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The objective of multiple description coding (MDC) is to encode a source into multiple bitstreams supporting multiple quality levels of decoding. In this paper, we only consider the two-description case, where the requirement is that a high-quality reconstruction should be decodable from the two bitstreams together, while lower, but still acceptable,(More)
We propose multiple description (MD) video coders which use motion compensated predictions. Our MD video coders utilize MD transform coding and three separate prediction paths at the encoder, to mimic the three possible scenarios at the decoder: both descriptions received or either of the single descriptions received. We provide three different algorithms(More)
—We consider the problem of predicting packet loss visibility in MPEG-2 video. We use two modeling approaches: CART and GLM. The former classifies each packet loss as visible or not; the latter predicts the probability that a packet loss is visible. For each modeling approach, we develop three methods, which differ in the amount of information available to(More)
In this paper we show that modulating the source rate of a video encoder based on feedback information from the network results in graceful degradation in picture quality during periods of congestion. Such source rate modulation techniques have been used in the past in designing video encoders used to generate data at a fixed rate. In such constant bit rate(More)
— Models for predicting the performance of multi-plexed variable bit rate video sources are important for engineering a network. However, models of a single source are also important for parameter negotiations and call admittance algorithms. In this paper we propose to model a single video source as a Markov renewal process whose states represent different(More)
This paper presents a source model for variable bit rate (VBR) video traffic. A finite state Markov chain is shown to accurately model one-and two-layer video of all activity levels on a per source basis. Our model captures the source dynamics, including the short-term correlations essential for studying network performance. The modeling technique is shown(More)