Ghost imaging (GI) can nonlocally image objects by exploiting the fluctuation characteristics of light fields, where the spatial resolution is determined by the normalized second-order correlation function $g^{(2)}$. However, the spatial shift-invariant property of $g^{(2)}$ is distorted when the number of samples is limited, which hinders the deconvolution methods from improving the spatial resolution of GI. In this paper, based on prior imaging systems, we propose a preconditioned deconvolution method to improve the imaging resolution of GI by refining the mutual coherence of a sampling matrix in GI. Our theoretical analysis shows that the preconditioned deconvolution method actually extends the deconvolution technique to GI and regresses into the classical deconvolution technique for the conventional imaging system. The imaging resolution of GI after preconditioning is restricted to the detection noise. Both simulation and experimental results show that the spatial resolution of the reconstructed image is obviously enhanced by using the preconditioned deconvolution method. In the experiment, 1.4-fold resolution enhancement over Rayleigh criterion is achieved via the preconditioned deconvolution. Our results extend the deconvolution technique that is only applicable to spatial shift-invariant imaging systems to all linear imaging systems, and will promote their applications in biological imaging and remote sensing for high-resolution imaging demands.

中文翻译：

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高分辨率鬼成像的预处理反卷积方法

鬼成像（GI）可以利用光场的波动特性对物体进行非局部成像，其中空间分辨率由归一化的二阶相关函数决定 $G^{(2)}$. 然而，空间位移不变性$G^{(2)}$当样本数量有限时失真，这阻碍了反卷积方法提高GI的空间分辨率。在本文中，基于先验成像系统，我们提出了一种预处理反卷积方法，通过细化 GI 中采样矩阵的相互相干性来提高 GI 的成像分辨率。我们的理论分析表明，预处理反卷积方法实际上将反卷积技术扩展到GI，并回归到传统成像系统的经典反卷积技术。预处理后的 GI 成像分辨率仅限于检测噪声。仿真和实验结果均表明，采用预处理反卷积方法显着提高了重建图像的空间分辨率。在实验中，1。通过预处理解卷积实现了瑞利准则的 4 倍分辨率增强。我们的结果将仅适用于空间位移不变成像系统的反卷积技术扩展到所有线性成像系统，并将促进其在生物成像和遥感中的应用，以满足高分辨率成像的需求。