Abstract
With the advancement of IPTV and HDTV technology, previous subtle errors in videos are now becoming more prominent because of the structure oriented and compression based artifacts. In this paper, we focus towards the development of a real-time video quality check system. Light weighted edge gradient magnitude information is incorporated to acquire the statistical information and the distorted frames are then estimated based on the characteristics of their surrounding frames. Then we apply the prominent texture patterns to classify them in different block errors and analyze them not only in video error detection application but also in error concealment, restoration and retrieval. Finally, evaluating the performance through experiments on prominent datasets and broadcasted videos show that the proposed algorithm is very much efficient to detect errors for video broadcast and surveillance applications in terms of computation time and analysis of distorted frames.
Abstract (translated)
随着IPTV和HDTV技术的进步，由于面向结构和基于压缩的工件，视频中先前的细微错误现在变得更加突出。在本文中，我们专注于开发实时视频质量检查系统。合并轻量级边缘梯度幅度信息以获取统计信息，然后基于其周围帧的特性估计失真帧。然后我们应用突出的纹理模式将它们分类为不同的块错误，并且不仅在视频错误检测应用中而且在错误隐藏，恢复和检索中分析它们。最后，通过对着名数据集和广播视频的实验来评估性能表明，所提出的算法在计算时间和失真帧分析方面非常有效地检测视频广播和监视应用的错误。
URL
https://arxiv.org/abs/1808.10086
