Dynamic Rate Allocation Algorithm Using Adaptive LMS End-to-End Distortion Estimation for Video Transmission over Error Prone Network
Angelo R. Dela Cruz, Ryan Rhay P. Vicerra, Argel A. Bandala, and Elmer P. Dadios
De La Salle University
2401 Taft Ave. Manila 1004, Philippines
Because of the inherent trade-off between source distortion and channel distortion in video transmission systems, joint optimization between bit-rate and distortion is still a challenging task. In this paper, we propose a method where the bit-rate allocation between source and channel encoder is controlled by the estimated end-to-end distortion at the encoder. The distortion estimation scheme is based on the adaptive forward linear predictor using least-mean square (LMS) algorithm. The forward predictor used the past values of actual end-to-end distortion to estimate the current distortion. The results show good estimate of end-to-end distortion and the proposed scheme improves video quality as compared to a standard rate control of H.264/AVC. The proposed scheme dynamically allocates the source encoder bits based on the estimated distortion.
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