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Journal articles on the topic "Phase extraction; Phase unwrapping; Algorithms"
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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 lowest misfit to the input model is achieved with the MCMC algorithm, at the cost of a much longer computational time. Then, real phases were extracted from a 3D exploration data set at different frequencies. This operation included an automated procedure to isolate the fundamental mode from higher order modes, phase unwrapping in two dimensions, and the estimation of the zero-offset phase. These phases are used to compute traveltimes between each source-receiver couple, which are input into the previously tested tomography algorithms. The resulting phase-velocity maps show good correspondence, highlighting the same geologic structures for all three methods. Finally, individual dispersion curves obtained by the superposition of phase-velocity maps at different frequencies are depth inverted to retrieve a 3D S-wave velocity model.
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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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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 method of detecting landslide disaster combining coherence of SAR image is developed, which makes up for the deficiency of single SAR and optical remote sensing acquisition ability. Especially in bad weather and abnormal climate areas, the speed of disaster emergency and the accuracy of extraction are improved. It is found that the deformation in this area is greatly affected by faults, and there is a tendency of uplift in the southeast plain and western mountainous area, while in the southwest part of the mountain area there is a tendency to sink. This research result provides a basis for decision-making for local disaster prevention and control.
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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 further decomposed into a series of intrinsic mode functions (IMFs) with different energy, using the ensemble empirical mode decomposition with the complementary adaptive noise (EEMDCAN) method. In the EEMDCAN decomposition, positive and negative adaptive noise pairs are added to each IMF layer to effectively eliminate the mode-mixing phenomenon that exists in the original empirical mode decomposition (EMD) method. An energy threshold is designed to select proper IMFs to reconstruct the envelop for high estimation accuracy and low noise effects. Finally, the least-square algorithm is used to do the ambiguous phases unwrapping to obtain the micro-curve, which can be further used to estimate the micro-motion parameters of the warhead. Simulation results show that the proposed method performs well with SNR at −5 dB with an accuracy level of sub-wavelength.
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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 parameters and the knowledge of all the specific geometric and radiometric information about the sensor might complicate the hardware and software requirements. Despite SAR data processing being a well-established imaging technique, the proposed algorithm aims to exploit the SAR coherent illumination, demonstrating the possibility of extracting the reference functions, both in range and azimuth directions, when a strong point scatterer (either natural or manmade) is present in the scene. The Singular Value Decomposition is used to exploit the inherent redundancy present in the raw data matrix, and phase unwrapping and polynomial fitting are used to reconstruct clean versions of the reference functions. Fairly focused images on both synthetic and real raw data matrices without the knowledge of mission parameters and ancillary data information can be obtained; as a byproduct, azimuth beam pattern and estimates of a few other parameters have been extracted from the raw data itself. In a previous paper, authors introduced a preliminary work dealing with this problem and able to obtain good-quality images, if compared to the standard processing techniques. In this work, the proposed technique is described, and performance parameters are extracted to compare the proposed approach to RD, showing good adherence of the focused images and pulse responses.
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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 unsatisfactory results even in the presence of low‐phase aliasing, whereas 2-D phase unwrapping deals with the complete problem, overcoming the limitations of 1-D unwrapping. The 2-D unwrapped phase is obtained as the solution of a variational problem that minimizes the differences between the gradients of the wrapped and unwrapped phase. The Euler equation is then integrated using the boundary conditions obtained from the wrapped phase. In addition to determining a unique unwrapped phase, this approach has the advantage that it limits the influence of phase aliasing. It is also more attractive than iterative 1-D unwrapping since it limits the propagation of unwrapping errors. Error propagation in phase unwrapping can strongly influence the result of any phase processing. Examples in this paper apply 2-D phase unwrapping to problems of refraction statics and interferometrical imaging using a remote system (SAR) and demonstrate how limited error propagation allows phase processing.
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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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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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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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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 phase unwrapping problem becomes non-trivial. In this paper, we investigate the performance of three different phase unwrapping algorithms when applied to three-dimensional (two spatial axes and one time axis) phase contrast datasets. A simple one-dimensional temporal unwrapping algorithm, a more complex and robust three-dimensional unwrapping algorithm and a novel velocity encoding unwrapping algorithm which involves unwrapping along a fourth dimension (the ‘velocity encoding’ direction) are discussed, and results from the three are presented and compared. It is shown that compared to the traditional approach, both dynamic range and signal-to-noise ratio can be increased by a factor of up to five times, which demonstrates considerable promise for a possible eventual clinical implementation. The results are also of direct relevance to users of any other technique delivering time-varying two-dimensional phase images, such as dynamic speckle interferometry and synthetic aperture radar.
