Abstract
This paper describes a new fast block matching algorithm alleviating the local minimum problem based on successive refinement of motion vector candidates. The proposed algorithm employs a layered structure. At the first layer, a full search is performed with an approximated matching criterion to obtain a candidate set for the motion vector within a short computation time. In each successive searching process, the matching criterion becomes refined and the search is performed with it only for the candidate set obtained at the preceding layer to refine the candidates. By repeating this process, at the last layer, only a single motion vector can be selected from a few candidates using the conventional MAD (Mean Absolute Difference) criterion without approximation. Since a full search is performed with a coarse matching criterion at the first layer, the proposed algorithm can diminish the local minimum problem in the existing fast search algorithms and also reduce the computation time drastically compared with a brute force search.
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