Statistical Multiplexing based on MPEG-4 Fine Granularity Scalability Coding

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Abstract

Conventional statistical multiplexing methods for MPEG-1/2 programs involve high computationally complex transcoding (decoding and re-encoding) process to convert the original bit-rate into the target bit-rate. To avoid a time-consuming transcoding process, a new statistical multiplexer is proposed to enable content provider to easily convert the bit-rates by exploiting the MPEG-4 fine granularity scalability (FGS) coding scheme. The proposed statistical multiplexer is particularly useful for multiple-program broadcasting applications, including Internet television and video on demand, as well as value-added MPEG-4 video streaming services for DVB and ATSC digital TV systems. The proposed multiplexer mainly includes two parts: the FGS-based frame lag scheme and the optimal bit-plane truncation scheme. The FGS-based frame lag scheme exploits intra- and inter-layer correlations exist in MPEG-4 FGS bit-streams. The optimal bit-plane truncation scheme dynamically truncates enhancement layers of FGS bit-streams under the available bandwidth constraint and the quality/smoothness constraint. Experimental results show that high statistical multiplexing efficiency, inter-program fairness, and intra-program smoothness are achieved by the proposed multiplexer.

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