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Journal articles on the topic 'Phase extraction; Phase unwrapping; Algorithms'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Barone, Ilaria, Emanuel Kästle, Claudio Strobbia, and Giorgio Cassiani. "Surface wave tomography using 3D active-source seismic data." GEOPHYSICS 86, no. 1 (2021): EN13—EN26. http://dx.doi.org/10.1190/geo2020-0068.1.

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Surface wave tomography (SWT) is a powerful and well-established technique to retrieve 3D shear-wave (S-wave) velocity models at the regional scale from earthquakes and seismic noise measurements. We have applied SWT to 3D active-source data, in which higher modes and heterogeneous spatial sampling make phase extraction challenging. First, synthetic traveltimes calculated on a dense, regular-spaced station array are used to test the performance of three different tomography algorithms (linearized inversion, Markov chain Monte Carlo [MCMC], and eikonal tomography). The tests suggest that the lo

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2

Liu, Junmin, and Maria Drangova. "Phase-unwrapping algorithm for translation extraction from spherical navigator echoes." Magnetic Resonance in Medicine 63, no. 2 (2009): 510–16. http://dx.doi.org/10.1002/mrm.22198.

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3

Xue, D., X. Yu, S. Jia, F. Chen, and X. Li. "STUDY ON LANDSLIDE DISASTER EXTRACTION METHOD BASED ON SPACEBORNE SAR REMOTE SENSING IMAGES – TAKE ALOS PALSAR FOR AN EXAMPLE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3 (April 30, 2018): 2023–27. http://dx.doi.org/10.5194/isprs-archives-xlii-3-2023-2018.

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In this paper, sequence ALOS PALSAR data and airborne SAR data of L-band from June 5, 2008 to September 8, 2015 are used. Based on the research of SAR data preprocessing and core algorithms, such as geocode, registration, filtering, unwrapping and baseline estimation, the improved Goldstein filtering algorithm and the branch-cut path tracking algorithm are used to unwrap the phase. The DEM and surface deformation information of the experimental area were extracted. Combining SAR-specific geometry and differential interferometry, on the basis of composite analysis of multi-source images, a meth

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Zhu, Nannan, Jun Hu, Shiyou Xu, Wenzhen Wu, Yunfan Zhang, and Zengping Chen. "Micro-Motion Parameter Extraction for Ballistic Missile with Wideband Radar Using Improved Ensemble EMD Method." Remote Sensing 13, no. 17 (2021): 3545. http://dx.doi.org/10.3390/rs13173545.

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Micro-motion parameters extraction is crucial in recognizing ballistic missiles with a wideband radar. It is known that the phase-derived range (PDR) method can provide a sub-wavelength level accuracy. However, it is sensitive and unstable when the signal-to-noise ratio (SNR) is low. In this paper, an improved PDR method is proposed to reduce the impacts of low SNRs. First, the high range resolution profile (HRRP) is divided into a series of segments so that each segment contains a single scattering point. Then, the peak values of each segment are viewed as non-stationary signals, which are fu

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Guaragnella, Cataldo, and Tiziana D’Orazio. "A Data-Driven Approach to SAR Data-Focusing." Sensors 19, no. 7 (2019): 1649. http://dx.doi.org/10.3390/s19071649.

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Synthetic Aperture RADAR (SAR) is a radar imaging technique in which the relative motion of the sensor is used to synthesize a very long antenna and obtain high spatial resolution. Several algorithms for SAR data-focusing are well established and used by space agencies. Such algorithms are model-based, i.e., the radiometric and geometric information about the specific sensor must be well known, together with the ancillary data information acquired on board the platform. In the development of low-cost and lightweight SAR sensors, to be used in several application fields, the precise mission par

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6

Spagnolini, Umberto. "2-D phase unwrapping and phase aliasing." GEOPHYSICS 58, no. 9 (1993): 1324–34. http://dx.doi.org/10.1190/1.1443515.

