A number of image quality metrics are based on psychophysical models of the human visual system. We propose a new framework for image quality assessment, gathering three indexes describing the image quality in terms of visual performance, visual appearance, and visual attention. These indexes are built on three vision models grounded on psychophysical data: we use models from Mantiuk et al. (visual performance), Moroney et al. (visual appearance), and Itti, Koch, and Niebur (visual attention). For accuracy reasons, the sensor and display system characteristics are taken into account in the evaluation process, so that these indexes characterize the image acquisition, processing, and display pipeline. We give evidence that the three image quality indexes, all derived from psychophysical data, are very weakly correlated. This emphasizes the need for a multicomponent description of image quality.