The problem of multimedia communications over best-effort networks is addressed here with multiple description coding (MDC) in a distributed framework. In this paper, we first compare four video MDC schemes based on different time splitting patterns and temporal twoor three-band motion-compensated temporal filtering (MCTF). Then, the latter schemes are extended with systematic lossy description...

Channel Coding with Side Information at the encoder(CCSI) can be visualized as a blind watermarking problem: the original host signal for embedding the watermark is known at the encoder but not at the decoder. Similarly, the Rate Distortion with Side Information at the decoder(RDSI) is known as distributed source coding: the rate distortion limits of an input source if a noisy observation of th...

Distributed source coding (DSC) is a coding paradigm for systems which fully or partly exploit the source statistics at the decoder to reduce the computational burden at the encoder. Distributed video coding (DVC) is one example. This paper considers the use of Low Density Parity Check Accumulate (LDPCA) codes in a DSC scheme with feed-back. To improve the LDPC coding performance in the context...

We consider multicast of correlated sources over a network. Assuming the use of random network coding, we provide a linear optimization formulation for allocation of link rates in the network, also known as subgraph construction. Such an approach requires joint distributed source and network coding, which often has a lower cost than of that required by separated source and network coding. We su...

Achievable rate distortion region for the quadratic Gaussian multi-terminal source coding was recently solved by Wagner, Tavildar, and Viswanath [1]. Although it is a very important result, the proofs are somewhat ad-hoc and hard to be generalized. Recently, Courtade and Weissman [2] established the complete achievable rate region of two-encoder multi-terminal source coding problem under logari...

In a communication network, suppose there are a collection of (correlated) source nodes that want to communicate to a common sink node, then the distributed source coding problem is one of designing a system (of encoders and decoder) that optimally compresses the correlated sources. The key aspect of the design is that the source nodes aren’t allowed to communicate with one another –i.e., the s...

Distributed source coding, separate encoding (compression) and joint decoding of statistically dependent sources, arises in an increasing number of applications like sensor networks and multiview video coding. Many of those applications are highly interactive, requiring the development of low-delay, energy-limited communication and computing schemes. Currently, this compression is performed by ...

In the context of Distributed Joint Source-Channel coding (DJSC), we conceive reduced-complexity Turbo Trellis Coded Modulation (TTCM)-aided syndrome-based block decoding for estimating the crossover probability pe of the Binary Symmetric Channel (BSC), which models the correlation between a pair of sources. Our joint decoder achieves an accurate correlation estimation for varying correlation c...

We address the problem of designing optimal quantizers for distributed source coding. The generality of our formulation includes both the symmetric and asymmetric scenarios, together with a number of coding schemes, such as the ideal coding achieving a rate equal to the joint conditional entropy of the quantized sources given the side information. We show the optimality conditions quantizers mu...

This paper deals with the application of distributed source coding (DSC) theory to remote sensing image processing systems. We first provide a brief overview of DSC of correlated information sources. We discuss several possible applications of DSC in a remote sensing system, aimed at improving the performance of on-board, on-the-ground and hybrid lossless image compression systems. We then focu...