4,517 research outputs found

    The Likelihood Encoder for Lossy Compression

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    A likelihood encoder is studied in the context of lossy source compression. The analysis of the likelihood encoder is based on the soft-covering lemma. It is demonstrated that the use of a likelihood encoder together with the soft-covering lemma yields simple achievability proofs for classical source coding problems. The cases of the point-to-point rate-distortion function, the rate-distortion function with side information at the decoder (i.e. the Wyner-Ziv problem), and the multi-terminal source coding inner bound (i.e. the Berger-Tung problem) are examined in this paper. Furthermore, a non-asymptotic analysis is used for the point-to-point case to examine the upper bound on the excess distortion provided by this method. The likelihood encoder is also related to a recent alternative technique using properties of random binning

    Secure Lossy Source Coding with Side Information at the Decoders

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    This paper investigates the problem of secure lossy source coding in the presence of an eavesdropper with arbitrary correlated side informations at the legitimate decoder (referred to as Bob) and the eavesdropper (referred to as Eve). This scenario consists of an encoder that wishes to compress a source to satisfy the desired requirements on: (i) the distortion level at Bob and (ii) the equivocation rate at Eve. It is assumed that the decoders have access to correlated sources as side information. For instance, this problem can be seen as a generalization of the well-known Wyner-Ziv problem taking into account the security requirements. A complete characterization of the rate-distortion-equivocation region for the case of arbitrary correlated side informations at the decoders is derived. Several special cases of interest and an application example to secure lossy source coding of binary sources in the presence of binary and ternary side informations are also considered. It is shown that the statistical differences between the side information at the decoders and the presence of non-zero distortion at the legitimate decoder can be useful in terms of secrecy. Applications of these results arise in a variety of distributed sensor network scenarios.Comment: 7 pages, 5 figures, 1 table, to be presented at Allerton 201

    A simple encoder scheme for distributed residual video coding.

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    Rate-Distortion (RD) performance of Distributed Video Coding (DVC) is considerably less than that of conventional predictive video coding. In order to reduce the performance gap, many methods and techniques have been proposed to improve the coding efficiency of DVC with increased system complexity, especially techniques employed at the encoder such as encoder mode decisions, optimal quantization, hash methods etc., no doubt increase the complexity of the encoder. However, low complexity encoder is a widely desired feature of DVC. In order to improve the coding efficiency while maintaining low complexity encoder, this paper focuses on Distributed Residual Video Coding (DRVC) architecture and proposes a simple encoder scheme. The main contributions of this paper are as follows: 1) propose a bit plane block based method combined with bit plane re-arrangement to improve the dependency between source and Side Information (SI), and meanwhile, to reduce the amount of data to be channel encoded 2) present a simple iterative dead-zone quantizer with 3 levels in order to adjust quantization from coarse to fine. The simulation results show that the proposed scheme outperforms DISCOVER scheme for low to medium motion video sequences in terms of RD performance, and maintains a low complexity encoder at the same time

    Sequential coding of Gauss-Markov sources with packet erasures and feedback

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    We consider the problem of sequential transmission of Gauss-Markov sources. We show that in the limit of large spatial block lengths, greedy compression with respect to the squared error distortion is optimal; that is, there is no tension between optimizing the distortion of the source in the current time instant and that of future times. We then extend this result to the case where at time t a random compression rate rt is allocated independently of the rate at other time instants. This, in turn, allows us to derive the optimal performance of sequential coding over packet-erasure channels with instantaneous feedback. For the case of packet erasures with delayed feedback, we connect the problem to that of compression with side information that is known at the encoder and may be known at the decoder — where the most recent packets serve as side information that may have been erased, and demonstrate that the loss due to a delay by one time unit is rather small
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