Wrapping-free phase retrieval with applications to interferometry, 3D-shape profiling, and deflectometry

Perciante, César D.; Strojnik, Marija; Паез, Гонзало; Martino, J. Matías Di; Ayubi, Gastón A.; Flores, Jorge L.; Ferrari, José A.

doi:10.1364/ao.54.003018

Cited by 11 publications

(4 citation statements)

References 29 publications

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“…The wrapping-free phase retrieval method proposed by Perciante et. al has been thoroughly described and discussed [34], this section only introduces its main idea briefly. Suppose Perciante's method is applied to four-step phase-shifting fringe.…”

Section: Perciante's Methodsmentioning

confidence: 99%

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Robust wrapping-free phase retrieval method based on weighted least squares method

Wang

Zhou

et al. 2017

Optics and Lasers in Engineering

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For many profilometry techniques, phase unwrapping is one of the most challenging process. In order to sidestep the phase unwrapping process, Perciante et. al [Appl Opt 2015; 54(10):3018-23] proposed a wrapping-free method based on the direct integration of the spatial derivatives of the patterns to retrieve the phase. But it is only applicable for the case of the phase continuity for the tested object, which means it may fail to handle fringe patterns containing complicated singularities, such as noise, shadow, shears and surface discontinuity. In view of this problems, a robust wrapping-free phase retrieval method is proposed in this paper, which is based on combined Perciante's method and weighted least-squares method. Two partial derivatives of the desired phase is obtained from the fringe patterns, meanwhile the carrier is eliminated using direct phase difference method. The phase singularities are determined using derivative variance correlation map (DVCM), and the weighting coefficient is obtained from the binary mask of the reverse DVCM. Simulations and experiments are conducted to prove the validity of the proposed method. Results are analyzed and compared with those of Perciante's method, demonstrating that the proposed method can be available for measuring objects with some kinds of singularities sources.

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Section: Perciante's Methodsmentioning

confidence: 99%

“…Recently, Perciante et. al [34] presented a wrapping-free phase retrieval method. It determines the phase of the test object following two steps: first, it derives two partial derivatives of the desired phase from the fringe patterns, and then it reconstructs the phase by the line integral of the two partial derivatives.…”

Section: Introductionmentioning

confidence: 99%

Robust wrapping-free phase retrieval method based on weighted least squares method

Wang

Zhou

et al. 2017

Optics and Lasers in Engineering

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“…Furthermore, the Least-Squares algorithm shows the inherent defects that flatten the peak value and fill the valley value during phase unwrapping, which will significantly decrease unwrapping performance. Perciante et al [14] proposed the wrapping-free unwrapping algorithm, which yields derivatives of the required horizontal and vertical phase from the corresponding fringe image and reconstructs the phase by calculating the two partial derivatives. Similar to the referenced algorithms [15][16], it converts the integral of the mentioned space derivatives as a solution to the Poisson equation.…”

Section: Introductionmentioning

confidence: 99%

A robust unwrapping method for local noise phase

Yu²,

Yang³

et al. 2022

International Conference on Signal Processing and Communication Security (ICSPCS 2022)

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Phase unwrapping algorithm is difficult to apply in INSAR image for the local high-density noise phase attributed to significant blocky noise. To achieve its application in such case, the pixels of noise phase are first detected, and are set to 0 with the automatic mask technique. For the phase that has a blocky noise region, the iteration algorithm of phase filling based on Least-Squares is developed in this study by calculating the unwrapping coefficient k to rebuild the true phase. The algorithm is promoted by MPIPU's ability to fill in the missing phase; it can also significantly suppress the error transfer attributed to iteration filling in the non-mask phase. Some experiments are performed on simulated data. As revealed from the results, the proposed method exhibits robust performance of phase unwrapping on local noise phase.

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“…It has been shown that this method can obtain good unwrapping results at discontinuities. Based on the wrapping-free phase retrieval method described in [17], Zhou et al [18] proposed a binary mask of a reverse DVCM as the weight mask. Since the second derivative of the four-step phaseshifting fringe pattern needs to be calculated, these methods are only suitable for particular measurement objects with singularities.…”

Section: Introductionmentioning

confidence: 99%

A Robust Discontinuous Phase Unwrapping Based on Least-Squares Orientation Estimator

Deng

Zhou

et al. 2021

Electronics

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Weighted least-squares (WLS) phase unwrapping is widely used in optical engineering. However, this technique still has issues in coping with discontinuity as well as noise. In this paper, a new WLS phase unwrapping algorithm based on the least-squares orientation estimator (LSOE) is proposed to improve phase unwrapping robustness. Specifically, the proposed LSOE employs a quadratic error norm to constrain the distance between gradients and orientation vectors. The estimated orientation is then used to indicate the wrapped phase quality, which is in terms of a weight mask. The weight mask is calculated by post-processing, including a bilateral filter, STDS, and numerical relabeling. Simulation results show that the proposed method can work in a scenario in which the noise variance is 1.5. Comparisons with the four WLS phase unwrapping methods indicate that the proposed method provides the best accuracy in terms of segmentation mean error under the noisy patterns.

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Wrapping-free phase retrieval with applications to interferometry, 3D-shape profiling, and deflectometry

Cited by 11 publications

References 29 publications

Robust wrapping-free phase retrieval method based on weighted least squares method

Robust wrapping-free phase retrieval method based on weighted least squares method

A robust unwrapping method for local noise phase

A Robust Discontinuous Phase Unwrapping Based on Least-Squares Orientation Estimator

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