Robust phase unwrapping algorithm for interferometric applications based on Zernike polynomial fitting and Wrapped Kalman Filter. (May 2022)

• Record Type: Journal Article
• Authors: Zhao, Zixin; Li, Junxiang; Fan, Chen; Du, Yijun; Zhou, Menghang; Zhang, Xuchao; Zhao, Hong
• Is Part Of: Optics and lasers in engineering. Volume 152(2022)
• Publication Date: 2022-05
• Subjects: Phase unwrapping -- Zernike polynomial -- Wrapped Kalman Filter -- Interferometry; Lasers in engineering -- Periodicals; Optical measurements -- Periodicals; Optics -- Periodicals; Lasers en ingénierie -- Périodiques; Mesures optiques -- Périodiques; Optique -- Périodiques; 621.36605
• DOI: 10.1016/j.optlaseng.2022.106952
• Languages: English
• ISSNs: 0143-8166

Abstract

Highlight: A noise robust phase unwrapping algorithm based on the combination of global Zernike polynomials fitting and the wrapped Kalman filter (WKF) is proposed. An efficient weight strategy based on quality map is applied in the proposed method. The results show that the proposed method can obtain a satisfactory unwrapped phase map even in a very harsh noise condition without sacrificing too much time. The convergence of WKF method is analyzed in this paper and different factors affecting the convergence of WKF are studied. 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.