Abstract: In view of serious jitter of aerial airborne imaging,different accuracies of obtained matching points in aerial video stabilization,and requirements of fast and precise aerial image stabilization technology,an image stabilization algorithm was proposed combining affine invariant constraint and Extend Kalman Filter (EKF) adaptive filter.Firstly,corners are detected from reference frame as feature points,the locally stable points are selected by the Harris detector.Then Delaunay triangulation is used to find initial matching,and the most accurate matching points which best satisfy the affine invariant constraint are filtered.Finally,EKF motion filter method is used to estimate and correct the statistical property of noise,so jitter of the camera can be removed but scanning motion can be retained simultaneously.As to a large number of simulation experiment of aerial images with a resolution of 640 pixel ×480 pixel,accurate model can be estimated by affine invariant constraints,the rapid motion compensation method takes 5.054 ms in the process of compensation,and saves for 69.5% than traditional motion compensation method.The experimental results illustrate that the proposed algorithm can stabilize the inter-frame jitter and track the real scene effectively.

Key words: Aerial video,Electronic image stabilization,Feature point,Affine invariant constraint,EKF motion filter