Open AccessPhase calibration unwrapping algorithm for phase data corrupted by strong decorrelation speckle noise
Author(s) -
Haiting Xia,
Silvio Montrésor,
Rongxin Guo,
Junchang Li,
Yan Feng,
Cheng Hu,
Pascal Picart
Publication year - 2016
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.24.028713
Subject(s) - decorrelation , algorithm , speckle noise , smoothing , noise (video) , computer science , speckle pattern , phase noise , gaussian noise , digital holography , phase (matter) , computation , calibration , phase retrieval , optics , holography , artificial intelligence , computer vision , physics , image (mathematics) , fourier transform , quantum mechanics
Robust phase unwrapping in the presence of high noise remains an open issue. Especially, when both noise and fringe densities are high, pre-filtering may lead to phase dislocations and smoothing that complicate even more unwrapping. In this paper an approach to deal with high noise and to unwrap successfully phase data is proposed. Taking into account influence of noise in wrapped data, a calibration method of the 1st order spatial phase derivative is proposed and an iterative approach is presented. We demonstrate that the proposed method is able to process holographic phase data corrupted by non-Gaussian speckle decorrelation noise. The algorithm is validated by realistic numerical simulations in which the fringe density and noise standard deviation is progressively increased. Comparison with other established algorithms shows that the proposed algorithm exhibits better accuracy and shorter computation time, whereas others may fail to unwrap. The proposed algorithm is applied to phase data from digital holographic metrology and the unwrapped results demonstrate its practical effectiveness. The realistic simulations and experiments demonstrate that the proposed unwrapping algorithm is robust and fast in the presence of strong speckle decorrelation noise.