基于稳健回归的AFM图像水平矫正算法

 AFM（Atomic Force Microscope，原子力显微镜）图像经常会出现背景倾斜或弯曲。背景倾斜的原因源于探针和样本表面的倾角或XYZ扫描仪带来的弯曲。本文将稳健的MM估计算法应用到AFM图像二维背景拟合中，消除背景的倾斜，并利用fast-s估计算法作为初始化，以缩短计算时间。实验结果表明，与传统方法相比，本方法的AFM图像水平矫正效果更好。

An AFM Image Leveling Algorithm Based on Robust Regression

AFM images always have some background slope or curvature that must be removed from the image. Sources of the background can be an offset angle between the probe and surface, or curvature introduced into the image from the XYZ scanner. There are a number of background subtraction options that are possible. In this paper, we take use of mm-estimators, one most commonly employed robust regression technique to calculate the background in the image and enhance its speed via fast-s estima- tion approach. Numerical results prove its excellent performances in AFM image leveling compared with other traditional algo- rithms.