24 November 2014 Electronic image stabilization algorithm based on PCA-SIFT feature matching and self-adaptive high-pass filtering
Author Affiliations +
Proceedings Volume 9301, International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition; 93011H (2014) https://doi.org/10.1117/12.2072051
Event: International Symposium on Optoelectronic Technology and Application 2014, 2014, Beijing, China
Abstract
As the electronic image stabilization (EIS) algorithm based on SIFT feature matching has the problem of complex computation and time consuming, a modified EIS algorithm based on PCA-SIFT feature matching and self-adaptive high-pass filtering is proposed in this paper. Firstly, feature points are extracted by using PCA-SIFT algorithm in reference frame and current frame. And the corresponding points are matched between these two images. Then the Random Sample Consensus (RANSAC) algorithm is used to eliminate the error matching pairs to reduce the influence of local motion in the scene and improve the estimation accuracy of global motion parameters. Finally, the random dithering parameters obtained by self-adaptive high-pass filtering are used to compensate the current frames. And the size of filter is adjusted automatically according to dithering frequency to prevent the overstabilization or understabilization. Experimental results show that the algorithm proposed in this paper can effectively remove vectors caused by random dithering and obtain a stable video.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Min Li, Min Li, BingJian Wang, BingJian Wang, Xiang Yi, Xiang Yi, Jingya Hao, Jingya Hao, Feihong Wu, Feihong Wu, Hanlin Qin, Hanlin Qin, } "Electronic image stabilization algorithm based on PCA-SIFT feature matching and self-adaptive high-pass filtering", Proc. SPIE 9301, International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93011H (24 November 2014); doi: 10.1117/12.2072051; https://doi.org/10.1117/12.2072051
PROCEEDINGS
7 PAGES


SHARE
Back to Top