基于相位估计的湍流降质图像盲复原

地基望远镜观测的空间目标图像受大气湍流的影响，其分辨率受到很大的限制。为了提高湍流降质图像的复原效果，提出一种改进的盲解卷积方法。首先，考虑观测图像受到高斯噪声和泊松噪声的干扰，推导出基于混合噪声模型的盲解卷积代价函数；然后，根据傅里叶光学原理，利用波前相位表示点扩展函数，将点扩展函数从像素值估计转换为参数估计；最后，通过参数化表示方式，将代价函数寻优从约束最优化问题转换为无约束最优化问题。模拟实验结果验证了本文模型与数值算法的有效性。

Phase Estimation based Blind Restoration for Atmospheric Turbulence Degraded Images

The resolution of space object images observed by ground-based telescope is greatly limited due to the influence of atmospheric turbulence. An improved blind deconvolution method is presented to enhance the performance of turbulence degraded images restoration. Firstly, a mixed noise model based blind deconvolution cost function is deduced under Gaussian and Poisson noise contamination of measurement. Then, point spread function (PSF) is described by wavefront phase aberrations in the pupil plane according to Fourier Optics theory. In this way, the estimation of PSF is generated from the wavefront phase parameterization instead of pixel domain value. Lastly, the cost function is converted from constrained optimization problem to non-constrained optimization problem by means of parameterization of object image and PSF. Experimental results show that the proposed method can recover high quality image from turbulence degraded images effectively.