Course

Information Theory Foundation: Entropy, its properties, conditional entropy, mutual information, Types of codes, Krafts McMillan Inequality theorem, Source coding theorem.Introduction to Compression Techniques: Introduction, Types of compression – Lossy, lossless. Performance measures, Modeling, Coding. Text Compression: Huffmann –

static and dynamic, application in text compression, Shannon Fano Elias Coding, Arithmetic coding, Dictionary based coding-static, adaptive, UNIX compress.

Scalar and Vector Quantization: Scalar Quantization – Introduction, Uniform and Adaptive quantization. Vector Quantization- Introduction, Advantages, LBG, Tree vector quantization, Trellis coded quantization Audio Compression: Distortion criteria- Auditory perception, PCM, DPCM, ADPCM, Predictive coding- basic algorithm, Basic sub-band coding, MPEG Audio Coding

Image Compression: Distortion criteria- The human visual system, Transform coding- DCT, JPEG, JBIG II, GIF, Wavelet based compression- wavelets, the scaling function, Haar Transforms, JPEG-2000. Video Compression: Motion Estimation and Compensation- Full search and Fast search algorithms, H.261, MPEG-1, MPEG-2, MPEG-4, MPEG -7.

1. Sayood and Khalid, “Introduction to Data Compression”, Third Edition, Morgan Kaufmann, 2006.
2. Richardson I E G, “Video Codec Design: Developing Image and Video Compression Techniques”,JohnWiley&Sons,2002.
3. Salomon D, “Data Compression: The Complete Reference”, Fourth Edition, Springer,2007
4. Gersho A and Kluwer R M G, “Vector Quantization and Signal Compression”, Academic Press,1992.