This paper presents an extensible and reusable framework which addresses the problem of video quality assessment over IP networks. The proposed tool (referred to as Video-Tester) supports raw uncompressed video encoding and decoding. It also includes different video over IP transmission methods (i.e.: RTP over UDP unicast and multicast, as well as RTP over TCP). In addition, it is furnished with a rich set of offline analysis capabilities. Video-Tester analysis includes QoS and bitstream parameters estimation (i.e.: bandwidth, packet inter-arrival time, jitter and loss rate, as well as GOP size and I-frame loss rate). Our design facilitates the integration of virtually any existing video quality metric thanks to the adopted Python-based modular approach. Video-Tester currently provides PSNR, SSIM, ITU-T G.1070 video quality metric, DIV and PSNR-based MOS estimations. In order to promote its use and extension, Video-Tester is open and publicly available.
On the other hand, it is also remarkable the seminal work (EvalVid) proposed by Klaue @cite_13 , a widely used tool-set for video transmission evaluation. This tool-set does actually include transmission, some quality of service (QoS) parameter estimation (packet loss, delay and jitter) and some bitstream parameter evaluations (frame loss rate and frame jitter). EvalVid video quality evaluation techniques include PSNR, Structural Similarity index (SSIM) @cite_16 , Mean Opinion Score (MOS, mapped from PSNR) and Distortion in Inverval (DIV, mapped from MOS as described in @cite_15 ).
@cite_15 @cite_16 @cite_13
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With EvalVid we present a complete framework and tool-set for evaluation of the quality of video transmitted over a real or simulated communication network. Besides measuring QoS parameters of the underlying network, like loss rates, delays, and jitter, we support also a subjective video quality evaluation of the received video based on the frame-by-frame PSNR calculation. The tool-set has a modular construction, making it possible to exchange both the network and the codec. We present here its application for MPEG-4 as example. EvalVid is targeted for researchers who want to evaluate their network designs or setups in terms of user perceived video quality. The tool-set is publicly available [11]. End-to-end packet delay is an important performance parameter on the Internet, because it heavily affects the quality of real-time applications. Currently, however, because the packet transmission quality (e.g., transmission delay, jitter, packet loss) may vary dynamically, it is not easy to handle real-time traffic. For UDP-based real-time applications, a smoothing buffer (playout buffer) is typically used at the client to compensate for variable delays. The issue of playout control has been studied previously, and several algorithms for controlling the playout buffer have been proposed. These studies considered the network parameters (e.g., packet loss ratio and playout delay), but not the quality perceived by end users. We first clarify the relations between mean opinion score (MOS) of played audio and the network parameters (e.g., packet loss, packet transmission delay, and transmission rate). Then, utilizing the MOS function, we propose a new playout buffer algorithm that considers the user's perceived quality for real-time applications. Our simulation and implementation tests show that the algorithm can enhance the perceived quality more effectively than existing algorithms. The Long Term Evolution (LTE) is a high data rates and fully All-IP network. Scheduling and resource allocation are very important tasks in LTE network. So that, the optimization of the real-time services transmission is very essential. However, there are many challenges when deploying the live multimedia services such as VoIP, Video, etc. This paper proposes a new scheduling scheme which based on the Wideband (WB) E-model, Channeland QoS-Aware (known as WE-MQS scheduler) for voice traffic in LTE downlink direction. The voice traffic flow is very sensitive to network impairments such as delay, packet loss, jitter, etc. The proposed scheduling scheme is based on the extension of the WB E-model and the consideration of Maximum Queue Size (MQS) as a factor for the metric. Since this scheduling scheme considers Mean Opinion Score (MOS) values, thus, it gets higher user perception. The simulation results show that the proposed scheme has the performance which not only satisfies QoS requirements of voice services but also outperforms well-known schedulers such as Frame Level Scheduler (FLS), Modified Largest Weighted Delay First (MLWDF) and Exponential Proportional Fair (EXP PF) schedulers in terms of delay for all the number of user (NU) and Packet Loss Rate (PLR) when the NU is more than 47. For the cell throughput, Fairness Index (FI), and Spectral Efficiency, the proposed scheduler is always in the middle of the remaining schedulers. The performance evaluation is compared in terms of Delay, PLR, Throughput, FI, and FI for FLS, M-LWDF, EXP PF schedulers and the proposed one.