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Course Detail

Course Name Data Compression
Course Code 15CSE342
Program B. Tech. in Computer Science and Engineering
Year Taught 2019


Unit 1

Information theoretic foundations: Lossless and lossy compression, Modelling and coding Entropy, conditional entropy, information, channels, Data models: static and adaptive, coding: Fano, Huffman, Golomb, Rice, Tunstall Arithmetic coding: Encoding, Decoding, Adaptation, Dictionary techniques: Static techniques.

Unit 2

Adaptive coding: the LZ family. Context modelling: PPM, Burrows-Wheeler, Moveto front, DMC. Lossless image compression: Multiresolution, CCITT Group 3 and 4, JBIG, JBIG2. Lossy coding preliminaries: Distortion, Rate distortion, linear system models. Scalar and vector quantization: Uniform and non-uniform quantizers, Adaptive quantization, Lloyd-Max quantizer.

Unit 3

Differential encoding: Predictive DPCM, Adaptive DPCM. Transform coding: Bases, inner products, orthogonality and orthonormality, Karhunen-Loéve transform, DCT, Walsh-Hadamard transform, JPEG

Text Books

  1. David Salomon and Giovanni Motta, “Handbook of Data Compression”, Fifth Edition, Springer, 2010.


  • David Salomon, “Data compression: the complete reference”, Third Edition, New York: Springer, 2004.
  • Sayood, Khalid, “Introduction to Data Compression”, Third Edition, Morgan Kaufmann, 2006.

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