Abstract :
In this paper, we first present new upper and lower bounds for the rate loss of multiple description source codes (MDSCs). For a two-description MDSC (2DSC), the rate loss of description i with distortion Di is Li = Ri $R(Di ), i isin {1, 2}, where Ri is the rate of the ith description; the joint rate loss associated with decoding the two descriptions together to achieve central distortion D0 is L 0 = R1 + R2 - R(D0). We show that given any memoryless source with variance sigma2 and mean squared error distortion measure, for any optimal 2DSC, (a) 0 les L0 les 0.8802 if D0 les D1 + D2 - sigma2; (b) 0 les L1, L2 les 0.4401 if D0 ges (1/D1 + 1/D2 - 1/sigma2)-1; (c) 0 les L1, L2 les 0.3802 and R(max{D1, D2}) - 1 les L0 les R(max{D1, D2}) + 0.3802 otherwise. We also present a tighter bound on the distance between the El Gamal-Cover inner bound and the achievable region. In addition, these new bounds, which are easy to compute, inspire new designs of low-complexity near-optimal 2DSC. In essence, we demonstrate that any optimal 2DSC can be nearly separated into a multi-resolution source code and a traditional single-resolution code, and the resulting rate penalty for each description is less than 0.6901 bit/sample for general sources and less than 0.5 bit/sample for successively refinable sources
Keywords :
mean square error methods; memoryless systems; source coding; El Gamal-Cover inner bound; central distortion; joint rate loss; low-complexity near-optimal 2DSC; mean squared error distortion measure; memoryless source; multi-resolution source code; near separability; optimal multiple description source codes; rate penalty; successively refinable sources; traditional single-resolution code; two-description MDSC; Compression algorithms; Decoding; Degradation; Delay systems; Distortion measurement; Loss measurement; Performance loss; Postal services; Rate distortion theory; Rate-distortion;