Fairness-oriented multi-stream rate adaptation using scalable video coding
Image Communication
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In this paper, we address the problem of joint rate allocation for scalable video coding (SVC) of multiple video programs using the fine granularity scalability (FGS), which is not specified by any current H.264/AVC profile. Most of the existing approaches are based on non-SVC platforms, where computationally expensive encoding or transcoding is demanded to adjust the bit-rate of each video program. Different from all these works, we develop a new statistical multiplexing system, where FGS is applied to compress the video programs. First, we propose an efficient look-ahead approach to distribute the base layer coding bit-rate. Second, a piecewise linear model is applied to accurately estimate the rate-distortion relationship in the FGS layers. Based on this model, a novel algorithm is designed to dynamically allocate the available bandwidth to different programs for rate adaptation in order to minimize the variation of quality of different video programs. Experiments are carried out to verify the performance of the proposed scheme by comparing it with existing methods. The results demonstrate the superiority of the proposed scheme and the quality difference between different programs is greatly reduced.