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The phase of complex signals is measured modulo-2π (wrapped phase); continuous‐phase information is obtained by adding properly chosen multiples of 2π shift to the wrapped phase. Unwrapping searches for the 2π combinations that minimize the discontinuity of the unwrapped phase as only the unwrapped phase can be analyzed and interpreted by further processing. The key problem of phase unwrapping is phase aliasing, a condition mainly caused by rapid phase variations. The extension of the one‐dimensional (1-D) phase unwrapping algorithms to a two‐dimensional (2-D) domain by 1-D slicing gives unsat

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Huntley, J. M., and H. O. Saldner. "Shape measurement by temporal phase unwrapping: comparison of unwrapping algorithms." Measurement Science and Technology 8, no. 9 (1997): 986–92. http://dx.doi.org/10.1088/0957-0233/8/9/005.

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8

Collaro, Antonio, Giorgio Franceschetti, Francesco Palmieri, and Maria Sedes Ferreiro. "Phase unwrapping by means of genetic algorithms." Journal of the Optical Society of America A 15, no. 2 (1998): 407. http://dx.doi.org/10.1364/josaa.15.000407.

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9

Heshmat, Samia, Satoshi Tomioka, and Shusuke Nishiyama. "Performance Evaluation of Phase Unwrapping Algorithms for Noisy Phase Measurements." International Journal of Optomechatronics 8, no. 4 (2014): 260–74. http://dx.doi.org/10.1080/15599612.2014.942927.

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10

Salfity, M. F., J. M. Huntley, M. J. Graves, O. Marklund, R. Cusack, and D. A. Beauregard. "Extending the dynamic range of phase contrast magnetic resonance velocity imaging using advanced higher-dimensional phase unwrapping algorithms." Journal of The Royal Society Interface 3, no. 8 (2005): 415–27. http://dx.doi.org/10.1098/rsif.2005.0096.

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Phase contrast magnetic resonance velocity imaging is a powerful technique for quantitative in vivo blood flow measurement. Current practice normally involves restricting the sensitivity of the technique so as to avoid the problem of the measured phase being ‘wrapped’ onto the range − π to + π . However, as a result, dynamic range and signal-to-noise ratio are sacrificed. Alternatively, the true phase values can be estimated by a phase unwrapping process which consists of adding integral multiples of 2 π to the measured wrapped phase values. In the presence of noise and data undersampling, the

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11

Zhang Zhihui, 张志会, 王华英 Wang Huaying, 刘佐强 Liu Zuoqiang, et al. "Phase Unwrapping Algorithms Based on Fast Fourier Transform." Laser & Optoelectronics Progress 49, no. 12 (2012): 120902. http://dx.doi.org/10.3788/lop49.120902.

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12

Zhang Yizhuo, 张亦卓, 王大勇 Wang Dayong, 赵洁 Zhao Jie, 万玉红 Wan Yuhong, 江竹青 Jiang Zhuqing, and 陶世荃 Tao Shiquan. "Investigation on Phase Unwrapping Algorithms in Digital Holography." Acta Optica Sinica 29, no. 12 (2009): 3323–27. http://dx.doi.org/10.3788/aos20092912.3323.

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13

Strand, Jarle, and Torfinn Taxt. "Performance evaluation of two-dimensional phase unwrapping algorithms." Applied Optics 38, no. 20 (1999): 4333. http://dx.doi.org/10.1364/ao.38.004333.

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14

Wang Huaying, 王华英, 于梦杰 Yu Mengjie, 刘飞飞 Liu Feifei, and 刘佐强 Liu Zuoqiang. "Four phase unwrapping algorithms based on fast Fourier transform." High Power Laser and Particle Beams 25, no. 5 (2013): 1129–33. http://dx.doi.org/10.3788/hplpb20132505.1129.

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15

Egidi, N., and P. Maponi. "A comparative study of two fast phase unwrapping algorithms." Applied Mathematics and Computation 148, no. 3 (2004): 599–629. http://dx.doi.org/10.1016/s0096-3003(02)00920-7.