Dissertations / Theses on the topic "Phase extraction; Phase unwrapping; Algorithms"
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Green, Roger James. "The use of Fourier transform methods in automatic fringe pattern analysis." Thesis, King's College London (University of London), 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.307203.
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Pallikarakis, Christos A. "Development of temporal phase unwrapping algorithms for depth-resolved measurements using an electronically tuned Ti:Sa laser." Thesis, Loughborough University, 2017. https://dspace.lboro.ac.uk/2134/23918.
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This thesis is concerned with (a) the development of full-field, multi-axis and phase contrast wavelength scanning interferometer, using an electronically tuned CW Ti:Sa laser for the study of depth resolved measurements in composite materials such as GFRPs and (b) the development of temporal phase unwrapping algorithms for depth re-solved measurements. Item (a) was part of the ultimate goal of successfully extracting the 3-D, depth-resolved, constituent parameters (Young s modulus E, Poisson s ratio v etc.) that define the mechanical behaviour of composite materials like GFRPs. Considering the success of OCT as an imaging modality, a wavelength scanning interferometer (WSI) capable of imaging the intensity AND the phase of the interference signal was proposed as the preferred technique to provide the volumetric displacement/strain fields (Note that displacement/strain fields are analogous to phase fields and thus a phase-contrast interferometer is of particular interest in this case). These would then be passed to the VFM and yield the sought parameters provided the loading scheme is known. As a result, a number of key opto-mechanical hardware was developed. First, a multiple channel (x6) tomographic interferometer realised in a Mach-Zehnder arrangement was built. Each of the three channels would provide the necessary information to extract the three orthogonal displacement/strain components while the other three are complementary and were included in the design in order to maximize the penetration depth (sample illuminated from both sides). Second, a miniature uniaxial (tensile and/or compression) loading machine was designed and built for the introduction of controlled and low magnitude displacements. Last, a rotation stage for the experimental determination of the sensitivity vectors and the re-registration of the volumetric data from the six channels was also designed and built. Unfortunately, due to the critical failure of the Ti:Sa laser data collection using the last two items was not possible. However, preliminary results at a single wavelength suggested that the above items work as expected. Item (b) involved the development of an optical sensor for the dynamic monitoring of wavenumber changes during a full 100 nm scan. The sensor is comprised of a set of four wedges in a Fizeau interferometer setup that became part of the multi-axis interferometer (7th channel). Its development became relevant due to the large amount of mode-hops present during a full scan of the Ti:Sa source. These are associated to the physics of the laser and have the undesirable effect of randomising the signal and thus preventing successful depth reconstructions. The multi-wedge sensor was designed so that it provides simultaneously high wavenumber change resolution and immunity to the large wavenumber jumps from the Ti:Sa. The analysis algorithms for the extraction of the sought wavenumber changes were based on 2-D Fourier transform method followed by temporal phase unwrapping. At first, the performance of the sensor was tested against that of a high-end commercial wavemeter for a limited scan of 1nm. A root mean square (rms) difference in measured wavenumber shift between the two of ~4 m-1 has been achieved, equivalent to an rms wavelength shift error of ~0.4 pm. Second, by resampling the interference signal and the wavenumber-change axis onto a uniformly sampled k-space, depth resolutions that are close to the theoretical limits were achieved for scans of up to 37 nm. Access of the full 100 nm range that is characterised by wavelength steps down to picometers level was achieved by introducing a number of improvements to the original temporal phase unwrapping algorithm reported in ref [1] tailored to depth resolved measurements. These involved the estimation and suppression of intensity background artefacts, improvements on the 2-D Fourier transform phase detection based on a previously developed algorithm in ref [2] and finally the introduction of two modifications to the original TPU. Both approaches are adaptive and involve signal re-referencing at regular intervals throughout the scan. Their purpose is to compensate for systematic and non-systematic errors owing to a small error in the value of R (a scaling factor applied to the lower sensitivity wedge phase-change signal used to unwrap the higher sensitivity one), or small changes in R with wavelength due to the possibility of a mismatch in the refractive dispersion curves of the wedges and/or a mismatch in the wedge angles. A hybrid approach combining both methods was proposed and used to analyse the data from each of the four wedges. It was found to give the most robust results of all the techniques considered, with a clear Fourier peak at the expected frequency, with significantly reduced spectral artefacts and identical depth resolutions for all four wedges of 2.2 μm measured at FWHM. The ability of the phase unwrapping strategy in resolving the aforementioned issues was demonstrated by successfully measuring the absolute thickness of four fused silica glasses using real experimental data. The results were compared with independent micrometer measurements and showed excellent agreement. Finally, due to the lack of additional experimental data and in an attempt to justify the validity of the proposed temporal phase unwrapping strategy termed as the hybrid approach, a set of simulations that closely matched the parameters characterising the real experimental data set analysed were produced and were subsequently analysed. The results of this final test justify that the various fixes included in the hybrid approach have not evolved to solve the problems of a particular data set but are rather of general nature thereby, highlighting its importance for PC-WSI applications concerning the processing and analysis of large scans.
