Generalized partial distortion search algorithm for fast block motion estimation

The quality against speed control for real-time video applications, such as the speed-oriented video conferencing or the high quality video entertainment, usually absents from many traditional fast block motion estimators. In this paper, a novel block-matching algorithm for fast motion estimation named generalized partial distortion search algorithm (GPDS) is proposed. It uses halfway-stop technique with progressive partial distortion (PPD) to increase the chance of early rejection of impossible. We candidate motion vectors at very early stages. Simulations on PPD show that 28 to 38 times computational reduction with only 0.45-0.50dB PSNR performance degradation as compared, to full search algorithm. In addition, a new normalized partial distortion comparison method is also proposed for enabling the control of searching speed against the prediction quality by a speedup factor k. This method also generalizes the conventional partial distortion search algorithm when k is equal to 1, and the generalized partial distortion search algorithm (NPDS) when k is equal to infinity. Experimental results show that GPDS with use of PPD could provide PSNR performance very close to full search algorithm and NPDS with 7 to 17 times and 22 to 33 times speedup, respectively, as compared to full search algorithm.