222 research outputs found
Successive Wyner-Ziv Coding Scheme and its Application to the Quadratic Gaussian CEO Problem
We introduce a distributed source coding scheme called successive Wyner-Ziv
coding. We show that any point in the rate region of the quadratic Gaussian CEO
problem can be achieved via the successive Wyner-Ziv coding. The concept of
successive refinement in the single source coding is generalized to the
distributed source coding scenario, which we refer to as distributed successive
refinement. For the quadratic Gaussian CEO problem, we establish a necessary
and sufficient condition for distributed successive refinement, where the
successive Wyner-Ziv coding scheme plays an important role.Comment: 28 pages, submitted to the IEEE Transactions on Information Theor
Side-information Scalable Source Coding
The problem of side-information scalable (SI-scalable) source coding is
considered in this work, where the encoder constructs a progressive
description, such that the receiver with high quality side information will be
able to truncate the bitstream and reconstruct in the rate distortion sense,
while the receiver with low quality side information will have to receive
further data in order to decode. We provide inner and outer bounds for general
discrete memoryless sources. The achievable region is shown to be tight for the
case that either of the decoders requires a lossless reconstruction, as well as
the case with degraded deterministic distortion measures. Furthermore we show
that the gap between the achievable region and the outer bounds can be bounded
by a constant when square error distortion measure is used. The notion of
perfectly scalable coding is introduced as both the stages operate on the
Wyner-Ziv bound, and necessary and sufficient conditions are given for sources
satisfying a mild support condition. Using SI-scalable coding and successive
refinement Wyner-Ziv coding as basic building blocks, a complete
characterization is provided for the important quadratic Gaussian source with
multiple jointly Gaussian side-informations, where the side information quality
does not have to be monotonic along the scalable coding order. Partial result
is provided for the doubly symmetric binary source with Hamming distortion when
the worse side information is a constant, for which one of the outer bound is
strictly tighter than the other one.Comment: 35 pages, submitted to IEEE Transaction on Information Theor
On rate-distortion with mixed types of side information
In this correspondence, we consider rate-distortion examples in the presence of side information. For a system with some side information known at both the encoder and decoder, and some known only at the decoder, we evaluate the rate distortion function for both Gaussian and binary sources. While the Gaussian example is a straightforward generalization of the corresponding result by Wyner, the binary example proves more difficult and is solved using a multidimensional optimization approach. Leveraging the insights gained from the binary example, we then solve the more complicated binary Heegard and Berger problem of decoding when side information may be present. The results demonstrate the existence of a new type of successive refinement in which the refinement information is decoded together with side information that is not available for the initial description
On Multistage Successive Refinement for Wyner-Ziv Source Coding with Degraded Side Informations
We provide a complete characterization of the rate-distortion region for the
multistage successive refinement of the Wyner-Ziv source coding problem with
degraded side informations at the decoder. Necessary and sufficient conditions
for a source to be successively refinable along a distortion vector are
subsequently derived. A source-channel separation theorem is provided when the
descriptions are sent over independent channels for the multistage case.
Furthermore, we introduce the notion of generalized successive refinability
with multiple degraded side informations. This notion captures whether
progressive encoding to satisfy multiple distortion constraints for different
side informations is as good as encoding without progressive requirement.
Necessary and sufficient conditions for generalized successive refinability are
given. It is shown that the following two sources are generalized successively
refinable: (1) the Gaussian source with degraded Gaussian side informations,
(2) the doubly symmetric binary source when the worse side information is a
constant. Thus for both cases, the failure of being successively refinable is
only due to the inherent uncertainty on which side information will occur at
the decoder, but not the progressive encoding requirement.Comment: Submitted to IEEE Trans. Information Theory Apr. 200
Polar Codes for Distributed Hierarchical Source Coding
We show that polar codes can be used to achieve the rate-distortion functions
in the problem of hierarchical source coding also known as the successive
refinement problem. We also analyze the distributed version of this problem,
constructing a polar coding scheme that achieves the rate distortion functions
for successive refinement with side information.Comment: 14 page
Multiuser Successive Refinement and Multiple Description Coding
We consider the multiuser successive refinement (MSR) problem, where the
users are connected to a central server via links with different noiseless
capacities, and each user wishes to reconstruct in a successive-refinement
fashion. An achievable region is given for the two-user two-layer case and it
provides the complete rate-distortion region for the Gaussian source under the
MSE distortion measure. The key observation is that this problem includes the
multiple description (MD) problem (with two descriptions) as a subsystem, and
the techniques useful in the MD problem can be extended to this case. We show
that the coding scheme based on the universality of random binning is
sub-optimal, because multiple Gaussian side informations only at the decoders
do incur performance loss, in contrast to the case of single side information
at the decoder. We further show that unlike the single user case, when there
are multiple users, the loss of performance by a multistage coding approach can
be unbounded for the Gaussian source. The result suggests that in such a
setting, the benefit of using successive refinement is not likely to justify
the accompanying performance loss. The MSR problem is also related to the
source coding problem where each decoder has its individual side information,
while the encoder has the complete set of the side informations. The MSR
problem further includes several variations of the MD problem, for which the
specialization of the general result is investigated and the implication is
discussed.Comment: 10 pages, 5 figures. To appear in IEEE Transaction on Information
Theory. References updated and typos correcte
Distributed video coding for wireless video sensor networks: a review of the state-of-the-art architectures
Distributed video coding (DVC) is a relatively new video coding architecture originated from two fundamental theorems namely, Slepian–Wolf and Wyner–Ziv. Recent research developments have made DVC attractive for applications in the emerging domain of wireless video sensor networks (WVSNs). This paper reviews the state-of-the-art DVC architectures with a focus on understanding their opportunities and gaps in addressing the operational requirements and application needs of WVSNs
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