In this paper, the expression for the SNR has been developed through the imaging model. It is concluded that the image SNR decreases with the increase of the number of light-emitting points of the target under the same hardware conditions and experimental parameters. Using uniform bright squares of different sizes as the target, the SNR of the reconstructed image is calculated. Simulation and prototype experiments have proved the correctness of the conclusion. Based on this conclusion, a method of segmented area imaging is proposed to improve the reconstructed image quality. The quality of all the images using this method with Wiener inverse filtering, R-Lucy deconvolution, and ADMM is better than the image quality obtained by full-area imaging.

在本文中，通过成像模型开发了SNR的表达式。可以得出结论，在相同的硬件条件和实验参数下，图像的信噪比随目标发光点数量的增加而降低。使用不同大小的均匀明亮方块作为目标，计算重建图像的SNR。仿真和原型实验证明了该结论的正确性。基于这一结论，提出了一种分割区域成像的方法，以提高重建图像的质量。使用此方法以及Wiener逆滤波，R-Lucy反卷积和ADMM的所有图像质量均优于通过全区域成像获得的图像质量。