AI Article Synopsis

  • The paper discusses a new method for extracting phase information from moiré fringes using the Morlet continuous wavelet transform, which is essential for accurate results in moiré tomography.
  • The authors provide a comprehensive explanation of the theory and algorithm behind this method and conduct experiments on four different flow fields to test its effectiveness.
  • Results show that the Morlet continuous wavelet transform outperforms traditional techniques like Fourier transform and Gabor wavelet transform in terms of accuracy and smoothness, indicating its potential for broader applications.

Article Abstract

The extraction of phase information is crucial in moiré tomography for achieving accurate results. In this paper, a method for extracting phase information of moiré fringes based on the Morlet continuous wavelet transform is introduced. A detailed exposition of the theoretical deduction and algorithmic procedure of this method is provided. And then, to validate the feasibility and applicability of this approach, four flow fields are conducted as test objects for experiments. Based on that, the phase results provided by the Morlet continuous wavelet transform are compared with those obtained by the reported techniques such as Fourier transform and Gabor wavelet transform. It is evident that Morlet continuous wavelet transform demonstrates superior accuracy and smoothness, which proves the reliability of this method. In summary, the method presented in this study probably offers an effective method with broad applications.

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Source
http://dx.doi.org/10.1364/AO.511443DOI Listing

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