlled instruction

Project designing and presentation.

Course inclusion in study plans

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