发表机构
School of Automation and Intelligent Manufacturing, Southern University of Science and Technology（南方科技大学自动化与智能制造学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文研究强感知完美感知约束下的连续细化有损信源编码，推导了率失真-感知区域，并证明伯努利信源在汉明失真下仍可连续细化。
AI 中文摘要
我们重新审视了一个名为连续细化的多终端有损信源编码问题，并在存在无限公共随机性的情况下，推导了强感知完美感知约束下的率失真-感知区域。具体而言，在连续细化中，目标是压缩一个信源序列，并允许两个不同的解码器以不同的失真水平恢复该信源序列。通过施加强感知完美感知约束，我们的结果通过分析感知质量的影响，细化了先前的结果。我们的可达性证明受输出约束有损信源编码的启发，而我们的逆命题证明则改编了标准连续细化问题的证明步骤。此外，我们提供了一个伯努利信源的数值示例来说明我们的结果，并表明在汉明失真下，即使有强感知完美感知约束，伯努利信源也是可连续细化的。
英文摘要
We revisit a multiterminal lossy source coding problem named successive refinement and derive the rate-distortion-perception region under the strong-sense perfect perception constraint in the presence of unlimited common randomness. Specifically, in successive refinement, one aims to compress a source sequence and allows two distinct decoders to recover the source sequence at different distortion levels. By imposing the strong-sense perfect perception constraint, our results refine the previous result by analyzing the impact of the perceptual quality. Our achievability proof is inspired by output constrained lossy source coding and our converse proof adapts the proof steps of the standard successive refinement problem. Furthermore, we provide a numerical example of the Bernoulli source to illustrate our result and show that the Bernoulli source under Hamming distortion is successively refinable even with the strong-sense perfect perception constraint.
CommentsExtended version of the ICASSP 2027 submission, including complete proofs
