基于噪声特性的大气湍流退化图像多帧盲反卷积复原

由于大气湍流和噪声的影响,造成观测目标图像的退化.为了目标的精确观测,根据噪声特性,结合符合物理意义的约束条件,提出了新的大气湍流图像盲反卷积复原最小化模型,并以共轭梯度数值优化方法交替迭代求解,复原观测目标图像.为验证提出的算法的有效性,在计算机上模拟参数为望远镜口径为2.0 m,大气相干长度为0.1 m,图像信噪比为10 dB的大气湍流退化和噪声污染的图像,以提出的盲反卷积复原方法复原,实验结果表明,提出的盲反卷积复原算法避免了传统的盲反卷积复原算法的缺陷,有效地克服大气湍流和噪声的影响,复原出了清晰的观测目标图像.该图像盲反卷积复原方法的研究,对地基望远镜的观测有重要的基础性作用.

Multiframe Blind Deconvolution Restoration of Atmospheric Turbulence-Degraded Images Based on Noise Characteristic

Due to influence of atmospheric turbulence and noise contaminated, the object images are always blurred. To observe object in high resolution, combining characteristic of noise, with physical constraint, a novel method of atmospheric turbulence-degraded images blind deconvolution restoration minimization model is proposed. Alternating minimization algorithm based on conjugate gradient method is applied for image restoration. Blurred images by atmospheric turbulence with atmospheric coherent length of 0.1 m for 2 m-diameter telescope and noise with signal-to-noise ratio of 10 dB are restored by the proposed method. The result demonstrates that the drawback of the traditional blind convolution method has been overcome, the influence of atmospheric turbulence and noise has been eliminated and clear observation object images have been restored. The study of blind deconvolution restoration technology purposed is meaningful for ground-based telescope in astronomical observation.