Kellogg Honors College and Department of Mathematics and Statistics, California State Polytechnic University, Pomona, California 91768, USA.
Opt Lett. 2012 Feb 1;37(3):413-5. doi: 10.1364/OL.37.000413.
A common task in microscopy is to fit an image of a fluorescent probe to a point spread function (PSF) in order to estimate the position of the probe. The PSF is often approximated as a Gaussian for mathematical simplicity. We show that the separable property of the Gaussian PSF enables a reduction of computational time from O(L2) to O(L), where L is the width (in pixels) of the image. When tested on realistic simulated data, our algorithm is able to localize the probes with precision close to the Cramér-Rao lower bound.
在显微镜中，常见的任务是将荧光探针的图像拟合到点扩散函数 (PSF) 中，以估计探针的位置。PSF 通常为了数学上的简单而近似为高斯函数。我们表明，高斯 PSF 的可分离性使得计算时间从 O(L2)减少到 O(L)，其中 L 是图像的宽度（以像素为单位）。在对现实模拟数据进行测试时，我们的算法能够以接近克拉美-罗下限的精度定位探针。
