As multimedia services such as video streaming, video conferencing, virtual reality (VR), and online gaming continue to expand, ensuring high perceptual visual quality becomes a priority to maintain user satisfaction and competitiveness. However, multimedia content undergoes various distortions during acquisition, compression, transmission, and storage, resulting in the degradation of experienced quality. Thus, perceptual visual quality assessment (PVQA), which focuses on evaluating the quality of multimedia content based on human perception, is essential for optimizing user experiences in advanced communication systems. Several challenges are involved in the PVQA process, including diverse characteristics of multimedia content such as image, video, VR, point cloud, mesh, multimodality, etc., and complex distortion scenarios as well as viewing conditions. In this paper, we first present an overview of PVQA principles and methods. This includes both subjective methods, where users directly rate their experiences, and objective methods, where algorithms predict human perception based on measurable factors such as bitrate, frame rate, and compression levels. Based on the basics of PVQA, quality predictors for different multimedia data are then introduced. In addition to traditional images and videos, immersive multimedia and generative artificial intelligence (GenAI) content are also discussed. Finally, the paper concludes with a discussion on the future directions of PVQA research.

翻译：随着视频流媒体、视频会议、虚拟现实（VR）和在线游戏等多媒体服务的持续扩展，确保高感知视觉质量已成为维持用户满意度和竞争力的关键。然而，多媒体内容在采集、压缩、传输和存储过程中会经历各种失真，导致体验质量下降。因此，感知视觉质量评估（PVQA）——专注于基于人类感知评估多媒体内容的质量——对于优化先进通信系统中的用户体验至关重要。PVQA过程涉及多项挑战，包括图像、视频、VR、点云、网格、多模态等多媒体内容的多样化特性，以及复杂的失真场景和观看条件。本文首先概述了PVQA的原理与方法，既包括用户直接评价体验的主观方法，也包括算法基于比特率、帧率、压缩等级等可测量因素预测人类感知的客观方法。基于PVQA的基础知识，本文继而介绍了针对不同多媒体数据的质量预测器。除传统图像和视频外，还讨论了沉浸式多媒体与生成式人工智能（GenAI）内容。最后，本文对PVQA研究的未来方向进行了总结性探讨。