无人机运动模糊图像复原技术

Research on UAV Motion-blurred Image Restoration

在无人机飞行过程中,由于成像系统会受到相对运动、姿态变化、机械振动、镜头离焦以及大气湍流效应等影响,造成获取的图像产生退化。由于图像复原问题通常情况下是病态的,综合利用了无人机运动的先验信息,提出了不同运动模糊情况下点扩散函数的估计方法,采用维纳滤波复原算法估计图像,给出了适用于无人机成像制导系统的图像复原方案。最后经仿真实验证明,该算法图像复原效果好,计算量小,抗噪声鲁棒性强,有较大的工程应用价值。

The image is degraded as many factors influence the imaging system of UAV in flying. These factors are relative motion, attitude disturbance, forced vibration, lens defocusing, atmospheric turbulence and so on. Image restoration problem is usually ill-conditioned when noises and these factors exist in the inverse problem. A method was presented to estimate point spread function based on using UAV prior motion and analysis of different motion-blurred. Wiener filter algorithm was adopted to estimate nature image. And the image restoration project was provided with UAV image guidance system. Experimental results show that the proposed algorithm can restore image effectively and improve performances of computation and noise adaptivity. The image restoration project can be efficiently employed in engineering.