Multiple Description Coding for Stationary and Ergodic Sources

Authors:
Jun Chen;Chao Tian;Suhas Diggavi
Affiliations:
IBM T. J. Watson Research Center;Swiss Federal Institute of Technology (EPFL);Swiss Federal Institute of Technology (EPFL)
Venue:
DCC '07 Proceedings of the 2007 Data Compression Conference
Year:
2007

Citing 0
Cited 3

Filter banks for prediction-compensated multiple description coding

IEEE Transactions on Signal Processing
Multiple description coding of discrete ergodic sources

Allerton'09 Proceedings of the 47th annual Allerton conference on Communication, control, and computing
N-channel asymmetric entropy-constrained multiple-description lattice vector quantization

IEEE Transactions on Information Theory

Quantified Score

Hi-index	0.06

Visualization

Abstract

We consider the problem of multiple description (MD) coding for stationary sources with the squared error distortion measure. The MD rate region is derived for the stationary and ergodic Gaussian sources, and is shown to be achievable with a practical transform lattice quantization scheme. Moreover, the proposed scheme is asymptotically optimal at high resolution for all stationary sources with finite differential entropy rate.