Several attempts to integrate visual saliency information in quality metrics are described in literature, albeit with contradictory results. The way saliency is integrated in quality metrics should reflect the mechanisms underlying the interaction between image quality assessment and visual attention. This interaction is actually two-fold: (1) image distortions can attract attention away from the Natural Scene Saliency (NSS), and (2) the quality assessment task in itself can affect the way people look at an image. A subjective study was performed to analyze the deviation in attention from NSS as a consequence of being asked to assess the quality of distorted images, and, in particular, whether, and if so how, this deviation depended on the distortion kind and/or amount. Saliency maps were derived from eye-tracking data obtained during scoring distorted images, and they were compared to the corresponding NSS, derived from eye-tracking data obtained during freely looking at high quality images. The study revealed some structural differences between the NSS maps and the ones obtained during quality assessment of the distorted images. These differences were related to the quality level of the images; the lower the quality, the higher the deviation from the NSS was. The main change was identified as a shrinking of the region of interest, being most evident at low quality. No evident role for the kind of distortion in the change in saliency was found. Especially at low quality, the quality assessment task seemed to prevail on the natural attention, forcing it to deviate in order to better evaluate the impact of artifacts.
In REF , the authors also reported that image distortion affects visual attention, especially for low quality images.
Interactions of visual attention and quality perception
Electronic Imaging
Engineering Physics Computer Science