An adaptive low-complexity global motion estimation algorithm
One important recent application of image registration has been in the estimation of global motion parameters for object-based video coding. A limitation of current global motion estimation approaches is the additional complexity of the gradient-descent optimization that is typically required to calculate the optimal set of global motion parameters. In this paper we propose a new low-complexity algorithm for global motion estimation. The complexity of the proposed algorithm is reduced by performing the majority of the operations in the gradient-descent optimization using logic operations rather than full-precision arithmetic operations. This use of logic operations means that the algorithm can be implemented much more easily in hardware platforms such as field programmable gate arrays (FPGAs). Experimental results show that the execution time for software implementations of the new algorithm is reduced by a factor of almost four when compared to existing fast implementations without any significant loss in registration accuracy.