If one mentions a difficult to pronounce name on the phone, a good choice to avoid misunderstandings is to use the phonetic alphabet, like this: "Tango Uniform - Delta Romeo Echo Sierra Delta Echo November." Channel coding adapts this principle to digital communication. It deals with transformations of data with the aim to protect it against distortion on a channel. Channel coding protects the integrity of data by adding redundancy. However, unlike cryptographic methods for integrity protection, channel coding does not assume intentional adversaries but rather random distortion according to stochastic channel models. Specific coding methods yield different performance depending on the channel model, the characteristics of the data and the available computational resources (and energy) at the coding and decoding devices.

Our research is specialised on finding efficient pre-processing algorithms for embedding operations into host signals. We explore structured and random codes regarding their properties to minimise the number of changes to the host signal. Our teaching activities span the entire field of modern information and coding theory.

• Informations- und Kodierungstheorie, by H. Klimant, R. Piotraschke and D. Schönfeld, 3. Auflage, Teubner, Wiesbaden, 2006.
• Reduced Embedding Complexity Using BP Message Passing for LDGM Codes, by P. Günther, D. Schönfeld and A. Winkler, in E. Delp und P. Wong: Steganography and Watermarking of Multimedia Contents X (Proc. of IST/SPIE), 2008.