Publication detail

Reference Free SSIM Estimation for Full HD Video Content

RIES, M. SLANINA, M. GARCIA, D.

Original Title

Reference Free SSIM Estimation for Full HD Video Content

English Title

Reference Free SSIM Estimation for Full HD Video Content

Type

conference paper

Language

en

Original Abstract

This paper proposes a reference free video quality estimation method for full high definition video services based on a structural similarity index. The design of our estimator is based on an artificial neural network. To achieve this, the neural network was trained with a set of video statistical parameters estracted from the most representative video contents. Moreover, estimations with neural networks allow higher applicability and require lower processing power as known reference based methods. Finally, the achieved correlation between the calculated and the estimated structural similarity index shows a very good fit.

English abstract

This paper proposes a reference free video quality estimation method for full high definition video services based on a structural similarity index. The design of our estimator is based on an artificial neural network. To achieve this, the neural network was trained with a set of video statistical parameters estracted from the most representative video contents. Moreover, estimations with neural networks allow higher applicability and require lower processing power as known reference based methods. Finally, the achieved correlation between the calculated and the estimated structural similarity index shows a very good fit.

Keywords

Video quality; structural similarity; high definition video service; artificial neural network

RIV year

2011

Released

19.04.2011

Publisher

Vysoké učení technické v Brně

Location

Brno

ISBN

978-1-61284-322-3

Book

Proceedings of the 21st International Conference Radioelektronika 2011

Pages from

225

Pages to

228

Pages count

4

BibTex


@inproceedings{BUT37076,
  author="Michal {Ries} and Martin {Slanina} and David Mora {Garcia}",
  title="Reference Free SSIM Estimation for Full HD Video Content",
  annote="This paper proposes a reference free video quality estimation method for full high definition video services based on a structural similarity index. The design of our estimator is based on an artificial neural network. To achieve this, the neural network was trained with a set of video statistical parameters estracted from the most representative video contents. Moreover, estimations with neural networks allow higher applicability and require lower processing power as known reference based methods. Finally, the achieved correlation between the calculated and the estimated structural similarity index shows a very good fit.",
  address="Vysoké učení technické v Brně",
  booktitle="Proceedings of the 21st International Conference Radioelektronika 2011",
  chapter="37076",
  howpublished="print",
  institution="Vysoké učení technické v Brně",
  year="2011",
  month="april",
  pages="225--228",
  publisher="Vysoké učení technické v Brně",
  type="conference paper"
}