Noiseless coding of correlated information sources

Slepian, D.; Wolf, J.K.

doi:10.1109/tit.1973.1055037

Cited by 3,405 publications

(2,792 citation statements)

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“…The Slepian-Wolf theorem shows that for lossless communication of correlated information sources, distributed encoding can perform as well as joint encoding [1]. Although this surprising and beautiful result does not extend fully, comparable results for lossy coding show that the rate loss can be small using Berger-Tung encoding (see, e.g., [2]), again suggesting that communication between encoders of correlated information sources has little or no utility.…”

Section: Introductionmentioning

confidence: 99%

Chatting in distributed quantization networks

Sun

Goyal

2012

2012 50th Annual Allerton Conference on Communication, Control, and Computing (Allerton)

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Abstract-Several key results in source coding offer the intuition that distributed encoding via vector-quantize-and-bin is only slightly suboptimal to joint encoding and oftentimes is just as good. However, when source acquisition requires the blocklength to be small, collaboration between sensors can greatly reduce distortion. For a distributed acquisition network where sensors are allowed to "chat" using a side channel, we provide exact characterization of distortion performance and quantizer design in the high-resolution (low-distortion) regime using a framework called distributed functional scalar quantization (DFSQ). The key result is that chatting can dramatically improve performance even when the intersensor communication is at very low rate. We also solve the rate allocation problem when communication links have heterogeneous costs and provide examples to demonstrate that this theory predicts performance at practical communication rates.

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Section: Introductionmentioning

confidence: 99%

Chatting in distributed quantization networks

Sun

Goyal

2012

2012 50th Annual Allerton Conference on Communication, Control, and Computing (Allerton)

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“…To overcome this problem, Systematic Lossy Error Protection (SLEP) architecture was proposed [5]- [7]. SLEP uses Wyner-Ziv coding [8][9] to protect the bitstream can also achieve graceful degradation of the decoded video quality without the requirement of layered coding.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Lossy Error Protection architecture in H.264 video transmission

Chen

Lee

Chang

2009

2009 9th International Symposium on Communications and Information Technology

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Abstract-Systematic Lossy Error Protection (SLEP) is a robust error resilient mechanism which uses Wyner-Ziv coding to protect the video bitstream. In this paper, we propose a low overhead adaptive lossy error protection (ALEP) mechanism that provides a good trade-off between the error resilience and decoded video quality. The proposed method can generate appropriate redundant slices to provide proper error correction capability for varying channel conditions. The proposed method maintains good video quality at low packet loss rate compared to original SLEP and still provides sufficient error correction capability at high packet loss rate in our simulation results. It achieves 2-3 dB PSNR improvement at 5% packet loss rate for various video sequences in our simulations.

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“…Hence, most of the computational load is moved from the encoder to the decoder, since in this case the distributed video decoders (and not the encoders) perform motion estimation and motion compensated interpolation. Two theorems from information theory, namely the Slepian-Wolf theorem [21] for lossless distributed source coding and the Wyner-Ziv (WZ) theorem [25] for lossy source coding with side information, suggest that such a system with intra-frame encoding and inter-frame decoding can come close to the efficiency of a traditional inter-frame encoding-decoding system.…”

Section: Introductionmentioning

confidence: 99%

Reduced decoder complexity and latency in pixel-domain Wyner–Ziv video coders

Morbée

Roca

Prades-Nebot

et al. 2007

SIViP

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In some video coding applications, it is desirable to reduce the complexity of the video encoder at the expense of a more complex decoder. Wyner-Ziv (WZ) video coding is a new paradigm that aims to achieve this. To allocate a proper number of bits to each frame, most WZ video coding algorithms use a feedback channel, which allows the decoder to request additional bits when needed. However, due to these multiple bit requests, the complexity and the latency of WZ video decoders increase massively. To overcome these problems, in this paper we propose a rate allocation (RA) algorithm for pixel-domain WZ video coders. This algorithm estimates at the encoder the number of bits needed for the decoding of every frame while still keeping the encoder complexity low. Experimental results show that, by using our RA algorithm, the number of bit requests over the feedback channel -and hence, the decoder complexity and the latency -are significantly reduced. Meanwhile, a very near-to-optimal rate-distortion performance is maintained.

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Noiseless coding of correlated information sources

Cited by 3,405 publications

References 1 publication

Chatting in distributed quantization networks

Chatting in distributed quantization networks

Adaptive Lossy Error Protection architecture in H.264 video transmission

Reduced decoder complexity and latency in pixel-domain Wyner–Ziv video coders

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