Real-Time Image Stabilization Method Based on Optical Flow and Binary Point Feature Matching

The strap-down missile-borne image guidance system can be easily affected by the unwanted jitters of the motion of the camera, and the subsequent recognition and tracking functions are also influenced, thus severely affecting the navigation accuracy of the image guidance system. So, a real-time imag...

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Vydáno v:Electronics (Basel) Ročník 9; číslo 1; s. 198
Hlavní autoři: Deng, Zilong, Yang, Dongxiao, Zhang, Xiaohu, Dong, Yuguang, Liu, Chengbo, Shen, Qiang
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 01.01.2020
Témata:
Accuracy
Algorithms
Cameras
Field programmable gate arrays
Image quality
Image stabilizers
Kalman filters
Matching
Missile control
Optical flow (image analysis)
Real time
Signal processing
Stabilization
Unmanned aerial vehicles
ISSN:2079-9292, 2079-9292
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Shrnutí:The strap-down missile-borne image guidance system can be easily affected by the unwanted jitters of the motion of the camera, and the subsequent recognition and tracking functions are also influenced, thus severely affecting the navigation accuracy of the image guidance system. So, a real-time image stabilization technology is needed to help improve the image quality of the image guidance system. To satisfy the real-time and accuracy requirements of image stabilization in the strap-down missile-borne image guidance system, an image stabilization method based on optical flow and image matching with binary feature descriptors is proposed. The global motion of consecutive frames is estimated by the pyramid Lucas-Kanade (LK) optical flow algorithm, and the interval frames image matching based on fast retina keypoint (FREAK) algorithm is used to reduce the cumulative trajectory error. A Kalman filter is designed to smooth the trajectory, which is conducive to fitting to the main motion of the guidance system. Simulations have been carried out, and the results show that the proposed algorithm improves the accuracy and real-time performance simultaneously compared to the state-of-art algorithms.
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ISSN:2079-9292
2079-9292
DOI:10.3390/electronics9010198