To eliminate distortion caused by vertical drift and illusory slopes in atomic force microscopy (AFM) imaging, a lifting-wavelet-based iterative thresholding correction method is proposed in this paper. This method achieves high-quality AFM imaging via line-by-line corrections for each distorted profile along the fast axis. The key to this line-by-line correction is to accurately simulate the profile distortion of each scanning row. Therefore, a data preprocessing approach is first developed to roughly filter out most of the height data that impairs the accuracy of distortion modeling. This process is implemented through an internal double-screening mechanism. A line-fitting method is adopted to preliminarily screen out the obvious specimens. Lifting wavelet analysis is then carried out to identify the base parts that are mistakenly filtered out as specimens so as to preserve most of the base profiles and provide a good basis for further distortion modeling. Next, an iterative thresholding algorithm is developed to precisely simulate the profile distortion. By utilizing the roughly screened base profile, the optimal threshold, which is used to screen out the pure bases suitable for distortion modeling, is determined through iteration with a specified error rule. On this basis, the profile distortion is accurately modeled through line fitting on the finely screened base data, and the correction is implemented by subtracting the modeling result from the distorted profile. Finally, the effectiveness of the proposed method is verified through experiments and applications.
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