Generalized partial distortion search algorithm for fast block motion estimation
Quality versus speed control for real-time video applications, such as speed-oriented videoconferencing or high quality video entertainment, usually is 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 also proposed for enabling control of searching speed against 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 normalized 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 the full search algorithm and NPDS with 7 to 17 times and 22 to 33 times speedup, respectively, as compared to the full search algorithm.