This article focuses on the compressed representations of pictures. The representation does not affect how many bits get from the Web server to the laptop, but it determines the usefulness of the bits that arrive. Many different representations are possible, and there is more involved in their choice than merely selecting a compression ratio. The techniques presented represent a single information source with several chunks of data ("descriptions") so that the source can be approximated from any subset of the chunks. By allowing image reconstruction to continue even after a packet is lost, this type of representation can prevent a Web browser from becoming dormant.

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Multiple description coding: compression meets the network

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 to control the mismatch between the prediction loops at the encoder and decoder. We present simulation results comparing the three approaches to two standards-based approaches to MD video coding. We show that when the main prediction loop at the encoder uses a two-channel reconstruction, it is important to have side prediction loops and transmit some redundancy information to control mismatch. We also examine the performance of our MD video coder with partial mismatch control in the presence of random packet loss, and demonstrate a significant improvement compared to more traditional approaches.

Multiple-description video coding using motion-compensated temporal prediction

We consider a simple multiple description (MD) video coder, that uses redundancy-rate-distortion criteria to split a one-layer stream generated by a standard video coder into two correlated streams. Our simulation results demonstrate that this MD coder has much better performance for large redundancies than our previous MDTC video coder, although it cannot perform as well at low redundancies. This MD video coder is very simple to implement and is compatible with H.263 to the extent that each description can be decoded by a standard H.263 decoder. This MD coder was used in a previous study on the transport of MD and layered video over an EGPRS wireless network, where the fact that it creates two streams with very balanced rates was a strong advantage.

Multiple description video using rate-distortion splitting

In this paper the windowed Fourier encoding-decoding scheme applied to the multiple description compression problem is analyzed. In the general case, four window functions are needed to define the encoder and decoder, although this number can be reduced to three or two by using time-shift or frequency-shift division schemes. The encoding coefficients are next divided into two groups according to the eveness of either the modulation or translation index. The distortion on each channel is analyzed using the Zak transform. For the optimal windows, explicit representation formulas are obtained and nonlocalization results are proved. Asymptotic formulas of the total distortion and transmission rate are established and the redundancy is shown to trade off between these two.

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The analysis and design of windowed Fourier frame based multiple description source coding schemes

A multiple description scalar quantization (MDSQ) based coding system can be regarded as a source coder (quantizer) followed by a channel coder, i.e. the combination of index and codeword assignment. The redundancy, or the correlation between the descriptions, is controlled by the number of diagonals covered by the index assignment. In this paper, we analyse dependencies between the variables involved in the MDSQ coding chain and design an estimation strategy making use of part of the global model of dependencies at each time. Inference of the hidden states of the connected models is done by applying belief propagation principles on the resulting Bayesian network. We try to evidence the most appropriate form of redundancy one should introduce in the context of variable length code compressed streams in order to fight against de-synchronizations when impaired by channel noise.

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Soft decoding of multiple descriptions

This paper considers the transmission of multiple descriptions over noisy channels rather than the on-off channels that are traditionally considered. We introduce the use of iterative decoding techniques similar to those used in "turbo" decoding to decode multiple correlated descriptions transmitted over a noisy channel. For a given transmission rate per channel and a given channel state, the efficacy of iterative decoding depends on the correlatedness of the two descriptions produced by the multiple description encoder. We demonstrate that there is an optimal amount of redundancy or correlation for a given channel state. Hence, multiple description codes may also be viewed as joint source-channel codes.

M. Srinivasan

Papers

Iterative decoding of multiple descriptions