Reiser Nikolaj, Guo Min, Shroff Hari, Riviere Patrick J La
ArXiv. 2023 Aug 1:arXiv:2308.00734v1.
Phase diversity is a widefield aberration correction method that uses multiple images to estimate the phase aberration at the pupil plane of an imaging system by solving an optimization problem. This estimated aberration can then be used to deconvolve the aberrated image or to reacquire it with aberration corrections applied to a deformable mirror. The optimization problem for aberration estimation has been formulated for both Gaussian and Poisson noise models but the Poisson model has never been studied in microscopy nor compared with the Gaussian model. Here, the Gaussian- and Poisson-based estimation algorithms are implemented and compared for widefield microscopy in simulation. The Poisson algorithm is found to match or outperform the Gaussian algorithm in a variety of situations, and converges in a similar or decreased amount of time. The Gaussian algorithm does perform better in low-light regimes when image noise is dominated by additive Gaussian noise. The Poisson algorithm is also found to be more robust to the effects of spatially variant aberration and phase noise. Finally, the relative advantages of re-acquisition with aberration correction and deconvolution with aberrated point spread functions are compared.
相位多样性是一种宽场像差校正方法，它通过解决一个优化问题，利用多幅图像来估计成像系统光瞳平面处的相位像差。然后，这个估计出的像差可用于对畸变图像进行去卷积，或者在对可变形镜应用像差校正的情况下重新获取图像。像差估计的优化问题已针对高斯噪声模型和泊松噪声模型进行了公式化，但泊松模型在显微镜领域从未被研究过，也未与高斯模型进行过比较。在此，在模拟中针对宽场显微镜实现并比较了基于高斯和泊松的估计算法。发现泊松算法在各种情况下与高斯算法相当或更优，并且在相似或更短的时间内收敛。当图像噪声主要由加性高斯噪声主导时，高斯算法在低光条件下确实表现更好。还发现泊松算法对空间变化像差和相位噪声的影响更具鲁棒性。最后，比较了使用像差校正重新获取图像和使用畸变点扩散函数进行去卷积的相对优势。