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Desroches, Damien. "Extraction de hauteurs d'eau géolocalisées par interférométrie radar dans le cas de SWOT." Thesis, Toulouse 3, 2016. http://www.theses.fr/2016TOU30030/document.
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La mission SWOT (Surface Water and Ocean Topography), menée par le CNES et le JPL et dont le lancement est prévu pour 2020, marque un tournant majeur pour l'altimétrie spatiale, à la fois en océanographie et en hydrologie continentale. Il s'agit de la première mission interférométrique SAR dont l'objectif spécifique est la mesure de la hauteur des eaux. L'instrument principal de la mission, KaRIn, un radar interférométrique en bande Ka, présente des caractéristiques particulières : angle de visée proche du nadir (0.6 à 3.9°), faible longueur d'onde (8.6 mm) et courte base stéréoscopique (10 m). Ces spécificités techniques entrainent des particularités propres à SWOT, à la fois en termes de phénoménologie et de traitement des données. Par ailleurs, du fait de la nature et du grand volume des données, de nouvelles méthodes de traitement sont envisagées, qui se distinguent de celles des missions interférométriques antérieures. Pour le mode " Low Rate " (LR) dédié à l'océanographie, une grande partie du traitement se déroulera à bord pour limiter le volume de données à transmettre au sol. Le mode " High Rate" (HR) visant principalement l'hydrologie continentale, présente lui aussi des originalités en termes de traitement, essentiellement réalisé au sol, de par la grande diversité de structure des surfaces d'eau qui seront observées. Pour les deux modes, la stratégie d'inversion de la phase en hauteurs géolocalisées ne peut être calquée sur celles des missions antérieures, fondées sur le déroulement spatial de la phase interférométrique. L'approche retenue est d'utiliser, autant que possible, un modèle numérique de terrain (MNT) de référence pour lever l'ambiguïté de phase et procéder directement à l'inversion de hauteur. Ceci permet à la fois de gagner en temps de traitement et de s'affranchir de l'utilisation des points de contrôle, difficiles à obtenir sur les océans comme sur les continents, du fait des variations de niveau d'eau et un rapport signal à bruit très faible sur les zones terrestres. Dans les cas où la précision du MNT de référence n'est pas suffisante pour assurer correctement le déroulement de la phase, des méthodes visant à détecter et réduire les erreurs sont proposées. Afin de faciliter l'utilisation des hauteurs géolocalisées issues de la phase l'interférométrique en mode HR, nous proposons une méthode qui permet d'améliorer considérablement la géolocalisation des produits, sans dégrader l'information de hauteur d'eau<br>The SWOT mission (Surface Water and Ocean Topography), conducted by CNES and JPL, and scheduled for launch in 2020, is a major step forward for spaceborne altimetry, both for oceanography and continental hydrology. It is the first interferometric SAR mission whose specific objective is the measurement of water surface height. The main instrument of the mission, KaRIn, a Ka-band Radar Interferometer, has particular characteristics: very low incidence angle (from 0.6 to 3.9°), short wavelength (8.6 mm), and short baseline (10 m). This technical configuration leads to properties that are specific to SWOT, both in terms of phenomenology and data processing. Moreover, due to the nature and the huge volume of data, new processing methods, different from those used in previous interferometric mission, are considered. For the Low Rate (LR) mode dedicated to oceanography, a large part of the processing will take place onboard to limit the data volume transmitted to ground. The High Rate (HR) mode, mainly targeting continental hydrology, also present original characteristics in terms of processing, essentially conducted on ground, due to the large diversity in the structure of the observed water surfaces. In both modes, the strategy for conversion of phase into geolocated heights cannot be directly based on those of previous missions, relying on spatial phase unwrapping. The approach retained here is to use, as far as possible, a reference Digital Terrain Model (DTM) to remove the phase ambiguity and proceed directly to height inversion. This allows both to reduce the computing time and to avoid the need for ground control points, which are difficult to obtain both over oceans and continental surfaces, due to varying water level and very low signal-to-noise ratio over land. For cases where the precision of reference DTM is not good enough to ensure a correct phase unwrapping, methods to detect and reduce the errors are proposed. To facilitate the use of the geolocated heights derived from the interferometric phase in HR mode, we propose a method that permits to significantly improve the geolocation of the products, without degrading the water height information
