A novel block matching algorithm based on successive refinement using motion correlation is presented, which estimates more accurate forward and back-ward 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.