Energy function behavior in optimization based image sequence stabilization in presence of moving objects

Abstract

In this paper, we address the registration of two images as an optimization problem within indicated bounds. Our contribution is to identify such situations where the optimum value represents the real transformation parameters between the two images. Consider for example Mean Square Error (MSE) as the energy function: Ideally, a minimum in MSE corresponds to transformation parameters that represent the real transformation between two images. In this paper we demonstrate in which situations the optimum value represents the real transformation parameters between the two images. To quantify the amount of disturbances allowed, these disturbances are simulated for two separate cases: moving objects and illumination variation. The results of the simulation demonstrate the robustness of stabilizing image sequences by means of MSE optimization. Indeed, it is shown that even a large amount of disturbances will not cause the optimization method to fail to find the real solution. Fortunately, the maximal amount of disturbances allowed is larger than the amount of signal disturbances that is typically met in practice.