Robust phase unwrapping algorithm for interferometric applications based on Zernike polynomial fitting and Wrapped Kalman Filter

Abstract

We propose a noise robust phase unwrapping algorithm based on the state-space model of Zernike polynomials fitting and the Wrapped Kalman Filter. In our method, the phase map is modeled as the linear combination of Zernike polynomials and the phase unwrapping problem reduces to the estimation of the fitting coefficients. To accurately calculate those coefficients under a noisy condition, the Wrapped Kalman Filter with a weighting strategy based on the second difference of the wrapped phase map is developed. As a result, our proposed method can successfully recover an absolute phase from a wrapped phase map corrupted by heavy noise. The results of synthetic data and experimental data show the outperformance of the proposed methods against other three representative algorithms.