Phase Unwrapping Error Correction Based on Multiple Linear Regression Analysis

Fringe projection profilometry (FPP) is prone to phase unwrapping error (PUE) due to phase noise and measurement conditions. Most of the existing PUE-correction methods detect and correct PUE on a pixel-by-pixel or partitioned block basis and do not make full use of the correlation of all information in the unwrapped phase map. In this study, a new method for detecting and correcting PUE is proposed. First, according to the low rank of the unwrapped phase map, multiple linear regression analysis is used to obtain the regression plane of the unwrapped phase, and thick PUE positions are marked on the basis of the tolerance set according to the regression plane. Then, an improved median filter is used to mark random PUE positions and finally correct marked PUE. Experimental results show that the proposed method is effective and robust. In addition, this method is progressive in the treatment of highly abrupt or discontinuous regions.

Automated summary

In this study, a new method for detecting and correcting phase unwrapping errors (PUE) in fringe projection profilometry is proposed. The method uses multiple linear regression analysis and an improved median filter to detect and correct errors in the unwrapped phase map. Experimental results show that the method is effective and robust, and it can handle highly abrupt or discontinuous regions.