Reducing molecular simulation time for AFM images based on super-resolution methods

• Zhipeng Dou,
• Jianqiang Qian,
• Yingzi Li,
• Rui Lin,
• Jianhai Wang,
• Peng Cheng and
• Zeyu Xu

Beilstein J. Nanotechnol. 2021, 12, 775–785, doi:10.3762/bjnano.12.61

• can be used to speed up the generation of training data and vary simulation resolution for AFM machine learning. Keywords: atomic force microscopy; Bayesian compressed sensing; convolutional neural network; molecular dynamics simulation; super resolution; Introduction Atomic force microscopy methods

• the reconstruction algorithm is essential for CS. The Bayesian compressed sensing (BCS) can achieve a better recovery performance due to its high degree of sparsity and the ability to estimate the posterior distribution of the reconstructed signal [45][46][47][48], even if the signal is not sparse. In

• changed to a hemisphere and a single atom. The tip is typically scanned parallel to the surface at a fixed distance to the molecule being investigated. The raster scanning method is also applied for the quasi-static mode with a size of 101 × 101. Bayesian compressed sensing For linear systems, the signal

A novel method to remove impulse noise from atomic force microscopy images based on Bayesian compressed sensing

• Yingxu Zhang,
• Yingzi Li,
• Zihang Song,
• Zhenyu Wang,
• Jianqiang Qian and
• Junen Yao

Beilstein J. Nanotechnol. 2019, 10, 2346–2356, doi:10.3762/bjnano.10.225

• , China School of Physics, Beihang University, Beijing 100191, China 10.3762/bjnano.10.225 Abstract A novel method based on Bayesian compressed sensing is proposed to remove impulse noise from atomic force microscopy (AFM) images. The image denoising problem is transformed into a compressed sensing

• matrices with some rows removed, are constructed by recording the position of the noise-free pixels. Third, the Bayesian compressed sensing reconstruction algorithm is applied to recover the image. Different from traditional compressed sensing reconstruction methods in AFM, each row of the AFM image is

• proposed method is robust and its performance is not influenced by the noise density in a certain range. Keywords: atomic force microscopy (AFM); Bayesian compressed sensing; denoising; image processing; impulse noise; Introduction Atomic force microscopy (AFM) is a powerful tool in the fields of