Real-Time Digital Image Stabilization Using Kalman Filters

Abstract

This paper presents a novel, real-time stabilization system that uses Kalman filters to remove short-term image fluctuations with retained smooth gross movements. The global camera motion is defined in terms of constant acceleration motion and constant velocity motion models, and Kalman filtering is employed to facilitate smooth operation. It is shown that the process noise variance has a direct effect on stabilization performance, and that it is possible to implement an efficient and robust stabilization system by adaptively changing the process noise variance value according to long-term camera motion dynamics.