Gradient-Based Algorithms for Block-Oriented MAP Estimation of Motion and Application to Motion-Compensated Temporal Interpolation

Motion estimation and motion-compensated filtering am key elements in most advanced television systems. A study of block-oriented motion estimation algorithms is presented, and their application to motion-compensated temporal interpolation Is described, In out approach, (he motion field within each block is described by a function of a few parameters that can represent typical local motion vector fields. A probabilistic formulation Is then used to develop maximum likelihood (ML) and maximum a posteriori probability (MAP) estimation criteria. The MAP criterion takes into account the dependence of the motion fields in adjacent blocks. A procedure. for minimizing the resulting objective function based on the Gauss-Newton algorithm Is presented. The use of multiresolution techniques, essential for satisfactory performam, Is discussed. Experimental results evaluating the algorithms for the task of motion-compensated temporal Interpolation an presented. The relative complexity of the algorithms Is also discussed.