A novel block matching algorithm based on successive refinement using motion correlation is presented, which estimates more accurate forward and backward motion vectors for interpolative prediction as well as forward and backward predictions in bidirectionally predictive-coded pictures. Experimental results show that this algorithm achieves good performance in PSNR and subjective quality with low computational complexity.
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