Adaptive Fast Full Search Algorithm using Partitioned Region and Optimized Search Order

In this paper, an adaptive fast full search algorithm is proposed. The fast full search algorithm only reduces the complexity of the block matching algorithm used for motion estimation of video coding. Since the spiral search method used in conventional algorithms starts searching at the center of the search range and then moves the candidate position to estimate motion pixel by pixel, it is best for slow motion pictures. The spiral search method usually has better performance than a full search using the raster scan search method. However, the proposed algorithm is best for sequences which have numerous rapid motions. In the first of two proposed stages, using a predicted motion vector, we determine the region search order based on gradient distances among all regions after partitioning the search range. In the second stage, by means of region order, the matching error of all candidate positions is calculated in an optimized search order which is derived from the local image complexity of the current macro-block to search. The proposed algorithm, based on a multilevel successive elimination algorithm, reduces the complexity of motion estimation up to 96.6% on average, compared with the conventional full search algorithm without any loss of image.