Video image assessment with a distortion-weighing spatiotemporal visual attention model

For the purpose of extracting attention regions from distorted videos, a distortion-weighing spatiotemporal visual attention model is proposed. On the impact of spatial and temporal saliency maps, visual attention regions are acquired directed in a bottom-up manner. Meanwhile, the blocking artifact saliency map is detected according to intensity gradient features. An attention selection is applied to identify one of visual attention regions with more relatively serious blocking artifact as the Focus of Attention (FOA) directed in a top-down manner. Experimental results show that the proposed model can not only accurately analyze the spatiotemporal saliency based on the intensity, the texture, and the motion features, but also able to estimate the blocking artifact of distortions in comparing with Walther’s and You’s models.