A compressed domain distortion measure for fast video transcoding

Video applications on different mobile devices are becoming increasingly popular. It is an attractive alternative to transcode a high quality non-scalable video bitstream to match constraints (such as bandwidth or processing power) of different platforms with a similar functionality as a scalable video format. In principle, such a transcoder can reduce either the bit per frame (bpf) or the frame per second (fps) of the original bitstream to meet a particular constraint. In the case that multiple candidates with different combinations of bpf and fps satisfy the constraint, an objective video quality measure is needed for the transcoder to choose the candidate with the overall best quality considering both the spatial quality (reflected by bpf) and the temporal quality (reflected by fps). Conventional measures, such as PSNR and MSE operate in the pixel-domain, require full decoding of both the original and candidate video bitstreams and are computationally very expensive. This drawback renders them unsuitable for real-time transcoding applications. To solve this problem, we propose a Mean Compressed Domain Error (MCDE) to predict the quality of the transcoded video. Experimental results show that the proposed MCDE can predict video quality accurately with a negligible computational complexity in comparison with the conventional MSE/PSNR.