生物学中的对称性
高斯分布
对称(几何)
亚像素渲染
极化(电化学)
算法
高斯过程
物理
高斯函数
分布(数学)
光学
中心(范畴论)
可靠性(半导体)
过程(计算)
粒子(生态学)
数学分析
计算机科学
计算物理学
稳健性(进化)
摘要
This paper presents and validates a center localization method based on the radial symmetric center (RSC) algorithm, specifically for atomic-column center localization in scanning transmission electron microscopy (STEM) images. The method leverages the radial symmetry of the particle intensity distribution and achieves subpixel localization accuracy through analytical computation, while avoiding the time-consuming iterative fitting process associated with traditional two-dimensional (2D) Gaussian fitting method. We performed a systematic comparison of the RSC method against the conventional center-of-mass (COM) and 2D-Gaussian fitting methods, focusing on the localization accuracy and computational speed. The results show that the RSC method maintains a high-localization accuracy comparable to Gaussian fitting, while providing a computational speed that is intermediate between that of 2D-Gaussian fitting and the COM method. It demonstrates advantages in both time efficiency and accuracy. Furthermore, we validate the accuracy and reliability of this method through three case studies: atomic-column localization and stress analysis of Au nanoparticles, statistical analysis of atomic spacing in Si/Ge superlattices, and ferroelectric polarization mapping of PbZrxTi1-xO3.
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