A New Genetic Search Algorithm for Motion Estimation

摘要

Motion estimation is essential for many inter frame video coding techniques, block- matching algorithms, such as FSA and TSS, have been widely used for motion estimation. The easiest implementation is the FSA, which evaluates all the blocks in the search window and has the highest computational cost. Therefore, many fast search algorithm including TSS, have been proposed to reduce the computational complexity, but most of them are based on the assumption that there should be only one optimal solution in the search window, however, in normal cases, there always exist multitudinous local optima, so they will miss the global optima, but get a suboptimal solution. In this paper, we propose a modified genetic search algorithm for motion estimation, the result shows that the method not only solve the problem of being trapped to local optima, but also have speed close to that of TSS.