Title :
No-Reference Transmission Distortion Modelling for H.264/AVC-Coded Video
Author :
Uzair, Muhammad ; Dony, Robert D.
Author_Institution :
Sch. of Eng., Univ. of Guelph, Guelph, ON, Canada
Abstract :
In this paper, a low-complexity No-reference algorithm for real-time estimation of the channel induced distortion is proposed. The algorithm is capable of providing video quality evaluation for the network service provider perspective to the end-user. An analytical model has been proposed to estimate the mean square error (mse) distortion at the MB, frame, and sequence level. The algorithm takes into account the spatiotemporal dynamics of the video sequence. The transmission distortion is estimated because of the spatial and temporal error concealment, along with the effects of temporal propagation distortion due to the motion compensation. The algorithm is capable of measuring the transmission distortion for video sequence encoded as I, P, and B frames, as compared to most of the proposed algorithms which are not capable of working with B frames at all. However, the bandwidth-constrained resource networks make compression very important, which is not possible without B frames. The proposed algorithm is experimentally tested and validated with video signals encoded according to the H.264/AVC video coding standard. A novel experimental setup is established to simulate the video traffic and simulation results show that the proposed algorithm shows better results as compared to other proposed algorithms.
Keywords :
estimation theory; image sequences; mean square error methods; motion compensation; video coding; H.264/AVC-coded video; MSE; analytical model; channel induced distortion; mean square error; motion compensation; real-time estimation; reference transmission distortion modelling; spatial error concealment; spatiotemporal dynamics; temporal error concealment; temporal propagation distortion; video quality; video sequence; video traffic; Distortion; Distortion measurement; Heuristic algorithms; Prediction algorithms; Quality assessment; Streaming media; Video recording; Distortion Modelling; H.264; Network Video; Quality Assessment; distortion modelling; network video; quality assessment;
Journal_Title :
Signal and Information Processing over Networks, IEEE Transactions on
DOI :
10.1109/TSIPN.2015.2476695