Motion estimation using dynamic programming with selective path search

A novel dynamic programming-based motion estimation algorithm is presented in this paper. During matching cost calculation, the algorithm selectively keeps the cost values for the best N candidates only. The required memory space is therefore considerably reduced. In addition, a new path searching approach is applied. When searching for the optimal path from pixel p, the algorithm considers both the nearby candidates and the best N candidates at pixel p-l. As a result, better estimations can be produced around motion boundaries. The experimental results show that the motions estimated through considering all the candidates are only slightly better than those estimated through selectively considering a small number of candidates, even though the former approach requires significantly more computational time and memory space.