Multi step motion estimation algorithm
Deepak Jayaswal, Mukesh A. Zaveri, R. E. Chaudhari · 2010
We propose a multi step motion estimation algorithm (MSME) that encompasses techniques such as motion vector prediction through initial search, refinement of motion vector to locate true motion vector and early termination criteria that suits to all type of video characteristic. This approach allows us to exploit random distribution of motion vector in successive video frames from which the initial candidate predictors are derived. The derived predictors are the most probable points in search window, which will assure that, the motion vectors in the vicinity of center point and at the edge of the search window does not miss out, as it does for earlier algorithms like Three step search(TSS), Four step search(FSS), Diamond(DS), etc and refinement stage used in the algorithm will allow us to extract true motion vector so that the picture quality is as good as Full search(FS) which is the optimal algorithm. The novelty of the proposed MSME algorithm is that the search pattern derived is not static but can dynamically shrink or enlarge to account for small and large motion. Fixed threshold used improves speed without sacrificing the quality of video. The Simulation result shows that our proposed algorithm outperforms all sub-optimal algorithms in terms of quality and speed up performance and in many cases PSNR of proposed algorithm is comparable to Full Search.