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The Rate-Distortion-Perception Tradeoff: The Role of Common Randomness
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A rate-distortion-perception (RDP) tradeoff has recently been proposed by Blau and Michaeli and also Matsumoto. Focusing on the case of perfect realism, which coincides with the problem of distribution-preserving lossy compression studied by Li et al., a coding theorem for the RDP tradeoff that allows for a specified amount of common randomness between the encoder and decoder is provided. The existing RDP tradeoff is recovered by allowing for the amount of common randomness to be infinite. The quadratic Gaussian case is examined in detail.
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Cited by 4 Pith papers
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R\'enyi Rate-Distortion-Perception-Privacy Tradeoff under Indirect Observation
The work characterizes the scalar Gaussian Rényi rate-distortion-perception-privacy tradeoff under indirect observation and introduces a conditional privacy measure that avoids penalizing legitimate semantic recovery.
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Rate-Distortion-Perception Trade-off with Strong Realism Constraints: Role of Side Information and Common Randomness
The paper gives single-letter rate-distortion-perception limits for lossy compression with side information under strong realism constraints, including a complete Gaussian solution.
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The Rate-Distortion-Deception Tradeoff
For any distortion budget and allowed statistical distance to a chosen target distribution, the minimum compression rate is the solution of an information-theoretic optimization problem; the paper derives it for Berno...
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Rate-Distortion-Perception Theory: Redefining the Fundamental Limits of Information Representation
This paper is a tutorial that assembles methods, mostly from the authors' prior work, for computing rate–distortion–perception trade-offs under f-divergence, α-divergence, Wasserstein, and perfect-realism constraints.
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