'Data Compression' is a course offered in the B. Tech. in Computer Science and Engineering program at School of Engineering, Amrita Vishwa Vidyapeetham.
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
- 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.
