Research On Video-based Anti-jitter Method Of Imaging

Electronic image stabilization is a new technology to stabilize image sequences with computer image processing. It has a lot of advantages, such as high image stabilizing precision, compact size, lightweight, low power consumption and reasonable price. It has been widely used in military and civil fields. The key technologies of electronic image stabilization are global motion estimation and motion compensation. The research on improving efficiency and accuracy of global motion estimation and distinguishing camera scan from dithering to realize real-time and accurate compensation becomes a hot topic at present.Dithering of the video sequence includes translation, rotation and zoom of complex movements. Traditional corner extraction method is easy to generate a lot of corners focused on moving objects in the scene. And the speed is low because of complex matching steps. If we use all corners to calculate the global motion parameters directly, it will result in accuracy problem because of the existence of local outliers and error matched points. So this paper presents an electronic image stabilization algorithm based on image partition and corner matching. First of all, the corners are extracted evenly from the reference frame by using Harris corner detection operator and then each feature window is built to find the corresponding corners in the current frame. At the same time in order to ensure accuracy and speed of estimation, by matching validation technique, we can solve the error matched problem arising in the course of matching and reduce the adverse effects of invalid corner pairs. Next, the global motion parameters can be obtained through Levenberg-Marquardt iterative method. Finally, the Kalman filter is applied to smooth the motion vectors to obtain the dithering vector and the image mosaic is used to compensate each current frame in order to improve the stability and integrity of the output video.The experimental results show that the pre-processing and iterative steps to the corners of the algorithm ensure the overall of the motion detection with high precision. The compensation results can follow scanning movement of the camera system in real time. At last the stable and integral output video sequence can be obtained.