基于图像复原的衍射望远镜暗弱目标成像

Faint-Object Imaging of Diffractive Telescopes Based on Image Restoration

衍射望远镜受限于衍射效率,其成像质量受到非成像级次衍射光的影响。针对这一问题,提出了一种基于噪声自适应估计的块匹配三维协同滤波图像复原算法。首先通过主成分分析法估计出模糊图像的噪声方差,然后结合已知的点扩展函数,通过所提算法复原出清晰图像。搭建衍射望远镜成像系统并开展实验研究。数值仿真和实验结果表明,所提算法使得复原图像调制度相比退化图像提高了3.58倍,能有效改善复原图像的细节,利于暗弱目标成像。所提算法为衍射望远镜系统对暗弱目标进行高对比度成像提供了一种有效的路径。

A diffractive telescope is limited by its diffraction efficiency,and its imaging quality is easily affected by non-imaging order diffracted light.To resolve this problem,this study proposes a block-matching and 3D collaborative filtering image restoration algorithm based on adaptive noise estimation.First,the noise variance of a blurred image is estimated using principal component analysis,which is then combined with the known point-spread function,and the clear image is restored using the proposed algorithm.The proposed algorithm is tested in an imaging system built from diffraction telescopes.Results of numerical simulation and measurement experiment show that the proposed algorithm can improve the modulation degree of restored images by 3.58 times compared to that of raw images and can effectively improve the details of restored images and facilitate the faint-object imaging.Therefore,the proposed algorithm provides an effective way for high-contrast imaging of faint objects using diffraction telescope systems.