Detail publikačního výsledku

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

SLANINA, M.; ŘÍČNÝ, V.

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

Druh

Stať ve sborníku v databázi WoS či Scopus

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.

Klíčová slova

H.264/AVC, video quality, no reference assessment, PSNR, artificial neural network.

Klíčová slova v angličtině

H.264/AVC, video quality, no reference assessment, PSNR, artificial neural network.

Autoři

SLANINA, M.; ŘÍČNÝ, V.

Rok RIV

2010

Vydáno

26.07.2008

Nakladatel

INSTICC

Místo

Porto

ISBN

978-989-8111-60-9

Kniha

Sigmap 2008 International Conference on Signal Processing and Multimedia Applications Proceedings

Strany od

244

Strany do

250

Strany počet

7

BibTex

@inproceedings{BUT26704,
  author="Martin {Slanina} and Václav {Říčný}",
  title="Estimating H.264/AVC Video PSNR Without Reference Using the Artificial Neural Network Approach",
  booktitle="Sigmap 2008 International Conference on Signal Processing and Multimedia Applications Proceedings",
  year="2008",
  pages="244--250",
  publisher="INSTICC",
  address="Porto",
  isbn="978-989-8111-60-9"
}