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NARVAL: A no-reference video quality tool for real-time communications
  DOI :  10.2352/ISSN.2470-1173.2019.12.HVEI-213  Published OnlineJanuary 2019
Abstract

In this paper we introduce two new no-reference metrics and compare their performance to state-of-the-art metrics on six publicly available datasets having a large variety of distortions and characteristics. Our two metrics, based on neural networks, combine the following features: histogram of oriented gradients, edges detection, fast fourier transform, CPBD, blur and contrast measurement, temporal information, freeze detection, BRISQUE and Video BLIINDS. They perform better than Video BLIINDS and BRISQUE on the six datasets used in this study, including one made up of natural videos that have not been artificially distorted. Our metrics show a good generalization as they achieved high performance on the six datasets.

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Augustin Lemesle, Alexis Marion, Ludovic Roux, Alexandre Gouaillard, "NARVAL: A no-reference video quality tool for real-time communicationsin Proc. IS&T Int’l. Symp. on Electronic Imaging: Human Vision and Electronic Imaging,  2019,  pp 213-1 - 213-7,  https://doi.org/10.2352/ISSN.2470-1173.2019.12.HVEI-213

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