基于估计点扩展函数值的湍流退化图像复原

提出了一种直接从湍流退化图像中估计湍流点扩展函数值的方法.本方法不再利用自 然或人工向导星图像来测定点扩展函数,而是直接利用两帧连续短曝光湍流退化图像作为输入， 在空域中对其进行适当的延拓,在频域中建立和选择关于湍流点扩展函数离散值的一系列计算 方程.为了克服噪声的干扰,在点扩展函数的非负性和空间光滑性的约束条件下,将点扩展函数 的计算问题转化为优化估计问题,通过极小化准则函数估计点扩展函数值,进而恢复退化图像. 实验结果表明,本文方法十分有效,复原效果好.

Restoring Turbulence-Degraded Images Based on Estimation of Turbulence Point Spread Function Values

A new method is proposed for estimating the PSF(point spread function) values of turbulence from turbulence degraded images. Instead of previously used natural or artificial guide star images to measure the PSF, two consecutive frames of short exposure turbulence degraded images are used directly as the input. Appropriate extension are made for the images in the spatial domain and a series of equations for calculating the PSF values are developed and chosen in the frequency domain. In order to overcome the interference of noise, the PSF calculation is transformed into the optimization estimation under the constraints of the PSF being non negative and spatial smoothing. The values of the PSF are estimated by minimization criteria function and then the degraded images are restored. Experimental results show that the proposed method is highly effective with good performance.