Please use this identifier to cite or link to this item: https://doi.org/10.1145/1291233.1291411
Title: A compressed domain distortion measure for fast video transcoding
Authors: Huang, Y.
Tran, A.V. 
Wang, Y. 
Keywords: Mean compressed domain error
Video transcoding
Issue Date: 2007
Source: Huang, Y., Tran, A.V., Wang, Y. (2007). A compressed domain distortion measure for fast video transcoding. Proceedings of the ACM International Multimedia Conference and Exhibition : 787-790. ScholarBank@NUS Repository. https://doi.org/10.1145/1291233.1291411
Abstract: 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. Copyright 2007 ACM.
Source Title: Proceedings of the ACM International Multimedia Conference and Exhibition
URI: http://scholarbank.nus.edu.sg/handle/10635/41867
ISBN: 9781595937025
DOI: 10.1145/1291233.1291411
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Page view(s)

52
checked on Jan 14, 2018

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.