适于微小型飞行器平台的稳像算法

为解决微小型飞行器由于机械振动、气流扰动等原因引起的图像高频抖动,设计了一种适用于该平台的稳像算法。采用基于生物视觉的匹配方法估计帧间运动矢量,建立了图像参数传递的数学模型;结合微小型飞行器的运动特点,提出了带约束的交互式多模型卡尔曼滤波方法(CIMMKF),针对绝对帧位移曲线和旋转角度滤波,引入硬约束条件减小模型不准确性产生的误差,再通过软约束平滑硬约束带来的局部跳变求得图像合适的校正量。最后,给出了一种新颖的微小型飞行器平台稳像算法性能的评估方法。实验结果表明,该稳像算法能够适应飞行器多种状态的交替改变,有效减小滤波延迟,去除高频抖动,保留主动运动,使稳定后图像质量满足观察要求,具有图像信息保留程度高、速度快的特点,尤其适用于微小型飞行器实时视频稳定。

Video stabilization for micro air vehicle platform

A new video stabilization technology for micro air vehicles was proposed to solve the problem of high frequency image jitter caused by mechanical vibration and atmospheric turbulence.Motion vectors between frames were estimated by biological vision based feature matching algorithm.And then,a mathematical model of image transform parameters passing was proposed.In motion compensation phase,absolute displacement curves and rotation vectors were filtered by constraint interacting multiple model Kalman filter(CIMMKF) with hard constraint and soft constraint.Hard constraint was used to reduce errors induced by model inaccurateness,while soft constraint was used to smooth local skips caused by hard constraint.A novel method was proposed to evaluate the performance of video stabilization algorithm for micro air vehicle platform.Experiment results show that this video stabilization method can adapt to micro air vehicles′ motion state variation,preserve intended motion,reduce filter delay effectively,and eliminate image high frequency jitter.The quality of stabilized videos can be satisfied by ground operators.This method is real-time and effective,especially appliable to micro air vehicle video stabilization.