Block Motion Estimation base on Statistical Image Feature for Video Sequences

K. Han, J. Lee, and Y. Jeong (Korea)


block motion estimation, image feature, motion vector


In this paper, we have proposed the block motion estimation algorithm based on statistical image feature for video sequences. First, the statistical feature of reference block is obtained, then applied to select the candidate starting points(SPs) in the regular starting points pattern(SPP) by comparing between the statistical feature of reference block and that of blocks which are spread over regular SPP. The final SPs are obtained by their mean absolute difference(MAD) value among the candidate SPs. Finally, the one of conventional fast search algorithm, such as BBGDS, DS, and three-step, generated the motion vector of reference block using the final SPs as its starting points. The experimental results showed that the starting points from final SPs were as close as to the global minimum as we expected..

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