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

• reconstructed separately in the proposed method, which will not reduce the quality of the reconstructed image. The denoising experiments are conducted to demonstrate that the proposed method can remove the impulse noise from AFM images while preserving the details of the image. Compared with other methods, the

• 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