ONE STEP SUB-PIXEL MOTION ESITMATION

A novel Lucas-Kanade sub-pixel motion estimation method is provided. The motion estimation algorithm enables the estimating of a motion vector with reduced computation cost while maintaining high sub-pixel accuracy. The novel algorithm consists of two processing stages. In the first stage, a conventional motion estimation method is applied to obtain the motion vector at integer-pixel level. In the second stage, the Lucas-Kanade algorithm is applied to improve the motion vector to sub-pixel accuracy based on gradient information. Experimental result shows that the proposed method reaches comparable PSNR performance as conventional ⅛-pel algorithm but with significant saving on computation cost.