Introduction to data compression 1000-2N09KDW
1. Mathematical underpinnings of losless compression.
2. Huffman coding
3. Arithmetic coding.
4. Dictionary methods.
5. PPM algorithm. Burrows-Wheeler transform. Algorithm MTF.
6. Dynamic Markov encoding. Technique CTW.
7. Mathematical underpinnings of lossy compression.
8. Scalar quantization..
9. Vector quantization
10. Differential encoding.
11. Transforms.
12. Standards JPEG and JPEG 2000.
Type of course
Mode
Course coordinators
Learning outcomes
Knowledge
* Knows basic algorithms used in losless and lossy compression. (KW_01).
Abilities
Is able to adapt the compression algorithm to data. (KU_01).
Competents
* Is prepared to understand materials concerning text and image compression. (KK_04).
* Is prepared to understand materials concerning universal compressors. (KK_04).
Assessment criteria
Oral exam in two forms A student may choose the form. Either classsical oral exam or presentation of a topic connected to compression and one question on content of the lecture or exercises.
Bibliography
Khalid Sayood "Kompresja Danych - Wprowadzenie", Readme, 2002.
Adam Drozdek "Wprowadzenie do Kompresji Danych", WNT, 1999.
David Salomon "Data Compression. The Complete Reference", Springer, 2007.
Additional information
Information on level of this course, year of study and semester when the course unit is delivered, types and amount of class hours - can be found in course structure diagrams of apropriate study programmes. This course is related to the following study programmes:
- Bachelor's degree, first cycle programme, Computer Science
- Master's degree, second cycle programme, Computer Science
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: