A Fast Motion Estimation Algorithm Using Spatial Correlation of Motion Vectors

In this paper, a fast motion estimation algorithm based on the spatial correlation of motion vectors is presented. The current block is classified as correlation-type block or independent-type block in the proposed algorithm, by utilizing the correlation information of three neighboring motion vectors. In order to reduce the computational complexity of motion estimation and maintain the performance of motion compensation, different search strategies are applied for the two types of block. Experimental results show that the proposed algorithm can reduce the computational complexity by about 49% compared with the Hexagon-Based Search (HEXBS) algorithm, while Peak Signal-to-Noise Ratio (PSNR) loss is only 0.15 dB in average. Compared to the Diamond Search (DS) algorithm, the computational reduction is about 60%, while the performance loss is only 0.24 dB in average.