The quest for the integration of visual saliency models in objective image quality assessment: A distraction power compensated combination strategy

Novel research on image quality metrics (IQMs) attempts to further improve their reliability by including visual attention aspects of the human visual system. Literature so far mainly focuses on the extension of a specific IQM with a specific visual saliency model. In this paper, we quest the integration of visual saliency models in IQMs, in terms of its statistical meaningfulness and combination strategy. In the first step an exhaustive evaluation is conducted by integrating twenty state-of-the-art saliency models into eight best-known IQMs for image quality assessment. It demonstrates linearly combining saliency and IQMs yields a statistically significant gain in performance. Based on the statistics, we revisit the combination strategy of saliency and IQMs and propose a new strategy taking into account the distraction power of local distortions. Results show that the proposed combination strategy consistently outperforms the conventionally used linear combination strategy.