On Adaptive Pattern Selection for Block Motion Estimation Algorithms

Pattern-based block motion estimation (PBME) algorithm has been widely adopted in digital video coding systems. Due to the large characteristics variations among video sequences, adaptive PBME algorithms that switch search patterns have been proposed. However, most adaptive search algorithms are heuristically designed based on the experimental data. In this paper, we like to construct an analytical model and explore the problem systematically. Also, we propose an adaptive genetic pattern search algorithm (AGPS). Simulations show that the proposed AGPS in average outperforms the existing popular search algorithms quite significantly in speed, while the peak signal noise ratio (PSNR) quality is maintained at the same level.