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An error-based video quality assessment method with temporal information

机译:基于时间信息的基于错误的视频质量评估方法

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摘要

Videos are amongst the most popular online media for Internet users nowadays. Thus, it is of utmost importance that the videos transmitted through the internet or other transmission media to have a minimal data loss and acceptable visual quality. Video quality assessment (VQA) is a useful tool to determine the quality of a video without human intervention. A new VQA method, termed as Error and Temporal Structural Similarity (EaTSS), is proposed in this paper. EaTSS is based on a combination of error signals, weighted Structural Similarity Index (SSIM) and difference of temporal information. The error signals are used to weight the computed SSIM map and subsequently to compute the quality score. This is a better alternative to the usual SSIM index, in which the quality score is computed as the average of the SSIM map. For the temporal information, the second-order time-differential information are used for quality score computation. From the experiments, EaTSS is found to have competitive performance and faster computational speed compared to other existing VQA algorithms.
机译:视频是当今互联网用户最受欢迎的在线媒体之一。因此,通过互联网或其他传输媒体传输的视频具有最小的数据丢失和可接受的视觉质量至关重要。视频质量评估(VQA)是无需人工干预即可确定视频质量的有用工具。本文提出了一种新的VQA方法,称为误差和时间结构相似性(EaTSS)。 EaTSS基于误差信号,加权结构相似性指数(SSIM)和时间信息差异的组合。误差信号用于对计算出的SSIM映射进行加权,然后用于计算质量得分。这是通常的SSIM索引的更好替代方法,在常规的SSIM索引中,质量得分被计算为SSIM映射的平均值。对于时间信息,将二阶时差信息用于质量得分计算。从实验中发现,与其他现有的VQA算法相比,EaTSS具有竞争性能和更快的计算速度。

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