计算机工程Issue(4)：263-266,272,5.DOI:10.3969/j.issn.1000-3428.2015.04.050
基于改进粒子滤波算法的视频超分辨率重建
Video Super Resolution Reconstruction Based on Improved Particle Filtering Algorithm
摘要
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.关键词
超分辨率重建/粒子滤波/运动估计/匹配精度/无迹卡尔曼滤波/权值Key words
super resolution reconstruction/particle filtering/motion estimation/matching accuracy/Unscented Kalman Filtering( UKF)/weight分类
信息技术与安全科学引用本文复制引用
王爱侠,赵越..基于改进粒子滤波算法的视频超分辨率重建[J].计算机工程,2015,(4):263-266,272,5.基金项目
沈阳市科技局基金资助项目(F12277181)。 （F12277181）
