AFM图像中非均匀条纹噪声的去除

J. Pellequer, Y. Chen, S. W. Chen
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引用次数: 4

摘要

由于探针分子与AFM尖端相互作用强度的突然增加,尖端振动的剧烈变化导致扫描样品表面时高度信息的丢失或获取不足。因此,条纹噪声出现,并立即成为表征AFM图像中物体的第一个遇到的障碍。提出了一种基于图像傅里叶谱的无监督去条纹方法。由于噪声像素的识别是去噪过程中的关键步骤,因此由无监督DeStripe选择的作为潜在噪声的像素可能不会令用户满意。目前的工作提出了一种替代方案,即潜在的噪声像素由输入参数决定。计算过程主要遵循前面描述的无监督DeStripe的设计。我们发现,与无监督的去条纹相比,有监督的去条纹清洗后的图像的分子特征更加突出。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Removal of Non-uniform Stripe Noises from AFM Images
Due to abrupt increase in interacting strength of probed molecules and the AFM tip, the dramatic change in tip vibrations leads to a loss or inadequate acquisition of height information during the scanning across the sample surfaces. Consequently, stripe noises occur and immediately become the first encountered obstacle for characterizing objects in AFM images. The un-supervised DeStripe has been developed for removing stripes based on the Fourier spectrum of image. Since identification of noisy pixels is a critical step in the denoising procedure, the pixels selected by un-supervised DeStripe as potentially noisy may not be satisfactory for the user. The present work presents an alternative that the potentially noisy pixels are decided by input parameters. The computational procedure mainly follows the design of un-supervised DeStripe as described previously [1]. We found that the molecular feature of the cleaned image by the supervised protocol is more prominent than that by the un-supervised DeStripe.
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