Residue calibrated least-squares unwrapping algorithm for noisy and steep phase maps
Cong Wei, Jun Ma, Xinyu Miao, Nianfeng Wang, Yi Zong, Caojin Yuan
Abstract
This work proposes a robust unwrapping algorithm for noisy and steep phase maps based on the residue calibrated least-squares method. The proposed algorithm calculates and calibrates the residues in the derivative maps to get a noise-free Poisson equation. Moreover, it compensates for the residuals between the wrapped and unwrapped phase maps iteratively to eliminate approximation errors and the smoothing effect of the least-squares method. The robustness and efficiency of the proposed algorithm are validated by unwrapping simulated and experimentally wrapped phase maps. Compared with the other three typical algorithms, the proposed algorithm has the most effective performance in noisy and steep phase unwrapping, providing a reliable alternative for practical applications.