A new efficient adaptive rood pattern search motion estimation algorithm

Motion estimation plays a crucial role in video coding; the Adaptive Rood Pattern Search (ARPS) algorithm is a well known fast motion estimation algorithm. However, ARPS has certain limitations, such as the lack of an accurate starting motion vector, a fixed Zero Motion Prejudgment (ZMP) threshold unsuitable for fast motion video sequences, and the repetitive use of a Unit Rood Pattern (URP) resulting in increased computational complexity. To address these issues, this paper proposes a novel algorithm called Efficient Adaptive Rood Pattern Search (EARPS). EARPS overcomes these limitations by employing the Full Search algorithm to obtain optimal motion vectors for the first column in each frame, adopting a dynamic ZMP threshold that adapts to varying motion speeds in video sequences and utilizing URP only once to reduce computational overhead. The performance of the new proposed EARPS algorithm is evaluated and compared with that of ARPS algorithm using various video sequences with different motion speeds. The number of searching points and Peak Signal-to-Noise Ratio (PSNR) are used to quantify computing complexity and accuracy. The experimental findings show that EARPS surpasses ARPS in terms of computing complexity while retaining a decent degree of PSNR accuracy. The proposed EARPS motion estimation algorithm main contribution is to achieve high speed with reasonable accuracy, regardless of the type of motion speed in the video frames. The EARPS algorithm offers a substantial advancement over ARPS, delivering a more efficient motion estimation method with broader applicability in video processing. It represents a significant contribution to the development of effective motion estimation algorithms.