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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao https://doi.org/10.1...arrow_drop_down
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Distributed Coding Based Multiple Descriptions for Robust Video Transmission over Error-Prone Networks

Authors: Dinh Trieu Duong;

Distributed Coding Based Multiple Descriptions for Robust Video Transmission over Error-Prone Networks

Abstract

In this paper, we propose a novel multiple description coding (MDC) method to enhance the robustness of video transmission over error-prone networks. The proposed MDC method provides benefits of both distributed video coding (DVC) and multiple description coding techniques, which can offer not only higher performance compared to the conventional MDC methods but also effective scheme for the error resilience. In the proposed MDC method, the input video sequence is split into odd and even group of pictures (GOPs) subsequences, which are independently encoded using the new H.265/High efficiency video coding (H.265/HEVC) based DVC technique. Though the codec itself is not the core novelty of this paper, our proposed codec is the first MDC codec in literature employing H.265/HEVC based DVC approaches, thus all results presented in this paper are new. Experimental results show that the proposed method can achieve a wide range of tradeoffs between coding efficiency and error resilience, and provide much better peak signal-to-noise ratio (PSNR) performance than other conventional MDC methods.

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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
Average
Average
Average
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