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Osmanoglu, Batuhan. "Applications and Development of New Algorithms for Displacement Analysis Using InSAR Time Series." Scholarly Repository, 2011. http://scholarlyrepository.miami.edu/oa_dissertations/622.
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Time series analysis of Synthetic Aperture Radar Interferometry (InSAR) data has become an important scientific tool for monitoring and measuring the displacement of Earth’s surface due to a wide range of phenomena, including earthquakes, volcanoes,landslides, changes in ground water levels, and wetlands. Time series analysis is a product of interferometric phase measurements, which become ambiguous when the observed motion is larger than half of the radar wavelength. Thus, phase observations must first be unwrapped in order to obtain physically meaningful results. Persistent Scatterer Interferometry (PSI), Stanford Method for Persistent Scatterers (StaMPS), Short Baselines Interferometry (SBAS) and Small Temporal Baseline Subset (STBAS)algorithms solve for this ambiguity using a series of spatio-temporal unwrapping algorithms and filters. In this dissertation, I improve upon current phase unwrapping algorithms, and apply the PSI method to study subsidence in Mexico City. PSI was used to obtain unwrapped deformation rates in Mexico City (Chapter 3),where ground water withdrawal in excess of natural recharge causes subsurface, clay-rich sediments to compact. This study is based on 23 satellite SAR scenes acquired between January 2004 and July 2006. Time series analysis of the data reveals a maximum line-of-sight subsidence rate of 300mm/yr at a high enough resolution that individual subsidence rates for large buildings can be determined. Differential motion and related structural damage along an elevated metro rail was evident from the results. Comparison of PSI subsidence rates with data from permanent GPS stations indicate root mean square(RMS) agreement of 6.9 mm/yr, about the level expected based on joint data uncertainty.The Mexico City results suggest negligible recharge, implying continuing degradation and loss of the aquifer in the third largest metropolitan area in the world. Chapters 4 and 5 illustrate the link between time series analysis and three-dimensional (3-D) phase unwrapping. Chapter 4 focuses on the unwrapping path.Unwrapping algorithms can be divided into two groups, path-dependent and path-independent algorithms. Path-dependent algorithms use local unwrapping functions applied pixel-by-pixel to the dataset. In contrast, path-independent algorithms use global optimization methods such as least squares, and return a unique solution. However, when aliasing and noise are present, path-independent algorithms can underestimate the signal in some areas due to global fitting criteria. Path-dependent algorithms do not underestimate the signal, but, as the name implies, the unwrapping path can affect the result. Comparison between existing path algorithms and a newly developed algorithm based on Fisher information theory was conducted. Results indicate that Fisher information theory does indeed produce lower misfit results for most tested cases. Chapter 5 presents a new time series analysis method based on 3-D unwrapping of SAR data using extended Kalman filters. Existing methods for time series generation using InSAR data employ special filters to combine two-dimensional (2-D) spatial unwrapping with one-dimensional (1-D) temporal unwrapping results. The new method,however, combines observations in azimuth, range and time for repeat pass interferometry. Due to the pixel-by-pixel characteristic of the filter, the unwrapping path is selected based on a quality map. This unwrapping algorithm is the first application of extended Kalman filters to the 3-D unwrapping problem. Time series analyses of InSAR data are used in a variety of applications with different characteristics. Consequently, it is difficult to develop a single algorithm that can provide optimal results in all cases, given that different algorithms possess a unique set of strengths and weaknesses. Nonetheless, filter-based unwrapping algorithms such as the one presented in this dissertation have the capability of joining multiple observations into a uniform solution, which is becoming an important feature with continuously growing datasets.
