Fast motion estimation algorithm using dual bit-plane matching criteria

Abstract

The constrained two-bit transform (C2BT) is recently proposed for low complexity motion estimation (ME) to reduce the high computational complexity of the typical two-bit transform (2BT) while maintaining the ME accuracy. And the bit-inverted Gray-coded bit-plane matching (BGCBPM) is also proposed to enhance the ME accuracy. In this paper, we propose a fast ME algorithm exploiting these two bit-plane matching (BPM) criteria. Using the low complexity image transformations of typical images into bit-planes and their corresponding matching criteria and another hybrid matching criterion, we can efficiently determine multiple candidate motion vectors and increase the ME accuracy substantially. Experimental results show that the peak-to-peak signal-to-noise ratio (PSNR) difference between the proposed algorithm and the typical sum of absolute differences (SAD) based full search algorithm is only 0.03 dB on average with negligible computational complexity increase.