On Successive Refinement for the Kaspi/Heegard–Berger Problem

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Successive refinement of information

269 Abslruct-The successive refinement of information consists of first approximating data using a few hits of information, then iteratively improving the approximation as more and more information is supplied. The goal is to achieve an optimal description at each stage. In general an ongoing description is sought which is rate-distortion optimal whenever it is interrupted. It is shown that a r...

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Rate-distortion bounds for scalable coding, and conditions under which they coincide with nonscalable bounds, have been extensively studied. These bounds have been derived for the general tree-structured refinement scheme, where reproduction at each layer is an arbitrarily complex function of all encoding indexes up to that layer. However, inmost practical applications (e.g., speech coding) “ad...

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Successive Refinement of Abstract Sources

In successive refinement of information, the decoder refines its representation of the source progressively as it receives more encoded bits. The rate-distortion region of successive refinement describes the minimum rates required to attain the target distortions at each decoding stage. In this paper, we derive a parametric characterization of the rate-distortion region for successive refinemen...

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Successive Refinement of Gaussian Projections

Successive refinement is a technique to encode a source iteratively, improving the distortion at each step. If the code rates of all steps combined can be as efficient as coding only for the final distortion in one go, then the source is said to be successively refinable. We turn our attention to vector sources and we propose to replace the high-distortion first stage by a projection to low-dim...

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ژورنال

عنوان ژورنال: IEEE Transactions on Information Theory

سال: 2010

ISSN: 0018-9448,1557-9654

DOI: 10.1109/tit.2010.2050951