Technology of Graphic & Image
|
3121-3123

Improved least-squares and Kalman filtering real-time image stabilization

Gu Le
Chen Zhiyun
School of Data Science & Engineering, East China Normal University, Shanghai 200062, China

Abstract

Video taken in the case of drones and vehicles traveling would be affected by the outside world causing video jitter. This paper proposed to use FAST to obtain the position information of feature points by comparing with the existing electronic image stabilization technology. Then it obtained the position information of the reference frame feature point in the current frame by the optical flow method combined with NCC matching. Based on this, it combined with RANSAC algorithm to eliminate the wrong matching feature points pairs. In order to improve the accuracy of motion vector estimation, this paper applied weighted least squares method to obtain the rigid transformation matrix between adjacent frames. The video was smoothed by Kalman filter to get the motion vector and compensated, and finally got a stable video in real time. The experimental table shows that it improves the fidelity of the inter-frame transform after video sequence stabilization, and achieves the real-time processing speed.

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.05.0355
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 10
Section: Technology of Graphic & Image
Pages: 3121-3123
Serial Number: 1001-3695(2019)10-053-3121-03

Publish History

[2019-10-05] Printed Article

Cite This Article

谷乐, 陈志云. 加权最小二乘法与卡尔曼滤波实时稳像技术 [J]. 计算机应用研究, 2019, 36 (10): 3121-3123. (Gu Le, Chen Zhiyun. Improved least-squares and Kalman filtering real-time image stabilization [J]. Application Research of Computers, 2019, 36 (10): 3121-3123. )

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  • Application Research of Computers Monthly Journal
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Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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