An Optimal Quad-Tree-Based Motion Estimator

In this paper we propose an optimal quad tree QT based motion estimator for video compression It is optimal in the sense that for a given bit budget for encoding the displacement vector eld DVF and the QT segmentation the scheme nds a DVF and a QT segmentation which minimizes the energy of the resulting displaced frame di erence DFD We nd the optimal QT decomposition and the optimal DVF jointly using the Lagrangian multiplier method and a multilevel dynamic program The resulting DVF is spatially inhomogeneous since large blocks are used in areas with simple motion and small blocks in areas with complex motion We present results with the proposed QT based motion estimator which show that for the same DFD energy the proposed estimator uses about fewer bits than the commonly used block matching algorithm