Electronic image stabilization algorithm based on filtering and curve fitting

Abstract

To solve the problem that now there is no method that can remove high frequency noise and low frequency noise simultaneously, this paper proposed a new method combining filtering and curve fitting, which can solve the high frequency noise and low frequency noise problem simultaneously. Firstly the offset between frames was estimated fast using bit-plane matching algorithm in this new method. Secondly the inter-frame offset was cumulated to get the global motion vector relative to the reference frame. And the global motion vector was filtered with Kalman filter to remove the high frequency noise. Finally curve fitting was executed on the global motion vector that has been filtered with Kalman filter to remove the low frequency noise. At last the steady intentional trajectory was got. The experimental results show that the method can effectively remove the high frequency and low frequency noise simultaneously, and video stabilization effect is good.