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No-reference image and video quality estimation / Sheila S. Hemami in Signal processing. Image communication, Vol. 25 N° 7 (Août 2010) 

Public ISBD [article]  in Signal processing. Image communication > Vol. 25 N° 7 (Août 2010) . - pp. 469–481 Titre : No-reference image and video quality estimation : Applications and human-motivated design Type de document : texte imprimé Auteurs : Sheila S. Hemami, Auteur ; Amy R. Reibman, Auteur Année de publication : 2012 Article en page(s) : pp. 469–481 Note générale : Electronique Langues : Anglais (eng) Mots-clés : No-reference  Video  quality  Quality  metrics  Quality  estimator  Applications  of  quality  metrics  Blind  quality  assessment Résumé : This paper reviews the basic background knowledge necessary to design effective no-reference (NR) quality estimators (QEs) for images and video. We describe a three-stage framework for NR QE that encompasses the range of potential use scenarios for the NR QE and allows knowledge of the human visual system to be incorporated throughout. We survey the measurement stage of the framework, considering methods that rely on bitstream, pixels, or both. By exploring both the accuracy requirements of potential uses as well as evaluation criteria to stress-test a QE, we set the stage for our community to make substantial future improvements to the challenging problem of NR quality estimation. ISSN : 0923-5965 En ligne : http://www.sciencedirect.com/science/article/pii/S0923596510000688 [article] No-reference image and video quality estimation : Applications and human-motivated design [texte imprimé] / Sheila S. Hemami, Auteur ; Amy R. Reibman, Auteur . - 2012 . - pp. 469–481. Electronique Langues : Anglais (eng) in Signal processing. Image communication > Vol. 25 N° 7 (Août 2010) . - pp. 469–481 Mots-clés : No-reference  Video  quality  Quality  metrics  Quality  estimator  Applications  of  quality  metrics  Blind  quality  assessment Résumé : This paper reviews the basic background knowledge necessary to design effective no-reference (NR) quality estimators (QEs) for images and video. We describe a three-stage framework for NR QE that encompasses the range of potential use scenarios for the NR QE and allows knowledge of the human visual system to be incorporated throughout. We survey the measurement stage of the framework, considering methods that rely on bitstream, pixels, or both. By exploring both the accuracy requirements of potential uses as well as evaluation criteria to stress-test a QE, we set the stage for our community to make substantial future improvements to the challenging problem of NR quality estimation. ISSN : 0923-5965 En ligne : http://www.sciencedirect.com/science/article/pii/S0923596510000688