Smoothness Constraints in Recursive Search Motion Estimation for Picture Rate Conversion

Many motion compensation algorithms are based on block matching. The quality of the block correlation depends on the validity of the brightness constancy assumption and the assumption of fixed translational motion within a block. These assumptions are invalid in areas with texture changes, noise, lighting changes, and rapid deformations. Smoothness priors should enforce stable estimates in these regions by propagating neighboring estimates, while preserving hard object boundaries (piecewise smoothness). Most motion estimation algorithms that successfully implement these constraints are computationally complex. In this paper, we show an intuitive and computationally efficient way to implement them within the framework of (real-time) recursive search, targeting consumer-market embedded devices with limited resources.