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Jing-FengWeng and 翁精鋒. "Robust Filtering and Phase Unwrapping Algorithms for Noise and Holes in Digital Image Processing." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/31089946044497287666.
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博士<br>國立成功大學<br>機械工程學系碩博士班<br>101<br>Interferometric system can capture the 2 dimensional interferograms, and then the captured images are converted into one 3 dimensional unwrapped phase map by using the image reconstruction process. The intact process is as follows. First, the 2 dimensional interferograms are converted into the wrapped phase map. Second, the wrapped phase map is unwrapped by the phase unwrapping algorithm. Finally, the 3 dimensional unwrapped phase map is obtained. Unfortunately, the noise which causes the phase unwrapping algorithm to fail usually occurs in the captured interferograms. This study classifies the common noise in current researches as three types of noise, namely speckle noise, residual noise, noise at the height discontinuities. The current researches focus on discussing one of these three types of noise. By contrast, this study discusses all of these three types of noise simultaneously. This study proposes the novel detection algorithm, namely the noise and phase jump detection scheme. This detection scheme can detect the noise and the phase jump positions in the wrapped phase map simultaneously, and then marks into two maps, namely the noise map and the phase jump map. Unfortunately, if the intensity of noise is too turbulent or the line of phase jump is too irregular, this detection scheme will produce the few detection errors.
In order to remove the noise and the detection errors, this study proposes the non-linear filtering algorithms, which combine the noise and phase jump detection scheme, and the adaptive median filter. Fortunately, the noise and the detection errors are effectively removed by the proposed filtering algorithms. In addition, the proposed filtering algorithms can reduce the degraded situation of smearing a phase jump located the 2π-high position and 0-low position, namely the shifting error. Importantly, the proposed filtering algorithms effectively combine with the two different types of phase unwrapping algorithms, namely path-dependent algorithms and path-independent algorithms, to remove the noise and unwrap the wrapped phase map simultaneously.
For the common image reconstruction, the filtering algorithm removes the noise in the wrapped phase map prior to the performance of the phase unwrapping algorithm. However, this study proposes the opposite method, using the novel rotation algorithm to unwrap the wrapped phase map prior to the performance of the filtering algorithm. Generally speaking, the common researches operate the phase jumps by shifting 2π, and eliminate the phase discontinuity between 2π-high and 0-low positions to become the continuous phase. By contrast, in this study, the rotation approach operates the phase jumps to obtain the continuous phase, rather than the approach of shifting 2π. The information of the rotation algorithm, including the magnitude and direction, is based on the phase jump map. It is noted that this rotation algorithm does not smear the phase jumps and saves the noise and holes. Finally, the filtering algorithm is used to remove the noise kept by this rotation algorithm, and the 3 dimensional reconstruction is completed.
Finally, this study modifies the theory of the noise and phase jump detection scheme, and proposes the modified phase jump map. One phase jump contains a 2π-high position and a 0-low position. Unfortunately, this original detection scheme only finds a 2π-high position and misses the corresponding 0-low position, or finds a 0-low position and misses the corresponding 2π-high position. The modified phase jump map is successfully capable of detecting both of 2π-high position and 0-low position. Moreover, it effectively reduces the detection error produced by the original detection scheme. The noise map and the modified phase jump map can be effectively applied to the phase unwrapping and filtering algorithms.
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Hsu, Kuan-Yu, and 徐冠宇. "Research and Development of Two-dimensional Windowed Fourier Transform Based Phase Unwrapping Algorithms for Interference Fringe Analysis." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/48496782676978504215.
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碩士<br>國立臺灣大學<br>應用力學研究所<br>103<br>The main application scenario of this thesis is using Michelson interferometer as the non-destructive testing method, which measures tiny deformation of objects by retrieving the phase of the interference fringes generated due to deformation. To retrieve the deformation induced phase, we measure the interference fringe first and then analyze the phase by a process called phase-unwrapping. Trying to take advantages of the rapid development of CCD/CMOS, which provides a platform to significantly increase the spatial modulation frequency, Fourier transform based phase-unwrapping algorithm was adopted in this thesis.
