TY - GEN
T1 - Real-time Image Stabilization Method Based on Low Altitude Fixed Wing UAV
AU - Li, Jiangtao
AU - Yang, Yu
AU - Li, Jie
AU - Xu, Huaxing
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - The existing electronic image stabilization techniques are mainly based on feature point matching, which is difficult to solve the problem that the low altitude fixed wing UAV Using strapdown camera platform collects fewer image feature points. To solve this problem, a real-time image stabilization method based on attitude angle information is proposed in this paper. Firstly, the attitude angle information collected by IMU and the image information collected by visual sensors are aligned in real time. Then, the attitude angles of pitch, roll and yaw are filtered differently, and the corresponding basic matrix is calculated according to the processed angular information. Finally, affine transformation is used to stabilize the original image sequence, and a smooth image sequence is obtained. The experimental results show that the peak-signal-to-noise ratio of the image sequence after image stabilization is increased by more than 5%. The algorithm is suitable for low altitude fixed wing UAV platform. For images with less feature point information, it can also eliminate jitters. At the same time, it has strong robustness to large maneuvers of aircraft.
AB - The existing electronic image stabilization techniques are mainly based on feature point matching, which is difficult to solve the problem that the low altitude fixed wing UAV Using strapdown camera platform collects fewer image feature points. To solve this problem, a real-time image stabilization method based on attitude angle information is proposed in this paper. Firstly, the attitude angle information collected by IMU and the image information collected by visual sensors are aligned in real time. Then, the attitude angles of pitch, roll and yaw are filtered differently, and the corresponding basic matrix is calculated according to the processed angular information. Finally, affine transformation is used to stabilize the original image sequence, and a smooth image sequence is obtained. The experimental results show that the peak-signal-to-noise ratio of the image sequence after image stabilization is increased by more than 5%. The algorithm is suitable for low altitude fixed wing UAV platform. For images with less feature point information, it can also eliminate jitters. At the same time, it has strong robustness to large maneuvers of aircraft.
KW - attitude angle
KW - fixed wing UAV
KW - image stabilization
KW - strapdown camera
UR - http://www.scopus.com/inward/record.url?scp=85141935877&partnerID=8YFLogxK
U2 - 10.1109/ICSESS54813.2022.9930217
DO - 10.1109/ICSESS54813.2022.9930217
M3 - Conference contribution
AN - SCOPUS:85141935877
T3 - Proceedings of the IEEE International Conference on Software Engineering and Service Sciences, ICSESS
SP - 314
EP - 318
BT - Proceedings of 2022 IEEE 13th International Conference on Software Engineering and Service Science, ICSESS 2022
A2 - Wenzheng, Li
PB - IEEE Computer Society
T2 - 13th IEEE International Conference on Software Engineering and Service Science, ICSESS 2022
Y2 - 21 October 2022 through 23 October 2022
ER -