A subsampling-predictor associated approach for fast global motion estimation

Abstract

Global Motion Estimation (GME) has many important roles in numerous applications, such as video compression, image stabilization, video-object segmentation, and etc. One well-known GME method is the gradient-based technique. This method uses optimization techniques, like the Levenberg–Marquardt algorithm, to minimize estimation error. Such algorithms require an initial value for the initializing step. In this paper, we propose a simple and reliable GME structure with a new predictor. This structure uses a three-step search and a predictor for the initializing step. It is also incorporated with a fast GME method that uses pixel subsampling. This incorporation reduces the computational complexity of GME without a significant loss of accuracy. This structure has less computational complexity and similar accuracy versus common methods.