A new hybrid block-matching motion estimation algorithm

A fast and efficient hybrid block-matching motion estimation algorithm is proposed in this paper. The fact that motion characteristics are relatively stable in a GOP (group of pictures) is utilized to reduce the computation burden without quality degradation. For P-frames, a multi-resolution block-matching algorithm is used. At the coarsest level, edge information is used to reduce searching positions before an exhaustive search. At the finer levels, only the several candidates chosen at the upper level are verified. For B-frames, MAE (mean absolute error) is used not only for the matching criteria, but also for classifying the macroblocks with the motion information extracted from P-frames. Concurrently, the search window size is adjusted using the contribution of different motion range to the improvement of the picture quality with motion compensation. When the decoded I-frame and P-frames are used as the reference, experimental results show that reconstructed digital frames have even better quality than the full search algorithm in terms of PSNR, under MPEG-1 coding environment.