KEYWORDS: Video, Error analysis, Video compression, Video coding, Internet, Computer programming, Spatial filters, Signal to noise ratio, Distortion, Visualization
In this research, a video delivery system is proposed by integrating the layered codec and the proposed corruption model. In the system, it is assumed that the base layer packets are delivered without loss since they are assigned the most reliable service level. Then, packets in the enhancement layer are analyzed with the corruption model and categorized for differentiated delivery services. The corruption model for generating the relative priority index (RPI) is extended to layered bitstreams. In addition to taking into account the initial error and the propagation error due to packet loss, the dependency between the same and different layers is reflected in the modified macroblock corruption model. In order to facilitate the prioritized delivery of the enhancement layer, the RPI-based corruption model for each packet as well as coordinated delivery of packetized video over QoS networks are investigated. Finally, a per-packet optimization framework with unequal error protection (UEP) is realized to consider both end-to-end video performance and pricing. The performance of the proposed solution is verified with extensive simulations.
Our previous work in the corruption model is extended in this research to cover a more general error propagation scenario, and then used to develop a joint AIR/UEP (adaptive intra-refresh/unequal error protection) scheme. Basically, we relate AIR to the importance of packets via the corruption model at the encoder. Once the intra refresh ratio is determined, which is currently assumed to be known either by a priori knowledge or the network feedback, the expected distortion for each macroblock is calculated based on the corruption model and AIR is performed accordingly. The corruption model exploits the initial error strength, which depends on the normative error concealment scheme, and motion vectors of previously coded frames. The expected loss impact of each macroblock is calculated concurrently by recycling the same corruption model in the reverse direction. Furthermore, if there is feedback about packet loss (e.g. ACK/NACK), the stored corruption models for lost macroblocks are updated by error tracking so that the updated models will affect subsequent AIR/UEP accordingly. Finally, packetization of protected data is considered for video transmission over IP networks.
In this work, each packet is associated with a varying degree of significance based on the impact of its loss, which is estimated with a corruption model. For a compressed video stream, initial and propagation errors are first described by the macroblock (MB)-based corruption model by taking into account error concealment, temporal dependency, and loop filtering. Next, at the packet-level, a corruption model using the relative priority index (RPI) is constructed by integrating MB-based models. Furthermore, the effect of multiple-packet loss is analyzed and the associated RPI is calculated to improve the model accuracy at a higher packet loss rate. With the RPI-based corruption model for each packet, coordinated delivery of packetized video over QoS networks is investigated. Finally, a per-packet optimization framework with unequal error protection (UEP) is realized to consider both end-to-end video performance and pricing. The performance of the proposed solution is verified with intensive simulations.
Several analytical models have been recently introduced to estimate the impact of the error propagation effect on the source video caused by lossy transmission channels. However, previous work focused either on the statistical aspects for the whole sequence or had a high computational complexity. In this work, we concentrate on estimating the distortion caused by the loss of a packet with a moderate computational complexity. The proposed model considers both the spatial filtering effect and the temporal dependency that affect the error propagation behavior. To verify this model, a real loss propagation effect is measured and compared with that of the expected distortion level derived by the model. Also, its applicability to the quality of service (QoS) of transmitted video is demonstrated through the packet video evaluation over the simulated differentiated service (DiffServ) forwarding mechanism.
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