Generalized partial distortion search algorithm for block-matching motion estimation

Abstract

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