A fast multi-pattern motion estimation algorithm based on the nature of error surfaces
Humaira Nisar, Tae‐Sun Choi · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2008
In this paper we propose an algorithm for reducing the complexity of motion estimation module in standard video compression applications. In several video coding standards, motion estimation becomes the most time consuming sub system such as H.264/AVC. Therefore recently research focuses on the development of novel algorithms to save computations with minimal effects over the video distortion. Since real world video sequences usually exhibit a wide range of motion content, from uniform to random, adaptive algorithms have revealed as the most robust general purpose solutions. In this paper a simple, computationally efficient and robust scheme for multi pattern motion estimation algorithm based on the nature of error surfaces has been proposed. A combination of spatial and temporal predictors has been used for multiple initial search center prediction, determination of magnitude of motion and search pattern selection. The multiple initial predictors help to identify the absolute zero motion blocks and true location of global minimum based on the characteristic of error surfaces. Hence the final predictive search center selected is closer to the global minimum. This results in smaller number of search steps to reach minimum location and increases the computation speed. Further computational speed up has been obtained by considering half stop technique and threshold for minimum distortion point. The computational complexity of the proposed algorithm is drastically decreased (average speedup ~ 43%) whereas the image quality measured in terms of PSNR (~.20 dB loss with respect to Full Search) also shows results close to Full Search algorithm.