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PreprintarXiv licencearXiv

Successive Refinement Under Strong-Sense Perfect Perception

  • Yu Yang
  • Changhong Liu
  • Weijie Yuan
  • Lin Zhou
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Abstract

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.

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Cite

BibTeXRIS
BibTeX
@misc{yang2026successive,
  title = {{Successive Refinement Under Strong-Sense Perfect Perception}},
  author = {Yu Yang and Changhong Liu and Weijie Yuan and Lin Zhou},
  howpublished = {arXiv},
  year = {2026},
  month = sep,
  doi = {10.48550/arxiv.2609.14404},
  eprint = {2609.14404},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.14404},
}
RIS
TY  - UNPB
TI  - Successive Refinement Under Strong-Sense Perfect Perception
AU  - Yu Yang
AU  - Changhong Liu
AU  - Weijie Yuan
AU  - Lin Zhou
PY  - 2026
DA  - 2026/09/13
PB  - arXiv
DO  - 10.48550/arxiv.2609.14404
UR  - https://arxiv.org/abs/2609.14404
AB  - 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.
ER  -