一种实时视频质量评价的回归方法

M. T. Vega, D. Mocanu, A. Liotta
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引用次数: 5

摘要

无参考(NR)指标提供了一种在不断增长的无线网络中评估视频质量的机制。其低计算复杂度和功能特点使其成为实时内容管理和移动流媒体控制的首选。不幸的是,普通NR指标的准确性很差,特别是在网络受损的视频流中。在这项工作中,我们引入了一种基于回归的视频质量度量,它足够简单,可以在瘦客户端上进行实时计算,并且与最先进的全参考(FR)度量相当准确,后者在功能和计算上在实时流媒体中是不可实现的。我们将我们的指标与FR指标VQM(视频质量指标)进行基准测试,发现了一个非常强的相关因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Regression Method for real-time video quality evaluation
No-Reference (NR) metrics provide a mechanism to assess video quality in an ever-growing wireless network. Their low computational complexity and functional characteristics make them the primary choice when it comes to realtime content management and mobile streaming control. Unfortunately, common NR metrics suffer from poor accuracy, particularly in network-impaired video streams. In this work, we introduce a regression-based video quality metric that is simple enough for real-time computation on thin clients, and comparably as accurate as state-of-the-art Full-Reference (FR) metrics, which are functionally and computationally inviable in real-time streaming. We benchmark our metric against the FR metric VQM (Video Quality Metric), finding a very strong correlation factor.
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