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231224s2013 xx |||||o 00| ||eng c |
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|a 10.1109/TIP.2012.2233486
|2 doi
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|a pubmed25n0745.xml
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|a (DE-627)NLM223515760
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|a eng
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|a Zhang, Fan
|e verfasserin
|4 aut
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|a Additive log-logistic model for networked video quality assessment
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|c 2013
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|a Text
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|a ƒaComputermedien
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|a ƒa Online-Ressource
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|a Date Completed 22.07.2013
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|a Date Revised 12.02.2013
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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|a Modeling subjective opinions on visual quality is a challenging problem, which closely relates to many factors of the human perception. In this paper, the additive log-logistic model (ALM) is proposed to formulate such a multidimensional nonlinear problem. The log-logistic model has flexible monotonic or nonmonotonic partial derivatives and thus is suitable to model various uni-type impairments. The proposed ALM metric adds the distortions due to each type of impairment in a log-logistic transformed space of subjective opinions. The features can be evaluated and selected by classic statistical inference, and the model parameters can be easily estimated. Cross validations on five Telecommunication Standardization Sector of International Telecommunication Union (ITU-T) subjectively-rated databases confirm that: 1) based on the same features, the ALM outperforms the support vector regression and the logistic model in quality prediction and, 2) the resultant no-reference quality met-ric based on impairment-relevant video parameters achieves high correlation with a total of 27 216 subjective opinions on 1134 video clips, even compared with existing full-reference quality metrics based on pixel differences. The ALM metric wins the model competition of the ITU-T Study Group 12 (where the validation databases are independent with the training databases) and thus is being put forth into ITU-T Recommendation P.1202.2 for the consent of ITU-T
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|a Journal Article
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|a Research Support, Non-U.S. Gov't
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|a Lin, Weisi
|e verfasserin
|4 aut
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|a Chen, Zhibo
|e verfasserin
|4 aut
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|a Ngan, King Ngi
|e verfasserin
|4 aut
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|i Enthalten in
|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
|d 1992
|g 22(2013), 4 vom: 07. Apr., Seite 1536-47
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|x 1941-0042
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|g volume:22
|g year:2013
|g number:4
|g day:07
|g month:04
|g pages:1536-47
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|u http://dx.doi.org/10.1109/TIP.2012.2233486
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