Welcome, Guest . Login . Türkçe
Where Am I: Ninova / Courses / Institute of Science and Technology / BLG 538E / Course Informations

Course Information

Course Name
Turkish Veri Sıkıştırma
English Data Compression
Course Code
BLG 538E Credit Lecture
Semester 1
3 3 - -
Course Language English
Course Coordinator Uluğ Bayazıt
Course Objectives Gain an understanding of the data compression system flow. Acquire the information theoretical foundation for data compression. Learn the basic time and transform domain methods for lossless and lossy compression. Comprehend design techniques such as mean square error minimizing predictor design, bit allocation to transform coefficients, codebook pruning and growing, that aim to optimize the rate-distortion performance. Familiarize with the applications of data compression methods to one, two or three dimensional data sequences with various statistical properties.
Course Description Introduction to data compression and source coding. Block coding. Huffman and arithmetic coding. Dictionary based coding. Scalar quantization. Vector quantization. . Predictive coding. Transform and subband coding. In class presentations of wavelet based image, audio, video and computer graphics compression methods.
Course Outcomes 1.Basic information theory concepts
2. Lossless source coding tools
3. Quantization methods
4. Predictive coding tools
5. Transform domain coding methods
6. Familiarize with applications and standards related to video, image, audio, speech, text, computer graphics coding
Required Facilities
Textbook Introduction to Data Compression
Khalid Sayood, 3rd Edition
Morgan Kaufmann, 2006
Other References 1. Allen Gersho, Robert M. Gray, Vector Quantization and Signal Compression, Kluwer Academic Publishers, 1992.
2. Nuggehally S. Jayant, Peter Noll, Digital Coding of Waveforms, Prentice Hall, 1990.
3. David Salomon, Data Compression: The Complete Reference, 3rd Edition, Springer, 2004.
4. Toby Berger, Rate Distortion Theory, A Mathematical Basis for Data Compression, Prentice Hall, 1971.
Courses . Help . About
Ninova is an ITU Office of Information Technologies Product. © 2021