Dragotti P.L., Gastpar M. Distributed Source Coding. Theory, Algorithms and Applications

Academic Press, 2009. — 348 p.In conventional source coding, a single encoder exploits the redundancy of the source in order to perform compression. Applications such as wireless sensor and camera networks, however, involve multiple sources often separated in space that need to be compressed independently. In such applications, it is not usually feasible to first transport all the data to a central location and compress (or further process) it there. The resulting source coding problem is often referred to as distributed source coding (DSC). Its foundations were laid in the 1970s, but it is only in the current decade that practical techniques have been developed, along with advances in the theoretical underpinnings. The practical advances were, in part, due to the rediscovery of the close connection between distributed source codes and (standard) error-correction codes for noisy channels. The latter area underwent a dramatic shift in the 1990s, following the discovery of turbo and low-density parity-check (LDPC) codes. Both constructions have been used to obtain good distributed source codes.
In a related effort, ideas from distributed coding have also had considerable impact on video compression, which is basically a centralized compression problem. In this scenario, one can consider a compression technique under which each video frame must be compressed separately, thus mimicking a distributed coding problem. The resulting algorithms are among the best-performing and have many additional features, including, for example, a shift of complexity from the encoder to the decoder.Part I Theory
Foundations of Distributed Source Coding
Distributed Transform Coding
Quantization for Distributed Source Coding
Zero-error Distributed Source Coding
Distributed Coding of Sparse Signals
Part II Algorithms and Applications
Toward Constructive Slepian-Wolf Coding Schemes
Distributed Compression in Microphone Arrays
Distributed Video Coding: Basics, Codecs, and Performance
Model-based Multiview Video Compression Using Distributed Source Coding Principles
Distributed Compression of Hyperspectral Imagery
Securing Biometric Data