Abstract

A new method of phase unwrapping is proposed for the absolute phase estimation based on the first-order polynomial phase approximation within a symmetric window generated around each pixel. The accurate estimation of polynomial coefficients is performed by formulating them as the elements of a state vector in a state space model. The extended Kalman filter offers a robust approach for the state estimation with the capability of handling high noise power. The polynomial coefficients estimates obtained at a given pixel are used as the initial conditions of the Kalman filter for its neighboring pixel, which results in the unwrapped phase estimation. The simulation and experimental results validate the performance of the proposed phase unwrapping method along with its ability of handling the masked phase fringe patterns with the help of a predefined binary mask and a pixel selection strategy.

© 2016 Optical Society of America

Phase unwrapping algorithm using polynomial phase approximation and linear Kalman filter

Rishikesh Kulkarni and Pramod Rastogi
Appl. Opt. 57(4) 702-708 (2018)

Phase-unwrapping method based on local polynomial models and a maximum a posteriori model correction

Alejandro Téllez-Quiñones, Juan C. Valdiviezo-N, Adán Salazar-Garibay, Hugo Carlos-Martínez, and Jesús A. Monroy-Anieva
Appl. Opt. 60(5) 1121-1131 (2021)

Absolute phase estimation: adaptive local denoising and global unwrapping

Jose Bioucas-Dias, Vladimir Katkovnik, Jaakko Astola, and Karen Egiazarian
Appl. Opt. 47(29) 5358-5369 (2008)

Robust particle-Kalman filtering phase unwrapping algorithm for wrapped fringe patterns

Xianming Xie and Jiaying Li
Appl. Opt. 61(23) 6677-6689 (2022)

Direct phase unwrapping method based on a local third-order polynomial fit

Alejandro Téllez-Quiñones, Ricardo Legarda-Sáenz, Adán Salazar-Garibay, Juan C. Valdiviezo-N, and Miguel León-Rodríguez
Appl. Opt. 58(2) 436-445 (2019)