Trying to remove the bottleneck associated with phase-unwrapping, Fourier spectrum of interference fringe obtained with pre-introduced spatial carrier frequency so as to distinguish the correct direction of object deformation, was adopted. This approach first proposed by Mitsuo Takeda in 1981 is similar to the Doppler interferometer that solves the directional ambiguity by providing a frequency shift. The only difference lies on either temporal or spatial frequency was pre-introduced. It is with this pre-introduced spatial frequency shift, retrieving the phase information by using only one interference fringe (intensity map) becomes feasible. More specifically, the above-mentioned approach circumvent the disadvantages associated with phase-shifting algorithms such as the 5,1 phase-shifting algorithm, etc. that require more than one image to analyze the phase information. It is to be noted that retrieve phase map from intensity map with a single intensity map not only saves valuable computation time but also provides us with a platform for dynamic measurement as high-speed camera can be used to record the time-varying interference fringes (intensity maps) first and then compute phase map after the deformation is completed.
Furthermore, in dealing with problems related to valid or effective functional domain (domain with valid interference fringes) and regions with vastly different signal-to-noise ratios (SNR), Windowed Fourier Transform (WFT) first proposed by Qian Kemao in 2004 was also introduced in this thesis. For phase unwrapping, this study used Least-Squares method to get the information of measured object rapidly. It is to be noted that this method leads to the use of Fourier transform to solve a Poisson’s equation with Neumann boundary conditions.
As Fourier transform algorithm was used in converting the intensity map to the phase map and then perform phase-unwrapping, these algorithms developed in this thesis provides us with an opportunity to adopt the many attempts over the last 50 years in speeding up the computation time associated with Fourier transform. Some of these methods include Fast Fourier Transform (FFT), Sparse Fast Fourier Transform (SFFT) and hardware solution such as Graphic Processing Unit (GPU), etc. All of which can then be integrated to develop an ultrafast phase analysis system, which can found applications potentials ranging from in-situ real-time optical field measurement, production-need driven automatic optical inspection (AOI), etc.
This works completed throughout this research include setting the Michelson interferometer, integrating MATLAB and LabVIEW to transfer experimentally induced optical intensity map to computers for signal post-processing, etc. To verify the overall effectiveness of this system, this study analyzed the phase information by measuring the mirror and stainless steel deformation by using the Michelson interferometer set up. The results of unwrapped phase matched the object deformation, successfully validated the accuracy and the feasibility of integrating these algorithms in this thesis.
Books on the topic "Phase extraction; Phase unwrapping; Algorithms"
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D, Pritt Mark, ed. Two-dimensional phase unwrapping: Theory, algorithms, and software. Wiley, 1998.
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Ghiglia, Dennis C., and Mark D. Pritt. Two-Dimensional Phase Unwrapping: Theory, Algorithms, and Software. Wiley & Sons, Incorporated, John, 2008.
Find full textBook chapters on the topic "Phase extraction; Phase unwrapping; Algorithms"
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Baldi, Antonio, Filippo Bertolino, and Francesco Ginesu. "Phase Unwrapping Algorithms: A Comparison." In Interferometry in Speckle Light. Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-642-57323-1_59.
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Heshmat, Samia, Satoshi Tomioka, and Shusuke Nishiyama. "Performance Evaluation of Phase Unwrapping Algorithms for Noisy Phase Measurements." In Fringe 2013. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-36359-7_20.
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McGlinchey, S., and C. Fyfe. "Automatic Extraction of Phase and Frequency Information from Raw Voice Data." In Artificial Neural Nets and Genetic Algorithms. Springer Vienna, 1998. http://dx.doi.org/10.1007/978-3-7091-6492-1_22.
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Amaya, Ivan, Cristian Jiménez, and Rodrigo Correa. "Phase Equilibrium Description of a Supercritical Extraction System Using Metaheuristic Optimization Algorithms." In Bioinspired Heuristics for Optimization. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-95104-1_3.
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Wu, QingE, and Weidong Yang. "Feature Extraction Algorithms to Color Image." In Computer Vision. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-5204-8.ch016.
