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The Wyner-Ziv Problem with Noisy Side-Information at the Encoder

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On the Information Rates of the Plenoptic Function

Martin Vetterli, Minh Do

The plenoptic function describes the visual information available to an observer at any point in space and time. Samples of the plenoptic function (POF) are seen in video and in general visual content (images, mosaics, panoramic scenes, etc.), and rep- res ...

Institute of Electrical and Electronics Engineers2010

Universal Source Polarization and Spare Recovery

Emmanuel Abbé

Polar codes allow to perform lossless compression of i.i.d. sources at the lowest rate with low encoding and decoding complexity. In this paper, it is shown that for binary sources, there exist “universal polar codes” which can compress any source of low e ...

2010

Lossy Source Coding with Gaussian or Erased Side-Information

Emre Telatar, Suhas Diggavi, Etienne Perron

In this paper we find properties that are shared between two seemingly unrelated lossy source coding setups with side information. The first setup is when the source and side information are jointly Gaussian and the distortion measure is quadratic. The sec ...

2009

Lossy Source Coding with Gaussian or Erased Side-Information

Emre Telatar, Suhas Diggavi, Etienne Perron

In this paper we find properties that are shared between two seemingly unrelated lossy source coding setups with side-information. The first setup is when the source and side-information are jointly Gaussian and the distortion measure is quadratic. The sec ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2009

Polar Codes are Optimal for Lossy Source Coding

Rüdiger Urbanke, Satish Babu Korada

We consider lossy source compression of a binary symmetric source with Hamming distortion function. We show that polar codes combined with a low-complexity successive cancellation encoding algorithm achieve the rate-distortion bound. The complexity of both ...

2009

Linear Compressive Networks

Michael Christoph Gastpar, Naveen Goela

A linear compressive network (LCN) is defined as a graph of sensors in which each encoding sensor compresses incoming jointly Gaussian random signals and transmits (potentially) low-dimensional linear projections to neighbors over a noisy uncoded channel. ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2009

Lower Bounds on the Rate-Distortion Function of Individual LDGM Codes

Rüdiger Urbanke, Shrinivas Kudekar

We consider lossy compression of a binary symmetric source by means of a low-density generator-matrix code. We derive two lower bounds on the rate distortion function which are valid for any low-density generator-matrix code with a given node degree distri ...

2008

Side-Information Scalable Source Coding

Suhas Diggavi

We consider the problem of side-information scalable (SI-scalable) source coding, where the encoder constructs a two-layer description, such that the receiver with high quality side information will be able to use only the first layer to reconstruct the so ...

Institute of Electrical and Electronics Engineers2008

Selected topics on distributed video coding

Mourad Ouaret

Distributed Video Coding (DVC) is a new paradigm for video compression based on the information theoretical results of Slepian and Wolf (SW), and Wyner and Ziv (WZ). While conventional coding has a rigid complexity allocation as most of the complex tasks a ...

EPFL2008

On the Heegard-Berger/Kaspi problem with decoder cooperation

Dinkar Vasudevan

We consider decoder cooperation in the Heegard-Berger/Kaspi problem. The encoder sends a common description of a source to two decoders, one of which has side information. Cooperation between the two decoders is of the form of a limited capacity link from ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2008