Fast exhaustive-search motion estimation based on accelerated multilevel successive elimination algorithm with multiple passes

Block-based motion estimation is widely employed by many video compression systems to capture temporal correlations of the data. While the exhaustive full search block matching method can find globally optimal candidates without any loss in the matching accuracy, high computational complexity of this method limits its practical applications. Lossless block matching algorithms based on successive candidate elimination were found to be effective in reducing the complexity of the full search method. In this paper, we introduce a new breadth-first method with multiple passes to speedup the depth-first multi-level successive elimination algorithm (MSEA), by exploiting the correlations between matching metrics of different levels. Simulations showed that the proposed lossless block-matching method based on MSEA reduced the running times of the conventional full search method by about 17.5 times and 9.5 times on average for QCIF and CIF sequences, respectively, representing about 11% and 34% improvements over the MSEA.