Course Contents 
In today's communication, storage and DSP technology, signals of various kinds (speech, audio, image, video, graphics) are usually represented in digital format. Although representation formats bring many advantages, an important drawback is the huge transmission or storage capacity required for digitized analog signals. For that reason, it is important to find digital representation formats that are more efficient, either via data compression or data reduction techniques. This course concentrates on the efficient and compact representation of audiovisual information in a digital format. The objective is to understand and being able to apply the concepts of digital signal (audio, speech, images, video) compression.
To this end a number of relevant compression and reduction techniques are described. Applications are found in telecommunications, multimedia, digital TV, HDTV, as well as in signal and image processing.

Study Goals 
1. Properties of audiovisual signals PCM, subsampling, digital representations, correlation in multimedia signals, redundancy, irrelevancy, quality.  Explain factors that make compression of multimedia signals possible  Apply PCM and subsampling, explain artefacts  Give definition (P)SNR quality, explain relation between SNR and bit rate  Relate visual compression artefacts to structure of compression scheme using VcDemo
2. Measures of information and VLC coding Shannon’s information measure, entropy, lossless source coding theorem, variable length coding (VLC), universal coding  Give definition of (differential) entropy, list properties of entropy measure  Calculate entropy of arbitrary source and for quantizer representation levels. Give entropy of a Gaussian source  Design Huffman code  Explain principle of runlength coding and 2D VLC coding  Explain principle of LZ coding, arithmetic coding
3. Quantization Scalar quantization, uniform and nonuniform quantization, combination with VLC encoding, vector quantization (VQ)  Design (non)uniform quantizer by minimizing variance of quantization error  Compare quantizers based on RD performance  Give RD performance of quantization of Gaussian sources  Explain problem of bit allocation and describe solution principle  Explain principle of VQ, draw block diagram, and explain its components
4. (Differential) Pulse Coded Modulation PCM coding block diagram, Differential PCM coding block diagram, prediction gain, linear predictor, optimal prediction coefficients, PCM and DPCM of images  Sketch and explain block diagrams of PCM and DPCM  Define and calculate optimal prediction coefficients and prediction gain  Explain role of correlation in DPCM encoding signals
5. Transform Coding Principle and block diagram of transform coding, decorrelation of signals using transforms, decomposition on basis functions, choice of transform/basis functions, KLT, WHT, DCT, extension to images, bit allocation, quantization and VLC coding of DCT coefficients, JPEG  Describe and validate properties of orthogonal transforms  Relate orthogonal transforms, basis functions/images, and transform coefficients  Give properties of KLT, WHT, and DCT transform on 1D and 2D signals  Motivate PCM/DPCM coding of DCT coefficients  Relate variance of DCT coefficients to selected quantizer  Explain role of DCT/JPEG quantization (normalization) matrix  Explain structure of JPEG encoder and decoder, describe the coding of an individual DCT block using JPEG
6. Subband/Wavelet Coding Principle and block diagram of subband/wavelet coding, basic 2band decompositions system, transfer function of 2band decomposition for ideal and nonideal filters, filter bank using QMF filters, multiple band decomposition, extension to images, bit allocation, quantization and VLC coding of subband coefficients, application to audio compression (mp3) and images (JPEG2000)  Draw block diagram of subband coding scheme and describe the role of the different components  Describe structure of the basic 2band filter bank, describe the components mathematically using linear systems theory, and give overall transfer function  Explain “perfect reconstruction” property  Determine how to obtain multiple band decompositions  Explain extension to subband coding of images  Motivate PCM/DPCM coding of subband coefficients  Relate variance of subband coefficients to selected quantizer
7. Motioncompensated DCTbased Video Coding MCDCT block diagram, motion estimation and compensation, MPEG  Motivate the structure of the MCDCT scheme  Explain role of motion estimation in relation to temporal DPCM  Explain principle and problems of motion estimation  Explain fullsearch, hierarchical and recursive blockbased motion estimation, and estimate their complexity
