A new successive elimination algorithm for fast block matching in motion estimation

In this paper, an algorithm, fine granularity successive elimination (FGSE), is proposed for fast optimal block matching in motion estimation. The FGSE is featured by providing a sequence of fine grained boundary levels in an aim to reject a checking candidate as early as possible, thus reducing computational load as much as possible. It is shown that the multilevel successive elimination algorithm (MSEA) is just a degraded case of FGSE with much coarser boundary levels. Comparative experiments are presented to verify the substantial speed-up gain of the proposed algorithm over the MSEA.