Title:  Data Coding and Compression 

Code:  KKO 

Ac.Year:  2019/2020 

Sem:  Summer 

Curriculums:  

Language of Instruction:  Czech 

Credits:  5 

Completion:  credit+exam (written) 

Type of instruction:  Hour/sem  Lectures  Seminar Exercises  Laboratory Exercises  Computer Exercises  Other 

Hours:  26  0  0  0  26 

 Exams  Tests  Exercises  Laboratories  Other 

Points:  70  0  0  0  30 



Guarantor:  Vašíček Zdeněk, doc. Ing., Ph.D. (DCSY) 

Lecturer:  Drábek Vladimír, doc. Ing., CSc. (DCSY) Vašíček Zdeněk, doc. Ing., Ph.D. (DCSY) 
Instructor:  Drábek Vladimír, doc. Ing., CSc. (DCSY) Šimek Václav, Ing. (DCSY) 

Faculty:  Faculty of Information Technology BUT 

Department:  Department of Computer Systems FIT BUT 


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. 
Description: 

  Introduction to data compression theory. Lossy and lossless data compression, adaptive methods, statistical  Huffman and arithmetic coding, dictionary methods LZ77, 78, transform coding, BurrowsWheeler transform. Hardware support for data compression. 
Knowledge and skills required for the course: 

  Knowledge of functioning of basic computer units. 
Subject specific learning outcomes and competencies: 

  Theoretical background of advanced data processing using compression. 
Generic learning outcomes and competencies: 

  Importance of advanced data compression. 
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, BurrowsWheeler transform.
 Other methods.
 Hardware support for data compression, MXT.

Syllabus  others, projects and individual work of students: 

 Individual project assignment. 
Fundamental literature: 


 Salomon, D.: Data Compression. The Complete Reference, Second Edition, Springer 2000, ISBN 0387950451

Study literature: 


 Lecture notes and study supports in eformat.

Progress assessment: 

  Project designing and presentation. 
Exam prerequisites: 

  Project designing and presentation. Min 10 points. 