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The existing image processing algorithms mainly studied on feature extraction of gray image with one-dimensional parameter, such as edges, corners. However, the extraction of some characteristic points to color image with three-dimensional parameters, such as the extraction of color edge, corner points, inflection points, etc., is an image problem to be urgently solved. In order to carry out a fast and accurate feature extraction on color image, this paper proposes two types of extraction algorithms to color edge and corner points of color image, i.e., similar color segment algorithm and pixel probabilistic algorithm, compares with the two algorithms, gives the two algorithms are used to different color distribution situations, as well as shows the extraction effect of color by the combination of the two algorithms, moreover, gives the contrast experiment and effect analysis of the two algorithms. To compare the similar color segment algorithm with the probabilistic algorithm, experimental results show that the similar color segment algorithm is better than the pixel probabilistic algorithm under the more obvious color edge, because it has the better edge detection, stronger anti-noise ability, faster processing speed and other advantages. Under the transition phase of color edge is gentle or color edge is no clear, the image detection effect of the pixel probabilistic algorithm is better than that of the similar color segment algorithm. But the combinative effect of the two algorithms is the best in this case, which is more close to the color effect of original image. Moreover, this paper analyzes the performance of the similar color segment algorithm, and gives the comparison of the proposed two algorithms and existing classical algorithms used usually to feature extraction of color image. The two algorithms proposed and these researches development in this paper have not only enriched the contents of image processing algorithms, but also provide a solution tool for image segmentation, feature extraction to target, precise positioning, etc., such as extraction of complexion, physiological color photographs processing, feature extraction of ionosphere, detection and extraction of biological composition of oceans, to be applied to a lots of departments, such as the police, hospital departments, surgery, polar department, and so on, as well as provide a way of thinking for the rapid, accurate detection of case, surgery, scientific research information search.
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Wu, QingE, and Weidong Yang. "Feature Extraction Algorithms to Color Image." In Examining Information Retrieval and Image Processing Paradigms in Multidisciplinary Contexts. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-1884-6.ch002.
Full textAbstract:
The existing image processing algorithms mainly studied on feature extraction of gray image with one-dimensional parameter, such as edges, corners. However, the extraction of some characteristic points to color image with three-dimensional parameters, such as the extraction of color edge, corner points, inflection points, etc., is an image problem to be urgently solved. In order to carry out a fast and accurate feature extraction on color image, this paper proposes two types of extraction algorithms to color edge and corner points of color image, i.e., similar color segment algorithm and pixel probabilistic algorithm, compares with the two algorithms, gives the two algorithms are used to different color distribution situations, as well as shows the extraction effect of color by the combination of the two algorithms, moreover, gives the contrast experiment and effect analysis of the two algorithms. To compare the similar color segment algorithm with the probabilistic algorithm, experimental results show that the similar color segment algorithm is better than the pixel probabilistic algorithm under the more obvious color edge, because it has the better edge detection, stronger anti-noise ability, faster processing speed and other advantages. Under the transition phase of color edge is gentle or color edge is no clear, the image detection effect of the pixel probabilistic algorithm is better than that of the similar color segment algorithm. But the combinative effect of the two algorithms is the best in this case, which is more close to the color effect of original image. Moreover, this paper analyzes the performance of the similar color segment algorithm, and gives the comparison of the proposed two algorithms and existing classical algorithms used usually to feature extraction of color image. The two algorithms proposed and these researches development in this paper have not only enriched the contents of image processing algorithms, but also provide a solution tool for image segmentation, feature extraction to target, precise positioning, etc., such as extraction of complexion, physiological color photographs processing, feature extraction of ionosphere, detection and extraction of biological composition of oceans, to be applied to a lots of departments, such as the police, hospital departments, surgery, polar department, and so on, as well as provide a way of thinking for the rapid, accurate detection of case, surgery, scientific research information search.
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El Hariri, Esraa, Nashwa El-Bendary, Aboul Ella Hassanien, and Amr Badr. "Automated Ripeness Assessment System of Tomatoes Using PCA and SVM Techniques." In Computer Vision and Image Processing in Intelligent Systems and Multimedia Technologies. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-6030-4.ch006.
