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We investigate a model for image/video quality assessment based on building aset of codevectors representing in a sense some basic properties of images,similar to well-known CORNIA model. We analyze the codebook building method andpropose some modifications for it. Also the algorithm is investigated from thepoint of inference time reduction. Both natural and synthetic images are usedfor building codebooks and some analysis of synthetic images used for codebooksis provided. It is demonstrated the results on quality assessment may beimproves with the use if synthetic images for codebook construction. We alsodemonstrate regimes of the algorithm in which real time execution on CPU ispossible for sufficiently high correlations with mean opinion score (MOS).Various pooling strategies are considered as well as the problem of metricsensitivity to bitrate.

Image quality prediction using synthetic and natural codebooks: comparative results