Adaptive Search Range Motion Estimation Using Neighboring MVDs

This paper presents a new fast motion estimation method where search ranges are determined by the probabilities of motion vector differences (MVDs). The MVDs' distribution is investigated and its parameter is estimated by the maximum likelihood estimator. With the estimated distribution, the search ranges is efficiently restricted by a prefixed probability for MVDs. Experimental results show that the performance of the proposed method is very similar to that of the full search algorithm in PSNR but it enables significant reduction in the computational complexity.