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

Wang, Minmin; Zhou, Changli; Si, Shuchun; Li, Xiaolei; Lei, Zhenkun; Li, Yanjie

doi:10.1016/j.optlaseng.2017.05.008

Cited by 13 publications

(4 citation statements)

References 36 publications

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“…Robust, unweighted, weighted iterative methods for phase unwrapping using fast transform DCT methodology have been introduced by Ghiglia and Romero [18]. Similarly, Wang et al [19] proposed a phase reconstruction method that combines Perciante's and the weighted LS. Perciante's method measured the continuous phase, representing that the method alone fails to identify singularities that depend on noise and other factors.…”

Section: Literature Reviewmentioning

confidence: 99%

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MRI Phase Image Unwrapping using DCT Based Modified Weighted Least Square Algorithm

Verma,

GOEL,

Tanveer

et al. 2023

Preprint

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Background: Phase images of magnetic resonance imaging (MRI) have applications in many fields, including the medical domain. It is often employed to identify biomarkers of neurodegenerative diseases such as Alzheimer's, Parkinson's, and others. However, directly extracted phase images from MRI exhibit the wrapped phase values within the ±π radian range. Methods: To circumvent these phase jumps or discontinuity, phase unwrapping is required. Path-following and minimum norms algorithms are unwrapping methods to retrieve the original unwrapped phase image. The path-following algorithm extracts the original phase value by considering the adjacent pixels along the integral path. In contrast, the minimum norms algorithm aims to minimize the difference between the partial derivatives of the wrapped and the unwrapped phase data. This paper presents the DCT-based modified minimum norm-based weighted least square (LS) phase unwrapping to improve the visibility and noise immunity of the phase images. The proposed algorithm eradicates residual noise by imposing spectral truncation of the low-frequency coefficient. Results and Conclusions: For the experimental validation of the proposed algorithm, the wrapped and unwrapped image phase profiles are demonstrated to show the effectiveness of the proposed phase unwrapping algorithm. In addition, the performance metrics, peak signal-to-noise ratio (PSNR), structural similarity index metric (SSIM), and root mean squared error (RMSE) are calculated to show the comparison of the proposed phase unwrapping algorithm with the state-of-the-art techniques.

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Section: Literature Reviewmentioning

confidence: 99%

“…Table 1 and Table 2 evidenced that modified methodology outperformed other methods for the first and second brain scans, respectively. [30] 45.66 0.8303 6.7232 DCT [19] 45.32 0.8302 6.8642 QGPU [31] 45.55 0.2032 11.2700 LPU [32] 46.01 0.2128 10.7840 Proposed Algorithm 46.05 0.8319 6.2558…”

Section: Comparison Of Phase Unwrapping Using Quality Matricesmentioning

confidence: 99%

MRI Phase Image Unwrapping using DCT Based Modified Weighted Least Square Algorithm

Verma,

GOEL,

Tanveer

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…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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“…They can be used as weights in the least square methods, modulating the optimization criteria. [2][3][4] Moreover, quality map-guided unwrapping methods based on data quality indices frequently appear in the research literature. Recently, improved schemes have been proposed, such as interwoven linked list, 5 priority queuing, 6,7 and quality mapping with edges and shadow areas.…”

Section: Introductionmentioning

confidence: 99%

Phase unwrapping method based on parallel local minimum reliability dual expanding for large-scale data

Gao

Sun

2019

J. Appl. Rem. Sens.

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Considering data reliability, the optimized connections of dual residues for phase discontinuity reconstruction provide a more reliable scheme and produce more robust unwrapped results. However, their practical implementation usually involves a time-consuming iterative global operation, which is not suitable for application to the phase unwrapping (PU) of big blocks of interferometric synthetic aperture radar (InSAR) phase data. A parallel PU method based on local minimum reliability dual expanding is proposed. With given quality weight maps, the dual reliability is defined based on residues, and the minimum reliability residue pairs are introduced to represent possible discontinuous boundaries. We provide a dynamic expanding method for the pairs with local minimum reliability searching and dual merging. The final minimum balanced trees obtained are used for path integrating of PU with the aid of reliability maps. The calculation of reliability maps, the residue pair searching, and the dynamic expanding are designed to be carried out in parallel. We employ the interface propagation scheme based on the eikonal equation and flood-filling for the parallel implement. Two big blocks of airborne InSAR data were processed by the proposed method, the experimental results and analysis verified its robustness and efficiency for the large-scale PU problem.

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

Cited by 13 publications

References 36 publications

MRI Phase Image Unwrapping using DCT Based Modified Weighted Least Square Algorithm

MRI Phase Image Unwrapping using DCT Based Modified Weighted Least Square Algorithm

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

Phase unwrapping method based on parallel local minimum reliability dual expanding for large-scale data

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