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Near separability of optimal multiple description source codes

Authors: null Hanying Feng;

Near separability of optimal multiple description source codes

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

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
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