Title:

Data Coding and Compression

Code:KKO
Ac.Year:2012/2013
Sem:Summer
Curriculums:
ProgrammeField/
Specialization
YearDuty
IT-MSC-2MBI-Compulsory-Elective - group S
IT-MSC-2MBS1stCompulsory
IT-MSC-2MGM-Compulsory-Elective - group G
IT-MSC-2MIN-Elective
IT-MSC-2MIS-Elective
IT-MSC-2MMI-Elective
IT-MSC-2MMM-Compulsory-Elective - group B
IT-MSC-2MPV1stCompulsory
IT-MSC-2MSK1stCompulsory-Elective - group C
Language of Instruction:Czech
Credits:5
Completion:credit+exam (written)
Type of
instruction:
Hour/semLecturesSeminar
Exercises
Laboratory
Exercises
Computer
Exercises
Other
Hours:2600026
 ExamsTestsExercisesLaboratoriesOther
Points:7000030
Guarantor:Drábek Vladimír, doc. Ing., CSc. (DCSY)
Lecturer:Drábek Vladimír, doc. Ing., CSc. (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, context methods and 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, context methods, transform coding, Burrows-Wheeler 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.
  • Context methods.
  • Transform coding, Burrows-Wheeler 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 0-387-95045-1
Study literature:
 
  • Lecture notes and study supports in e-format.
Progress assessment:
  Project designing and presentation.
Exam prerequisites:
  Project designing and presentation.
 

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