Abstract: In the super resolution reconstruction,a key step is the video motion estimation. Compared with other
methods,matching algorithm based on features of video has higher robustness. However,the accuracy of this kind of methods is affected by the position and selection of feature points. To overcome this problem,this paper introduces the particle filtering into the motion estimation to reduce the matching error. The main disadvantage of the particle filtering is particle degeneracy. In this paper,an extended Kalman filtering is used to general the proposal distribution,and an Unscented Kalman Filtering(UKF) is used to refine particles. Experimental results show that,compared with other eight classic filtering algorithms, the proposed algorithm has much better performance, and for the super resolution reconstruction issue,the proposed algorithm can estimate the motion more accurately.
super resolution reconstruction,