Interferogram phase iterative recovery method based on Schmidt orthogonalization

Abstract

The invention discloses an interferogram phase iterative recovery method based on Schmidt orthogonalization, and relates to the technical field of interferogram processing. The method comprises the steps: obtaining the intensity distribution of a set of interferograms by using the phase shift interferometry, and eliminating the interferogram background by the subtracting of the intensity distribution to obtain a differential interferogram without a background; recombining and normalizing the differential interferogram without the background to obtain an iterative relation between a variable for obtaining a precise phase of the interferogram and the phase; performing the iteration of the variable to obtain a final accurate phase value according to the above iterative relation, and completing the phase recovery of the interferogram. The method breaks through the limitation of a traditional orthogonal method, can achieve the precise phase recovery of the interferogram with less than one stripe, and is insensitive to the phase shift amount by recombining the interferogram, and can complete the accurate phase recovery even if there is only a very small phase shift amount between the interferograms.

Description

technical field [0001] The invention relates to the technical field of interferogram processing, in particular to an iterative recovery method for interferogram phase based on Schmidt orthogonalization. Background technique [0002] The random phase shift algorithm itself does not require the amount of phase shift, and only needs a certain number (generally more than three) of interferograms to obtain the phase, so it does not require a complex control system to achieve a definite phase shift step; for example In 2004, Wang proposed an advanced iterative algorithm (AIA), which is often used as a reference comparison algorithm for phase recovery. AIA can obtain high-precision phase distribution and phase shift from a series of interferograms. AIA not only does not require the interferogram phase shift step size but also has high calculation accuracy. There is a similar algorithm based on Lissajous graph fitting, which finally uses the least squares fitting to obtain the phas...

AI Technical Summary

Problems solved by technology

Recently, Li used a two-channel interferometry system to realize the phase recovery of less than one fringe, but this algorithm needs to ensure that the phase shift of the two channels is different, which means that the algorithm can only be used in a two-channel interferometry system. Traditional interferometry systems The conditions may not be met, and the system construction will have a greater impact on the calculation results

For the case where the phase shift range of the interferogram is small, in 2016 Deng[34] achieved the effect of increasing the phase shift by reorganizing the interferogram, and then combined with the PCA algorithm to complete the phase recovery, but this method, like PCA, also needs to ensure that the interferogram at least 1 stripe

In 2017, Wang proposed a mid-band spatial spectrum matching (MSSM) method that can not only achieve good results in the case of small phase shifts, but also for the case where the number of fringes in the interferogram is less than 1. Accurate phase recovery is possible, but this method requires that the phase shift between the interferograms cannot be close to π, which limits its scope of use

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