Low-complexity frame importance modelling and resource allocation scheme for error-resilience H.264 video streaming

Abstract

In this paper, we addressed the problem of redundancy allocation for protecting packet loss for better quality of service (QoS) in real-time H.264 video streaming. A novel error-resilient approach is proposed for the transmission of pre-encoded H.264 video stream under bandwidth constrained networks. A novel frame importance model is derived for estimating relative importance index for different H.264 video frames. Combining with the characteristics of the network, the optimal resource allocation strategy for different video frames can be determined for achieving improved error resilience. The model uses frame error propagation index (FEPI) to characterize video quality degradation caused by error propagation in different frames in a GOP when suffer from packet loss. This model can be calculated in DCT domain with the parameters extracted directly from the bitstream. Therefore, the complexity of the proposed scheme is very low and much better for real-time video transmission. Simulation results show that the proposed scheme can improve the receiver side reconstructed video quality remarkably under different channel loss patterns.