Partial Distortion Search Algorithm Using Predictive Search Area for Fast Full-Search Motion Estimation

摘要

In this letter, a fast partial distortion search algorithm for motion estimation is presented. The proposed method is based on the observation that when normalized partial distortion is utilized, the false rejection of impossible candidates most likely occurs within a small area adjacently located near the true motion vector. Our objective is to enhance the prediction accuracy in this small predictive search area and further save computations outside this area. Experimental results show that the proposed algorithm achieves an average 42 times speedup ratio as compared to full-search algorithm with only 0.05 dB degradation in PSNR performance.