Low complexity weighted two-bit transforms based multiple candidates motion estimation exploiting the redundant computations

Abstract

A low complexity weighted two-bit transforms (2BT) based multiple candidates motion estimation algorithm is proposed in this paper. By exploiting almost the identical operations in two different matching error criteria, we can efficiently determine two best motion vectors according to the respective matching criteria and can enhance the overall motion estimation accuracy. Experimental results show that the proposed algorithm achieves peak-to-peak signal-to-noise ratio (PSNR) gains about 0.47dB on average compared with the conventional 2BT-based motion estimation.