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One of the prime factors in ensuring a consistent marketing of crops is product quality, and the process of determining ripeness stages is a very important issue in the industry of (fruits and vegetables) production, since ripeness is the main quality indicator from the customers' perspective. To ensure optimum yield of high quality products, an objective and accurate ripeness assessment of agricultural crops is important. This chapter discusses the problem of determining different ripeness stages of tomato and presents a content-based image classification approach to automate the ripeness assessment process of tomato via examining and classifying the different ripeness stages as a solution for this problem. It introduces a survey about resent research work related to monitoring and classification of maturity stages for fruits/vegetables and provides the core concepts of color features, SVM, and PCA algorithms. Then it describes the proposed approach for solving the problem of determining different ripeness stages of tomatoes. The proposed approach consists of three phases, namely pre-processing, feature extraction, and classification phase. The classification process depends totally on color features (colored histogram and color moments), since the surface color of a tomato is the most important characteristic to observe ripeness. This approach uses Principal Components Analysis (PCA) and Support Vector Machine (SVM) algorithms for feature extraction and classification, respectively.
Conference papers on the topic "Phase extraction; Phase unwrapping; Algorithms"
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Liu, Sheng, and Lian X. Yang. "Phase unwrapping by a noise immune algorithm: fringe estimation, quality segmentation, and sorted extraction." In SPIE Optics + Photonics. SPIE, 2006. http://dx.doi.org/10.1117/12.679260.
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Hao, Yudong, Yang Zhao, and Dacheng Li. "Design of temporal phase unwrapping algorithms." In International Symposium on Photonics and Applications, edited by Yee Loy Lam, Koji Ikuta, and Metin S. Mangir. SPIE, 1999. http://dx.doi.org/10.1117/12.368502.
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Jing, Chao, Ping Zhou, and Yimo Zhang. "Phase extracting and unwrapping algorithm of electrical speckle shearing phase-shifting pattern interferometry." In SPIE/COS Photonics Asia, edited by Yunlong Sheng, Chongxiu Yu, and Changhe Zhou. SPIE, 2016. http://dx.doi.org/10.1117/12.2247750.
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Du, Rui, and Lijia Yang. "Phase unwrapping algorithms in laser propagation simulation." In ISPDI 2013 - Fifth International Symposium on Photoelectronic Detection and Imaging, edited by Jun Ohta, Nanjian Wu, and Binqiao Li. SPIE, 2013. http://dx.doi.org/10.1117/12.2035045.
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Arminger, Bernd R., Bernhard G. Zagar, and Bettina Heise. "Comparison of Various Algorithms for Phase Unwrapping in Optical Phase Microscopy." In 2007 IEEE Instrumentation & Measurement Technology Conference IMTC 2007. IEEE, 2007. http://dx.doi.org/10.1109/imtc.2007.379082.
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Onat, Emrah, and Yakup Ozkazanc. "An Analysis on Path Following Phase Unwrapping Algorithms." In 2020 28th Signal Processing and Communications Applications Conference (SIU). IEEE, 2020. http://dx.doi.org/10.1109/siu49456.2020.9302505.
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Köhler, Johannes, Jan C. Peters, Tobias Nöll, and Didier Stricker. "Improvement of Phase Unwrapping Algorithms by Epipolar Constraints." In International Conference on Computer Vision Theory and Applications. SCITEPRESS - Science and and Technology Publications, 2015. http://dx.doi.org/10.5220/0005271404720479.
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Kotlicki, Krzysztof. "New algorithms for phase unwrapping: implementation and testing." In Acousto-Optics and Applications III, edited by Antoni Sliwinski, Bogumil B. J. Linde, and Piotr Kwiek. SPIE, 1998. http://dx.doi.org/10.1117/12.330507.
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Lyuboshenko, Igor, and Henri Maitre. "Robust algorithms for phase unwrapping in SAR interferometry." In Aerospace Remote Sensing '97, edited by Jacky Desachy and Shahram Tajbakhsh. SPIE, 1997. http://dx.doi.org/10.1117/12.295599.
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Li, Yongguo. "Study on phase unwrapping algorithms in interferogram processing." In 3rd International Symposium on Advanced Optical Manufacturing and testing technologies: Optical test and Measurement Technology and Equipment, edited by Junhua Pan, James C. Wyant, and Hexin Wang. SPIE, 2007. http://dx.doi.org/10.1117/12.783659.
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