Video signals are a very important part of multimedia applications. Due to limited network bandwidth, video signals are subjected to the compression process, which introduces different compression artifacts. During network transmission, additional artifacts are introduced in video signals due to random bit errors and packet loss (PL). Both mentioned artifact types degrade visual quality of the video signal and thus, it has to be continuously monitored to ensure the required quality of service (QoS) provided to end users. An important component of the video quality monitoring system deals with video transmission artifact detection. In this paper, a no-reference (NR) pixel-based video transmission artifact detection algorithm is proposed, called the packet loss area measure (PLAM) algorithm. When detecting video transmission artifacts, the PLAM algorithm takes into account spatial and temporal information of a video signal. The performance of the proposed PLAM algorithm has been compared to those of the three existing different PL detection algorithms on a broad set of significantly different video signals from two publicly available video databases. One of these databases, called the Referent Packet Loss (RPL) database, has been created within this research and is presented in this paper. The algorithm performance testing results show that PLAM achieves high performance and overcomes other tested algorithms. Furthermore, the results show that the PLAM algorithm is very robust when detecting video transmission artifacts in video signals of different contents, with distinct degradation levels and PL error-concealment methods used in decoder post-processing. Due to its low computational complexity, the PLAM algorithm is capable of processing Full HD and Ultra HD video signals with the frame rate up to 100 and 25 frames per second (fps), respectively, in real time, in the case when high-end CPU is used.
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This work was supported by Josip Juraj Strossmayer University of Osijek business fund through the internal competition for the research and artistic projects IZIP-2016, via the project “Providing of digital video signal based services in rural and rarely populated areas”.
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Glavota, I., Kaprocki, Z., Vranješ, M. et al. No-reference real-time video transmission artifact detection for video signals. J Real-Time Image Proc 17, 799–820 (2020). https://doi.org/10.1007/s11554-018-0824-6
- Video transmission artifact detection
- Real time