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Wide Range and Dynamic Video Image Stabilization Applied in UAV Aerial Photographing

机译:宽范围和动态视频图像稳定应用于UAV航空拍摄

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In the process of aerial photographing, due to the wide range of complex scene conditions such as air flow changes and the influence of light and atmosphere, which lead to the large dynamic instability phenomenon such as mechanical vibration and even violent shaking when the camera carrier moves, this paper proposes a new video stabilization algorithm for the wide range and large dynamic state. Firstly, the feature points of reference frame are extracted by GFTT algorithm, and the motion vector between frames is obtained by using sparse optical flow method to find matching feature points in the current frame of continuous video image. Secondly, on the basis of traditional Kalman filter, a hybrid filter composed of Kalman filter and Gauss discrete filter is used to smooth the motion of each frame image. Finally, a stable video sequence is obtained by motion compensation. The experimental results show that the MSE parameters of this algorithm are 21.4% lower than those of the traditional Kalman filter based image stabilization algorithm, which can meet the requirements of wide range and dynamic video image stabilization.
机译:在空中拍摄过程中,由于空气流动变化的宽范围的复杂场景条件和光线和大气的影响,这导致了大量的动态不稳定现象,例如当相机载体移动时甚至剧烈摇动,本文提出了一种新的视频稳定算法,用于广泛和大的动态状态。首先,通过GFTT算法提取参考帧的特征点,并且通过使用稀疏光学流方法来获得帧之间的运动矢量来找到连续视频图像的当前帧中的匹配特征点。其次,在传统的卡尔曼滤波器的基础上,使用由卡尔曼滤波器和高斯分立滤波器组成的混合滤波器来平滑每个帧图像的运动。最后,通过运动补偿获得稳定的视频序列。实验结果表明,该算法的MSE参数低于传统卡尔曼滤波器的图像稳定算法的21.4%,这可以满足广泛范围和动态视频图像稳定的要求。

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