The gray prediction search algorithm for block motion estimation

Due to the temporal and spatial correlation of the image sequence, the moti on vector of a block is highly related to the motion vectors of its adjacen t blocks in the same image frame. If we can obtain useful and enough inform ation from the adjacent motion vectors, the total number of search points u sed to find the motion vector of the block may be reduced significantly, Us ing that idea, an efficient gray prediction search (GPS) algorithm for bloc k motion estimation is proposed in this paper. Based on the gray system the ory, the GPS can determine the motion vectors of image blocks quickly and c orrectly. The experimental results show that the proposed algorithm perform s better than other search algorithms, such as 3SS, CS, PHODS, 4SS, BBGDS, SES, and PSA, in terms of six different measures: 1) average mean square er ror per pixel; 2) average peak signal-to-noise ratio; 3) average prediction errors per pixel; 4) average entropy of prediction errors; 5) average perc entage of unpredictable pels per frame; and 6) average search points per bl ock.