Estimation of point spread function for long-exposure atmospheric turbulence-degraded images
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摘要: 大气湍流能明显降低光学系统的成像质量，距离目标越远，曝光时间越长，受大气扰动越严重，图像越模糊。利用大气湍流退化点扩散函数可以对模糊图像进行复原，但实际自然条件下的点扩散函数往往难以准确获得。结合课题研究背景，针对长曝光大气湍流退化图像复原提出了近似等腰三角形模型，通过该模型能得到准确的大气湍流点扩散函数，并采用维纳滤波获得清晰复原图像。实验表明该方法能够对大视场、远距离条件下获得的长曝光大气湍流退化自然图像估计出准确的点扩散函数，复原图像拥有较好的视觉效果，通过计算灰度平均梯度值和拉普拉斯梯度模两个客观评价标准，进一步证实了该算法的有效性。Abstract: The image quality will be remarkably declined by the atmosphere turbulence in the optical system. The farther the distance, the longer exposure time, the more serious atmospheric disturbance, then the more blurred images. It is able to restore the blurred images by utilizing the spread function of the atmosphere-turbulence degradation, but it is hard to obtain its accurate form of the natural atmosphere turbulence. According to the research background, in this paper an approximate isosceles triangle model was proposed to approach the accurate point spread function of the long-exposure atmospheric turbulence-degraded image, then a Wiener filter was designed to restore the blurred images. Numerical experiments show that the restore method is validated tentatively for the long-exposure atmospheric turbulence-degraded natural images with the large field of view and long distance. The effectiveness of the method is proven further by evaluating the restored images with the gray mean grads and the Laplacian sum standards.
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Key words:
- image restoration /
- point spread function /
- atmospheric turbulence /
- blurred images
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