ESTIMATING H.264/AVC VIDEO PSNR WITHOUT REFERENCE - Using the Artificial Neural Network Approach

Martin Slanina, Václav Říčný

2008

Abstract

This paper presents a method capable of estimating peak signal-to-noise ratios (PSNR) of digital video sequences compressed using the H.264/AVC algorithm. The idea is in replacing a full reference metric - the PSNR (for whose evaluation we need the original as well as the processed video data) - with a no reference metric, operating on the encoded bit stream only. As we are working just with the encoded bit stream, we can spare a significant amount of computations needed to decode the video pixel values. In this paper, we describe the network inputs and network configurations, suitable to estimate PSNR in intra and inter predicted pictures. Finally, we make a simple evaluation of the proposed algorithm, having the correlation coefficient of the real and estimated PSNRs as the measure of optimality.

References

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Paper Citation


in Harvard Style

Slanina M. and Říčný V. (2008). ESTIMATING H.264/AVC VIDEO PSNR WITHOUT REFERENCE - Using the Artificial Neural Network Approach . In Proceedings of the International Conference on Signal Processing and Multimedia Applications - Volume 1: SIGMAP, (ICETE 2008) ISBN 978-989-8111-60-9, pages 244-250. DOI: 10.5220/0001932502440250


in Bibtex Style

@conference{sigmap08,
author={Martin Slanina and Václav Říčný},
title={ESTIMATING H.264/AVC VIDEO PSNR WITHOUT REFERENCE - Using the Artificial Neural Network Approach},
booktitle={Proceedings of the International Conference on Signal Processing and Multimedia Applications - Volume 1: SIGMAP, (ICETE 2008)},
year={2008},
pages={244-250},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001932502440250},
isbn={978-989-8111-60-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Signal Processing and Multimedia Applications - Volume 1: SIGMAP, (ICETE 2008)
TI - ESTIMATING H.264/AVC VIDEO PSNR WITHOUT REFERENCE - Using the Artificial Neural Network Approach
SN - 978-989-8111-60-9
AU - Slanina M.
AU - Říčný V.
PY - 2008
SP - 244
EP - 250
DO - 10.5220/0001932502440250