Image Compression (3 cu) 173347

Course description

The course introduces to algorithms in image compression. It covers coding methods such as Huffman, Golomb and arithmetic coding; statistical, predictive and context modeling methods; DCT and wavelet transforms, vector quantization, and fractal-based compression. The existing image compression standards are also considered including JBIG, JBIG-2, JPEG, JPEG-LS, JPEG-2000 and MPEG but the emphasizes is on the compression methods in these standards rather than the specifications details.

Lectures

Teacher: Pasi Fränti
Schedule: 40 h, starting from 9.9.
Monday 12-14 (D106)
Tuesday 12-14 (D106)
Lecture material

Exercises

Teacher: Pavel Kopylov
Schedule: 20 h, starting from 16.9.
Monday 14-16 (B180)
Exercises

Preliminary knowledge

Data structures and algorithms is required. Other recommended courses related to the topic are Introduction to Signals, Image Analysis, and Pattern Recognition.

Exams

1. intermediate exam: 1.11. at 14.00, Room M3 (Metria building)
2. intermediate exam: 3.12. at 12.00, Room 106
General exam dates

Recommended literature

P. Fränti, "Image Compression", Lecture Notes, 2002. (Word document)
M. Nelson, Data Compression: The Complete Reference (2nd edition). Springer-Verlag, New York, 2000.
M. Rabbani, P.W. Jones, Digital Image Compression Techniques. Bellingham, USA, SPIE Optical Engineering Press, 1991.
I.H. Witten, A. Moffat, and T.C. Bell, Managing Gigabytes: Compressing and Indexing Documents and Images. Van Nostrand Reinhold, 1994.
W.B. Pennebaker, J.L. Mitchell, JPEG Still Image Data Compression Standard. Van Nostrand Reinhold, 1993.
D.S. Taubman, M.W. Marcellin, JPEG-2000: Image Compression Fundamentals, Standards and Practice. Kluwer, 2002

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