Title :
Reference free SSIM estimation for full HD video content
Author :
Ries, Michal ; Slanina, Martin ; Garcia, David Mora
Author_Institution :
Inst. of Telecommun., Univ. of Technol. Vienna, Vienna, Austria
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 extracted 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 :
high definition video; neural nets; statistical analysis; video signal processing; artificial neural network; full HD video content; full high definition video service; reference free SSIM estimation; reference-free video quality estimation; structural similarity index; video statistical parameter; Artificial neural networks; Estimation; High definition video; Indexes; Quantization; Streaming media; Training; Video quality; artificial neural network; high definition video service; structural similarity;
Conference_Titel :
Radioelektronika (RADIOELEKTRONIKA), 2011 21st International Conference
Conference_Location :
Brno
Print_ISBN :
978-1-61284-325-4
DOI :
10.1109/RADIOELEK.2011.5936447