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16

Zhang, Qican, Yu Han, and Yingshan Wu. "Comparison and combination of three spatial phase unwrapping algorithms." Optical Review 26, no. 4 (2019): 380–90. http://dx.doi.org/10.1007/s10043-019-00513-7.

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17

Zeng, Fan Guang, Guang Min Wu, John D. Mai, and Jian Ming Chen. "Bayesian MRF Modeling and Graph Cuts for Phase Unwrapping with Discontinuity Phase Flaws：A Comparative Study." Applied Mechanics and Materials 496-500 (January 2014): 1915–18. http://dx.doi.org/10.4028/www.scientific.net/amm.496-500.1915.

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Phase unwrapping (PU) is a difficult task commonly found in applications involving interferometric synthetic aperture radar (InSAR), magnetic resonance imaging (MRI) and optical surface profile measurements; all of which involve mathematically ill-posed problems. Conventional algorithms exhibit strong shortcomings in PU when phase discontinuity flaws exist. To simulate these situations, we are custom-designed test data with a phase discontinuity flaw. This simulated data is a 3D Gaussian distribution with an arc-shaped notch as a phase flaw. PU is carried out by Bayesian inference and MRF (Mar

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18

Han Yu, 韩宇, 张启灿 Zhang Qican, and 吴应山 Wu Yingshan. "Performance Comparison of Three Basic Phase Unwrapping Algorithms and Their Hybrid Algorithms." Acta Optica Sinica 38, no. 8 (2018): 0815006. http://dx.doi.org/10.3788/aos201838.0815006.

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19

Cheng, Nai-Jen, and Wei-Hung Su. "Phase-Shifting Projected Fringe Profilometry Using Binary-Encoded Patterns." Photonics 8, no. 9 (2021): 362. http://dx.doi.org/10.3390/photonics8090362.

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A phase unwrapping method for phase-shifting projected fringe profilometry is presented. It did not require additional projections to identify the fringe orders. The pattern used for the phase extraction could be used for phase unwrapping directly. By spatially encoding the fringe patterns that were used to perform the phase-shifting technique with binary contrasts, fringe orders could be discerned. For spatially isolated objects or surfaces with large depth discontinuities, unwrapping could be identified without ambiguity. Even though the surface color or reflectivity varied periodically with

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20

Hou, X. X., G. M. Huang, and Z. Zhao. "Extracting DEM from airborne X-band data based on PolInSAR." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-7/W4 (June 26, 2015): 35–39. http://dx.doi.org/10.5194/isprsarchives-xl-7-w4-35-2015.

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Polarimetric Interferometric Synthetic Aperture Radar (PolInSAR) is a new trend of SAR remote sensing technology which combined polarized multichannel information and Interferometric information. It is of great significance for extracting DEM in some regions with low precision of DEM such as vegetation coverage area and building concentrated area. In this paper we describe our experiments with high-resolution X-band full Polarimetric SAR data acquired by a dual-baseline interferometric airborne SAR system over an area of Danling in southern China. Pauli algorithm is used to generate the double

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21

Duong, Chen, and Chen. "Absolute Depth Measurement Using Multiphase Normalized Cross-Correlation for Precise Optical Profilometry." Sensors 19, no. 21 (2019): 4683. http://dx.doi.org/10.3390/s19214683.

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In a multifrequency phase-shifting (MFPS) algorithm, the temporal phase unwrapping algorithm can extend the unambiguous phase range by transforming the measurement range from a short fringe pitch into an extended synthetic pitch of two different frequencies. However, this undesirably amplifies the uncertainty of measurement, with each single-frequency phase map retaining its measurement uncertainty, which is carried over to the final unwrapped phase maps in fringe-order calculations. This article analyzes possible causes and proposes a new absolute depth measurement algorithm to minimize the p

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22

Zebker, Howard A., and Yanping Lu. "Phase unwrapping algorithms for radar interferometry: residue-cut, least-squares, and synthesis algorithms." Journal of the Optical Society of America A 15, no. 3 (1998): 586. http://dx.doi.org/10.1364/josaa.15.000586.

