An HVS-inspired video deinterlacer based on visual saliency

In this paper, a spatial saliency-guided motion-compensated deinterlacing method is proposed which accounts for the properties of the Human Visual System (HVS): Our algorithm classifies the field according to its texture and viewer’s region of interest and adapts the motion estimation and compensation, as well as the saliency-guided interpolation to ensure high-quality frame reconstruction.