Introduction: Compression Techniques, Modeling and Coding
Mathematical Preliminaries for Lossless Compression Overview, Introduction to Information Theory, Models, Coding
Huffman Coding, Overview, The Huffman Coding Algorithm, Minimum Variance Huffman Codes, Adaptive Huffman Coding, Application of Huffman Coding
Arithmetic Coding, Overview, Introduction, Coding a Sequence, Generating a Binary Code, Comparison of Huffman and Arithmetic Coding, Applications
Dictionary Techniques Overview, Introduction, Static Dictionary, Adaptive Dictionary, Applications
Mathematical Preliminaries for Lossy Coding Overview, Introduction, Distortion Criteria, Models
Scalar Quantization: Overview, Introduction, The Quantization Problem, Uniform Quantizer, Adaptive Quantization, Non-uniform Quantization
Vector Quantization: Overview, Introduction, Advantages of Vector Quantization over Scalar Quantization
Transform Coding, Overview, Introduction, The Transform, Transforms of Interest, Discrete Cosine Transform, Quantization and Coding of Transform Coefficients, Application to Image Compression – JPEG, Application to Audio Compression,
Wavelet-Based Compression, Image Compression, Embedded Zero-tree Coder, Set Partitioning in Hierarchical Trees, JPEG 2000
Self Learning Component
To be decided by course coordinator at the beginning of semester, which will be a blend of one or more of the e-Learning Resources, Video Lectures, Online courses, tools, research material, web links etc. along with the related assessment component(s).
Laboratory Work
Above concepts are to be implemented and at least 5 experiments are to be carried out.
References
- Introduction to Data Compression –By Khalid Sayood Morgan Kaufmann, Harcourt India Publication
Data Compression 