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23

Vasil'ev, V. N., I. P. Gurov, and V. M. Chugunov. "Phase unwrapping of interference fringes using recursion and iteration algorithms of phase automatic frequency control." Journal of Optical Technology 70, no. 11 (2003): 771. http://dx.doi.org/10.1364/jot.70.000771.

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24

Zuo, Chao, Lei Huang, Minliang Zhang, Qian Chen, and Anand Asundi. "Temporal phase unwrapping algorithms for fringe projection profilometry: A comparative review." Optics and Lasers in Engineering 85 (October 2016): 84–103. http://dx.doi.org/10.1016/j.optlaseng.2016.04.022.

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25

Ettl, Peter, and Katherine Creath. "Comparison of phase-unwrapping algorithms by using gradient of first failure." Applied Optics 35, no. 25 (1996): 5108. http://dx.doi.org/10.1364/ao.35.005108.

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26

Marroquin, Jose L., Ramon Rodriguez-Vera, Manuel Servin, and Maximino Tapia. "Parallel algorithms for phase unwrapping based on Markov random field models." Journal of the Optical Society of America A 12, no. 12 (1995): 2578. http://dx.doi.org/10.1364/josaa.12.002578.

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27

Cui Haihua, 崔海华, 廖文和 Liao Wenhe, 程筱胜 Cheng Xiaosheng, 戴宁 Dai Ning, and 傅士强 Fu Shiqiang. "Mathematic Descriptions and Analysis of Quality Weighting Factors in Phase Unwrapping Algorithms." Acta Optica Sinica 30, no. 1 (2010): 97–104. http://dx.doi.org/10.3788/aos20103001.0097.

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28

Arevalillo-Herraez, Miguel, Francisco R. Villatoro, and Munther A. Gdeisat. "A Robust and Simple Measure for Quality-Guided 2D Phase Unwrapping Algorithms." IEEE Transactions on Image Processing 25, no. 6 (2016): 2601–9. http://dx.doi.org/10.1109/tip.2016.2551370.

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29

Chen, Curtis W., and Howard A. Zebker. "Network approaches to two-dimensional phase unwrapping: intractability and two new algorithms." Journal of the Optical Society of America A 17, no. 3 (2000): 401. http://dx.doi.org/10.1364/josaa.17.000401.

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30

Zhao, Zixin, Hangying Zhang, Changqing Ma, Chen Fan, and Hong Zhao. "Comparative study of phase unwrapping algorithms based on solving the Poisson equation." Measurement Science and Technology 31, no. 6 (2020): 065004. http://dx.doi.org/10.1088/1361-6501/ab63e8.

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31

Li, Yongguo, Jianqiang Zhu, and Weixing Shen. "Phase unwrapping algorithms, respectively, based on path-following and discrete cosine transform." Optik 119, no. 11 (2008): 545–47. http://dx.doi.org/10.1016/j.ijleo.2007.03.003.

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32

Ajourlou, P., S. Samiei Esfahany, and A. Safari. "A NEW STRATEGY FOR PHASE UNWRAPPING IN INSAR TIME SERIES OVER AREAS WITH HIGH DEFORMATION RATE: CASE STUDY ON THE SOUTHERN TEHRAN SUBSIDENCE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W18 (October 18, 2019): 35–40. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w18-35-2019.

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Abstract. The primary step in all timeseries interferometric synthetic aperture radar (T-InSAR) algorithms is the phase unwrapping step to resolve the inherent cycle ambiguities of interferometric phases. In areas with a high spatio-temporal deformation gradient, phase unwrapping fails due to the aliasing problem, and so it can result in an underestimation of deformation signal. One way to handle this problem is to use the so called Small-Baseline Subset (SBAS) algorithms; in these algorithms, by using only small-baseline interferograms – hence interferograms with small deformation gradients –

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33

Fang, Suping, Leijie Wang, Pengcheng Yang, Lei Meng, and Masaharu Komori. "Object-image-based method to construct an unweighted quality map for phase extraction and phase unwrapping." Applied Optics 50, no. 10 (2011): 1482. http://dx.doi.org/10.1364/ao.50.001482.

