Perception-aware lossy source coding has attracted significant recent interest. It augments the classical distortion criterion with an explicit perception constraint, thereby enabling more refined control over fidelity and perceptual quality. Despite rapid progress, the diversity of rate-distortion-perception formulations and their underlying assumptions remains poorly understood by many practitioners. In particular, there is often a tendency to rely heavily on the expressive power of deep neural networks and generative models without clear theoretical guidance, using fundamental limits merely as performance benchmarks rather than as sources of design insight. This tutorial paper aims to bridge this gap by surveying information-theoretic principles that can be leveraged to develop constructive approaches to perception-aware lossy source coding. We distill practical guidelines implied by rate-distortion-perception theory and demonstrate how they inform the design of implementable coding schemes. A simple unit-circle example is used as a pedagogical tool to illustrate key ideas, architectural principles, and tradeoffs in an intuitive and unified manner. Both one-shot and asymptotic settings are examined to highlight conceptual similarities and operational differences. We also clarify the role of common randomness and the notion of universal representation, and elucidate the connections between perception-aware and conventional lossy source coding. Overall, this tutorial provides a principled foundation for developing perception-aware compression systems that go beyond black-box model design.

翻译：近年来，感知感知的有损信源编码引起了广泛关注。该方法通过引入明确的感知约束来增强传统失真准则，从而实现对保真度与感知质量更精细的控制。尽管取得了快速进展，但率失真感知公式的多样性及其潜在假设仍令许多实践者感到困惑。特别地，人们往往倾向于过度依赖深度神经网络和生成模型的表达能力，而缺乏清晰的理论指导，仅将基本极限作为性能基准而非设计洞察的来源。本教程论文旨在弥补这一差距，系统梳理可应用于开发感知感知有损信源编码构造性方法的信息论原理。我们提炼出率失真感知理论蕴含的实用设计准则，并展示这些准则如何指导可实现编码方案的设计。通过一个简单的单位圆示例作为教学工具，以直观统一的方式阐释核心思想、架构原则及权衡关系。同时考察单次传输与渐进传输两种场景，突出概念相似性与操作差异性。我们还厘清了公共随机性与通用表征概念的作用，并阐明感知感知编码与传统有损信源编码之间的关联。总体而言，本教程为开发超越黑箱模型设计的感知感知压缩系统提供了原理性基础。