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

Authors:
Todd P. Coleman;Anna H. Lee;Muriel Médard;Michelle Effros
Affiliations:
-;-;-;-
Venue:
DCC '04 Proceedings of the Conference on Data Compression
Year:
2004

Citing 0
Cited 6

Collecting correlated information from a sensor network

SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
Lower bounds for asymmetric communication channels and distributed source coding

SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
Approaching the Slepian-Wolf boundary using practical channel codes

Signal Processing - Special section: Distributed source coding
A general and optimal framework to achieve the entire rate region for Slepian-Wolf coding

Signal Processing - Special section: Distributed source coding
Geometry-driven distributed compression of the plenoptic function: performance bounds and constructive algorithms

IEEE Transactions on Image Processing
Heegard-Berger video coding using LMMSE estimator

PCM'06 Proceedings of the 7th Pacific Rim conference on Advances in Multimedia Information Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

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