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34

He, Wei, Yiyuan Cheng, Ling Xia, and Feng Liu. "A New Particle Swarm Optimization-Based Method for Phase Unwrapping of MRI Data." Computational and Mathematical Methods in Medicine 2012 (2012): 1–9. http://dx.doi.org/10.1155/2012/475745.

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A new method based on discrete particle swarm optimization (dPSO) algorithm is proposed to solve the branch-cut phase unwrapping problem of MRI data. In this method, the optimal order of matching the positive residues with the negative residues is first identified by the dPSO algorithm, then the branch cuts are placed to join each pair of the opposite polarity residues, and in the last step phases are unwrapped by flood-fill algorithm. The performance of the proposed algorithm was tested on both simulated phase image and MRI wrapped phase data sets. The results demonstrated that, compared with

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35

He, Wan Tao, Xiang Lin Meng, Yan Yan Guo, and Can Zhao. "Comparison of Multi-Frequency Phase Unwrapping Algorithm for Shape Measurement Using Digital Fringe Projection." Advanced Materials Research 188 (March 2011): 258–62. http://dx.doi.org/10.4028/www.scientific.net/amr.188.258.

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As technology development, projected digital fringe pattern is widely used in measuring three- dimensional (3D) shape, even in the presence of surface discontinuities. This paper investigates the reliability and accuracy of two multi-frequency phase unwrapping algorithms by experimental means. The first, which unwraps through a sequence of phase maps produced with exponentially change in spatial frequency with time, is found to be less robust and accuracy than the second, which only use three different frequency to beat new frequency for unwrapping the phase. Through experiment, the best frequ

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36

Heshmat, Samia, Satoshi Tomioka, and Shusuke Nishiyama. "Phase extraction and unwrapping using rotational and direct compensators for digital hologram." Optical Engineering 52, no. 10 (2013): 101910. http://dx.doi.org/10.1117/1.oe.52.10.101910.

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37

Shi, Yan, Zhi-Yi Li, Long Li, and Chang-Hong Liang. "An electromagnetic parameters extraction method for metamaterials based on phase unwrapping technique." Waves in Random and Complex Media 26, no. 4 (2016): 417–33. http://dx.doi.org/10.1080/17455030.2016.1165899.

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38

Esch, Christina, Joël Köhler, Karlheinz Gutjahr, and Wolf-Dieter Schuh. "One-Step Three-Dimensional Phase Unwrapping Approach Based on Small Baseline Subset Interferograms." Remote Sensing 12, no. 9 (2020): 1473. http://dx.doi.org/10.3390/rs12091473.

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One of the most critical steps in a multitemporal D-InSAR analysis is the resolution of the phase ambiguities in the context of phase unwrapping. The Extended Minimum Cost Flow approach is one of the potential phase unwrapping algorithms used in the Small Baseline Subset analysis. In a first step, each phase gradient is unwrapped in time using a linear motion model and, in a second step, the spatial phase unwrapping is individually performed for each interferogram. Exploiting the temporal and spatial information is a proven method, but the two-step procedure is not optimal. In this paper, a me

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39

Pepe, Antonio. "Multi-Temporal Small Baseline Interferometric SAR Algorithms: Error Budget and Theoretical Performance." Remote Sensing 13, no. 4 (2021): 557. http://dx.doi.org/10.3390/rs13040557.

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Multi-temporal interferometric synthetic aperture radar (MT-InSAR) techniques are well recognized as useful tools for detecting and monitoring Earth’s surface temporal changes. In this work, the fundamentals of error noise propagation and perturbation theories are applied to derive the ground displacement products’ theoretical error bounds of the small baseline (SB) differential interferometric synthetic aperture radar algorithms. A general formulation of the least-squares (LS) optimization problem, representing the SB methods implementation’s core, was adopted in this research study. A partic

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40

Gdeisat, Munther. "Performance evaluation and acceleration of Flynn phase unwrapping algorithm using wraps reduction algorithms." Optics and Lasers in Engineering 110 (November 2018): 172–78. http://dx.doi.org/10.1016/j.optlaseng.2018.02.014.

