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Main menu for Browse IS/STAG
Course info
KMI / KOM
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Course description
Department/Unit / Abbreviation
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KMI
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KOM
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Academic Year
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2024/2025
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Academic Year
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2024/2025
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Title
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Data Compression
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Form of course completion
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Exam
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Form of course completion
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Exam
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Accredited / Credits
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Yes,
5
Cred.
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Type of completion
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Combined
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Type of completion
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Combined
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Time requirements
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Lecture
2
[Hours/Week]
Tutorial
2
[Hours/Week]
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Course credit prior to examination
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Yes
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Course credit prior to examination
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Yes
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Automatic acceptance of credit before examination
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No
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Included in study average
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YES
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Language of instruction
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Czech, English
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Occ/max
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Automatic acceptance of credit before examination
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No
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Summer semester
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0 / -
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0 / -
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0 / 10
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Included in study average
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YES
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Winter semester
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0 / -
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0 / -
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0 / -
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Repeated registration
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NO
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Repeated registration
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NO
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Timetable
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Yes
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Semester taught
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Summer semester
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Semester taught
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Summer semester
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Minimum (B + C) students
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not determined
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Optional course |
Yes
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Optional course
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Yes
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Language of instruction
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Czech, English
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Internship duration
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0
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No. of hours of on-premise lessons |
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Evaluation scale |
A|B|C|D|E|F |
Periodicity |
každý rok
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Evaluation scale for credit before examination |
S|N |
Periodicita upřesnění |
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Fundamental theoretical course |
Yes
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Fundamental course |
Yes
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Fundamental theoretical course |
Yes
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Evaluation scale |
A|B|C|D|E|F |
Evaluation scale for credit before examination |
S|N |
Substituted course
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None
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Preclusive courses
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N/A
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Prerequisite courses
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N/A
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Informally recommended courses
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N/A
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Courses depending on this Course
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N/A
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Histogram of students' grades over the years:
Graphic PNG
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XLS
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Course objectives:
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In the course basic as well as modern methods of lossless data
compression and lossy compression of multimedia data are introduced.
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Requirements on student
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-
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Content
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1. Intro: Required notions from information theory and coding
(entropy), taxonomy of compr
ession methods, basic notions and data models, simple methods (RLE,
MTF, Delta).
2. Statistical methods: Shannon-Fano, Huffman, arithmetic and
Q-coding, principles and implementation.
3. Context methods: Prediction by partial matching (PPM) and context
mixing (PAQ) methods.
4. Dictionary methods: LZ77 class and LZSS and Deflate methods, LZ78
class and LZW method, principles and implementation.
5. Block sorting method: Burrows-Wheeler transformation (BWT),
principle and implementation.
6. Other lossless methods: Grammar-based, statistical and other LZ
methods, LZMA.
7. Lossy compression methods: Multimedia data representation and color
spaces (models), survey of methods, quantization, DPCM, transform
(DCT, DFT) and subband (wavelet) coding.
8. Image compression: GIF, PNG, TIFF, JPEG, wavelet, fractal, WebP.
9. Video compression: M-JPEG, DV, motion prediction, MPEG/H.26*, VP*,
Theora, containers (MPEG, Ogg, WebM, AVI, Flash).
10. Audio compression: Prediction, psychoacoustics, syntetization,
MPEG (MP3, AAC), Dolby (AC-3), Vorbis, Speex, FLAC, MIDI.
11. Graphics compression: Representation (polygonal meshes),
topological surgery, progresive meshes, wavelet compression, MPEG.
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Activities
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Fields of study
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Guarantors and lecturers
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Guarantors:
doc. Mgr. Jan Outrata, Ph.D. (100%),
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Lecturer:
doc. Mgr. Jan Outrata, Ph.D. (100%),
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Tutorial lecturer:
doc. Mgr. Jan Outrata, Ph.D. (100%),
Mgr. Markéta Trnečková, Ph.D. (100%),
Mgr. Jan Tříska, Ph.D. (100%),
Mgr. Tomáš Urbanec (100%),
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Literature
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Basic:
Salomon D., Motta G. (2010). Handbook of Data Compression, 5th edition.. Springer.
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Basic:
Khalid Sayood Ph.D. (2017). Introduction to Data Compression 5th Edition. Morgan Kaufmann.
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Basic:
Colt McAnlis, Aleks Haecky. (2016). Understanding Compression: Data Compression for Modern Developers. O'Reilly Media.
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Recommended:
Salomon D. (2006). Data Compression: The complete Reference, 4th edition. Springer.
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Recommended:
Hankerson D. C., Harris G. A., Johnson P. D. (2003). Introduction to. Chapman and Hall/CRC.
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Recommended:
Sayood K. (2003). Lossless compression handbook. Academic Press.
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On-line library catalogues
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Prerequisites - other information about course preconditions |
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Competences acquired |
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Teaching methods |
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Assessment methods |
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