In this paper, regional attention to structural degradations in images is analyzed to improve perceptual quality prediction performance of objective image quality metrics. Subjective experiments were conducted to identify regions-of-interest for a set of natural images. A region-selective metric design is then applied to four objective image quality metrics which were trained and validated with respect to quality prediction accuracy and generalization to unknown images. For this purpose, data is used from subjective quality experiments conducted at two independent laboratories. It is shown that the region-selective design is highly beneficial for the considered objective image quality metrics, in particular, prediction accuracy can be significantly increased.
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