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41

Chen, Curtis W., and Howard A. Zebker. "Network approaches to two-dimensional phase unwrapping: intractability and two new algorithms: erratum." Journal of the Optical Society of America A 18, no. 5 (2001): 1192. http://dx.doi.org/10.1364/josaa.18.001192.

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42

Liu, Xueqian, and Hongyi Yu. "Time-Domain Joint Parameter Estimation of Chirp Signal Based on SVR." Mathematical Problems in Engineering 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/952743.

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Parameter estimation of chirp signal, such as instantaneous frequency (IF), instantaneous frequency rate (IFR), and initial phase (IP), arises in many applications of signal processing. During the phase-based parameter estimation, a phase unwrapping process is needed to recover the phase information correctly and impact the estimation performance remarkably. Therefore, we introduce support vector regression (SVR) to predict the variation trend of instantaneous phase and unwrap phases efficiently. Even though with that being the case, errors still exist in phase unwrapping process because of it

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43

Yamada, Isao, and Kazuhiro Oguchi. "High-resolution estimation of the directions-of-arrival distribution by algebraic phase unwrapping algorithms." Multidimensional Systems and Signal Processing 22, no. 1-3 (2010): 191–211. http://dx.doi.org/10.1007/s11045-010-0141-0.

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Li Jie, 李杰, 王玉荣 Wang Yurong, 孟祥锋 Meng Xiangfeng, et al. "Classification and Comparison of Phase Shift Extraction Algorithms in Generalized Phase-Shifting Interferometry." Chinese Journal of Lasers 40, no. 12 (2013): 1208003. http://dx.doi.org/10.3788/cjl201340.1208003.

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Li, Jie, Yurong Wang, Xiangfeng Meng, Xiulun Yang, and Qingpu Wang. "An evaluation method for phase shift extraction algorithms in generalized phase-shifting interferometry." Journal of Optics 15, no. 10 (2013): 105408. http://dx.doi.org/10.1088/2040-8978/15/10/105408.

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Yuan Qun, 袁群, 高志山 Gao Zhishan, 李建欣 Li Jianxin, 周宇轩 Zhou Yuxuan та 褚光 Chu Guang. "Phase Extraction Algorithms of Multi-Beam Interference Based on π/4 Phase-Shifting Averaging". Acta Optica Sinica 31, № 11 (2011): 1112004. http://dx.doi.org/10.3788/aos201131.1112004.

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QI Zi-wen, 戚子文, 刘炳国 LIU Bing-guo, 张仲海 ZHANG Zhong-hai, 卢丙辉 LU Bing-hui, and 刘国栋 LIU Guo-dong. "Comparison of phase extraction algorithms in testing of phase defects with two-point interference." Chinese Optics 9, no. 4 (2016): 483–90. http://dx.doi.org/10.3788/co.20160904.0483.

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Muanenda, Yonas, Stefano Faralli, Claudio J. Oton, Cheng Cheng, Minghong Yang, and Fabrizio Di Pasquale. "Dynamic phase extraction in high-SNR DAS based on UWFBGs without phase unwrapping using scalable homodyne demodulation in direct detection." Optics Express 27, no. 8 (2019): 10644. http://dx.doi.org/10.1364/oe.27.010644.

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Weng, Jing-Feng, and Yu-Lung Lo. "Integration of robust filters and phase unwrapping algorithms for image reconstruction of objects containing height discontinuities." Optics Express 20, no. 10 (2012): 10896. http://dx.doi.org/10.1364/oe.20.010896.

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Wei, Zhi-Qiang, and Ya-Qiu Jin. "Multi-patch and centre-expansion algorithms for phase unwrapping of large InSAR images with dense residues." International Journal of Remote Sensing 31, no. 10 (2010): 2757–65. http://dx.doi.org/10.1080/01431160903095452.

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