A Synonymous Variational Perspective on the Rate-Distortion-Perception Tradeoff
Zijian Liang, Kai Niu, Changshuo Wang, Jin Xu, Ping Zhang

TL;DR
This paper introduces a novel theoretical framework for understanding the rate-distortion-perception tradeoff in signal compression through a synonymity-based semantic perspective, establishing a new variational analysis approach.
Contribution
It reformulates perceptual reconstruction as recovering any sample within a synonym set, and develops a synonymous variational inference framework with a new tradeoff analysis.
Findings
Establishes a synonymous RDP tradeoff based on the new framework.
Shows divergence naturally arises from synset-based reconstruction.
Clarifies the relationship between perceptual quality and semantic information.
Abstract
The fundamental limit of natural signal compression has traditionally been characterized by classical rate-distortion (RD) theory through the tradeoff between coding rate and reconstruction distortion, while the rate-distortion-perception (RDP) framework introduces a divergence-based measure of perceptual quality as a modeling principle rather than a theoretically-derived principle, leaving its theoretical origin unclear. In this paper, motivated by a synonymity-based semantic information perspective, we reformulate perceptual reconstruction as recovering any admissible sample within an ideal synonymous set (synset) associated with the source, rather than the source sample itself, and correspondingly establish a synonymous source coding architecture. On this basis, we develop a synonymous variational inference (SVI) analysis framework with a synonymous variational lower bound (SVLBO)…
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