Detail publikace

Estimating H.264/AVC Video PSNR Without Reference Using the Artificial Neural Network Approach

Originální název

Estimating H.264/AVC Video PSNR Without Reference Using the Artificial Neural Network Approach

Anglický název

Estimating H.264/AVC Video PSNR Without Reference Using the Artificial Neural Network Approach

Jazyk

en

Originální abstrakt

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.

Anglický abstrakt

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.

BibTex


@inproceedings{BUT26704,
  author="Martin {Slanina} and Václav {Říčný}",
  title="Estimating H.264/AVC Video PSNR Without Reference Using the Artificial Neural Network Approach",
  annote="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.",
  address="INSTICC",
  booktitle="Sigmap 2008 International Conference on Signal Processing and Multimedia Applications Proceedings",
  chapter="26704",
  howpublished="print",
  institution="INSTICC",
  year="2008",
  month="july",
  pages="244--250",
  publisher="INSTICC",
  type="conference paper"
}