Source coding with correlated decoder side information is considered. We impose the practical constraint that the encoder be unaware of even the statistical dependencies between source and side information. Two classes of rate-adaptive distributed source codes, both based on Low-Density Parity-Check (LDPC) codes, are developed and their design is studied. Specific realizations are shown to be b...

In the paper we advocate image compression technique in the scope of distributed source coding framework. The novelty of the proposed approach is twofold: classical image compression is considered from the positions of source coding with side information and, contrarily to the existing scenarios, where side information is given explicitly, side information is created based on deterministic appr...

A video coding paradigm called PRISM (Power-efficient, Robust, hIgh compression, Syndrome-based Multimedia coding) built on distributed source coding principles has been recently proposed in [1]. In this paper, we study a scalable version of PRISM which addresses both spatial and temporal scalability. The proposed codec inherits the main attributes of the PRISM architecture, namely increased ro...

We extend high-rate quantization theory to distributed source coding for the case in which the rate is the conditional entropy of the quantization index given the side information. This theory is applied to orthonormal block transforms for distributed source coding. A formula for the optimal rate allocation and an approximation to the optimal transform are derived. We implement a transform-doma...

In this work, we consider a distributed source coding problem with a joint distortion criterion depending on the sources and the reconstruction. This includes as a special case the problem of computing a function of the sources to within some distortion and also the classic Slepian-Wolf problem [62], Berger-Tung problem [46], Wyner-Ziv problem [44], Yeung-Berger problem [47] and the Ahlswede-Ko...

PILGRIM, RYAN ZACHARY. Source Coding Optimization for Distributed Average Consensus. (Under the direction of Dror Baron.) Consensus is a common method for computing a function of the data distributed among the nodes of a network. Of particular interest is distributed average consensus, whereby the nodes iteratively compute the sample average of the data stored at all the nodes of the network us...

A printed photograph is difficult to reuse because the digital information that generated the print may no longer be available. This paper describes a mechanism for approximating the original digital image by combining a scan of the printed photograph with small amounts of digital auxiliary information kept together with the print. The auxiliary information consists of a small amount of digital...

Inspired by mobile satellite communications systems, we consider a source coding system which consists of multiple sources, multiple encoders, and multiple decoders. Each encoder has access to a certain subset of the sources, each decoder has access to certain subset of the encoders, and each decoder reconstructs a certain subset of the sources almost perfectly. The connectivity between the sou...

In networked systems where distributed inferencing and control needs to be performed, the raw-data generated at different nodes needs to be transformed and combined in a number of ways to extract actionable information. This requires performing distributed computations on the rawdata. A pure data-transfer solution approach would advocate first reliably reproducing the rawdata at decision-making...

We consider the distributed source coding system of L correlated Gaussian sources Yl, l = 1, 2, · · · , L which are noisy observations of correlated Gaussian remote sources Xk, k = 1, 2, · · · ,K. We assume that Y L = (Y1, Y2, · · · , YL) is an observation of the source vector X = (X1, X2, · · · , XK), having the form Y L = AX+N, where A is a L×K matrix and N = (N1, N2, · · · , NL) is a vector ...