On Some New Approaches to Practical Slepian-Wolf Compression Inspired by Channel Coding

We introduce three new innovations for compression using LDPCs for the Slepian-Wolf problem. The first is a general iterative Slepian-Wolf decoding algorithm that incorporates the graphical structure of all the encoders and operates in a `turbo-like' fashion. The second innovation introduces source-splitting to enable low-complexity pipelined implementations of Slepian-Wolf decoding at rates besides corner points of the Slepian-Wolf region. This innovation can also be applied to single-source block coding for reduced decoder complexity. The third approach is a linear programming relaxation to maximum-likelihood sequence decoding that exhibits the ML-certificate property. This can be used for decoding a single binary block-compressed source as well as decoding at vertex points for the binary SlepianWolf problem. All three of these innovations were motivated by recent analogous results in the channel coding domain.

• Type: Conference
• Year: 2004
• Where: DCC
• Authors: Anna H. Lee, Michelle Effros, Muriel Médard, Todd P. Coleman
• Keywords: Binary Slepianwolf Problem, Channel Coding Domain, Computer Graphics, DCC 2004, Slepian-Wolf Decoding Algorithm