基于稳健回归的AFM图像水平矫正算法

计算机与现代化

基于稳健回归的AFM图像水平矫正算法

中国科学院电子学研究所，北京100190

收稿日期:2014-03-27 出版日期:2014-06-13 发布日期:2014-06-25
作者简介:翟腾飞（1988-）,男,江苏南通人,中国科学院电子学研究所硕士研究生,研究方向：图像处理；雷宏（1962-）,男,研究员，博士生导师,研究方向：合成孔径雷达天线，信号处理。

An AFM Image Leveling Algorithm Based on Robust Regression

Institute of Electronics， Chinese Academy of Science， Beijing 100190, China

Received:2014-03-27 Online:2014-06-13 Published:2014-06-25

摘要/Abstract

摘要： 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。

关键词: AFM图像水平矫正, 稳健回归, MM估计, fast-s估计

Abstract: 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 estimation approach. Numerical results prove its excellent performances in AFM image leveling compared with other traditional algorithms.

Key words: AFM image leveling, robust regression, MM-estimator, fast-s estimation

翟腾飞，雷宏，冯文森. 基于稳健回归的AFM图像水平矫正算法[J]. 计算机与现代化.

ZHAI Teng-fei, LEI Hong, FENG Wen-sen. An AFM Image Leveling Algorithm Based on Robust Regression[J]. Computer and Modernization.

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