Relevant bibliographies by topics / Unwrapping

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
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Academic literature on the topic 'Unwrapping'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Unwrapping"

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Kang, Y., C. Y. Zhao, Q. Zhang, and C. S. Yang. "INSAR UNWRAPPING ERROR CORRECTION BASED ON QUASI-ACCURATE DETECTION OF GROSS ERRORS (QUAD)." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3 (April 30, 2018): 723–28. http://dx.doi.org/10.5194/isprs-archives-xlii-3-723-2018.

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Unwrapping error is a common error in the InSAR processing, which will seriously degrade the accuracy of the monitoring results. Based on a gross error correction method, Quasi-accurate detection (QUAD), the method for unwrapping errors automatic correction is established in this paper. This method identifies and corrects the unwrapping errors by establishing a functional model between the true errors and interferograms. The basic principle and processing steps are presented. Then this method is compared with the L1-norm method with simulated data. Results show that both methods can effectively suppress the unwrapping error when the ratio of the unwrapping errors is low, and the two methods can complement each other when the ratio of the unwrapping errors is relatively high. At last the real SAR data is tested for the phase unwrapping error correction. Results show that this new method can correct the phase unwrapping errors successfully in the practical application.
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Santino, Jack, and Daniel Miller. "Unwrapping Christmas." Contemporary Sociology 24, no. 2 (March 1995): 262. http://dx.doi.org/10.2307/2076909.

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Young, Kevin D. "Unwrapping Bacteria." PLoS Genetics 10, no. 1 (January 2, 2014): e1004054. http://dx.doi.org/10.1371/journal.pgen.1004054.

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Podell, Richard N. "Unwrapping urticaria." Postgraduate Medicine 78, no. 8 (December 1985): 83–97. http://dx.doi.org/10.1080/00325481.1985.11699221.

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Lewis, Anne C. "Unwrapping Teaching." Phi Delta Kappan 85, no. 6 (February 2004): 419–20. http://dx.doi.org/10.1177/003172170408500602.

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Maddox, Richard, and Daniel Miller. "Unwrapping Christmas." Sociology of Religion 55, no. 4 (1994): 496. http://dx.doi.org/10.2307/3711993.

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Tauxe, Caroline S., and Daniel Miller. "Unwrapping Christmas." Man 29, no. 3 (September 1994): 744. http://dx.doi.org/10.2307/2804387.

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Talbot, Nicholas J. "Unwrapping theLaccariagenome." New Phytologist 180, no. 2 (October 2008): 259–60. http://dx.doi.org/10.1111/j.1469-8137.2008.02636.x.

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Lemke, Greg. "Unwrapping myelination." Nature 383, no. 6599 (October 1996): 395–96. http://dx.doi.org/10.1038/383395a0.

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He, Guo Tian, Ying Chun Ran, Li Song, and Zhong Xun Wang. "Study on a Rotary Self-Check Phase Unwrapping Algorithm." Applied Mechanics and Materials 246-247 (December 2012): 204–7. http://dx.doi.org/10.4028/www.scientific.net/amm.246-247.204.

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This article presented a rotary self-check phase unwrapping algorithm. The algorithm was mainly to process phase unwrapping for the phase main value got from Interferometer in accurately measuring object surface topography, and then accurately restored the object surface topography. The object surface topography measured by Interferometer generally tended to be smooth, the phase unwrapping was not difficult without noise interference. The algorithm processed phase unwrapping by the path of gradually rotational diffusion from the middle to the around in the wrapped phase map, at the same time the check for the error was carried out. It used the median filter technology to process the phase unwrapping error, and avoided the transmission of phase unwrapping error, had a greater inhibitory effect on the noises. This method did not identify the residuals, had small amount of operations, and Unwrapping velocity was several times faster than the fastest traditional branch blocking algorithm.
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Dissertations / Theses on the topic "Unwrapping"

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AI-Sawaf, Firas. "Efficient phase unwrapping." Thesis, Cranfield University, 2005. http://hdl.handle.net/1826/3960.

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In the field of optical interferometry, two-dimensional projections of light interference patterns are often analysed in order to obtain measurements of interest. Such interference patterns, or interferograms, contain phase information which is inherently wrapped onto the range -t to it. Phase unwrapping is the processes of the restoration of the unknown multiple of 2ir, and therefore plays a major role in the overall process of interferogram analysis. Unwrapping phase information correctly becomes a challenging process in the presence of noise. This is particularly the case for speckle interferograms, which are noisy by nature. Many phase unwrapping algorithms have been devised by workers in the field, in order to achieve better noise rejection and improve the computational performance. This thesis focuses on the computational efficiency aspect, and picks as a starting point an existing phase unwrapping algorithm which has been shown to have inherent noise immunity. This is, namely, the tile-based phase unwrapping method, which attains its enhanced noise immunity through the application of the minimum spanning tree concept from graph theory. The thesis examines the problem of finding a minimum spanning tree, for this particular application, from a graph theory perspective, and shows that a more efficient class of minimum spanning tree algorithms can be applied to the problem. The thesis then goes on to show how a novel algorithm can be used to significantly reduce the size of the minimum spanning tree problem in an efficient manner.
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Al-Sawaf, Firas. "Efficient phase unwrapping." Thesis, Cranfield University, 2005. http://dspace.lib.cranfield.ac.uk/handle/1826/3960.

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In the field of optical interferometry, two-dimensional projections of light interference patterns are often analysed in order to obtain measurements of interest. Such interference patterns, or interferograms, contain phase information which is inherently wrapped onto the range -t to it. Phase unwrapping is the processes of the restoration of the unknown multiple of 2ir, and therefore plays a major role in the overall process of interferogram analysis. Unwrapping phase information correctly becomes a challenging process in the presence of noise. This is particularly the case for speckle interferograms, which are noisy by nature. Many phase unwrapping algorithms have been devised by workers in the field, in order to achieve better noise rejection and improve the computational performance. This thesis focuses on the computational efficiency aspect, and picks as a starting point an existing phase unwrapping algorithm which has been shown to have inherent noise immunity. This is, namely, the tile-based phase unwrapping method, which attains its enhanced noise immunity through the application of the minimum spanning tree concept from graph theory. The thesis examines the problem of finding a minimum spanning tree, for this particular application, from a graph theory perspective, and shows that a more efficient class of minimum spanning tree algorithms can be applied to the problem. The thesis then goes on to show how a novel algorithm can be used to significantly reduce the size of the minimum spanning tree problem in an efficient manner.
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Karout, Salah. "Two-dimensional phase unwrapping." Thesis, Liverpool John Moores University, 2007. http://researchonline.ljmu.ac.uk/5814/.

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Marlow, Gregory. "Week 08, Video 04: UV Unwrapping." Digital Commons @ East Tennessee State University, 2020. https://dc.etsu.edu/digital-animation-videos-oer/58.

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Kinell, Lars. "Shape measurements using temporal phase unwrapping." Licentiate thesis, Luleå tekniska universitet, 2000. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-25651.

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This licentiate thesis is devoted to shape measurements using two different optical methods. The first one is a classical triangulation method, which uses projected fringes. The second one is a new interferometric method, which uses wavelength scanning. Both are whole field measuring methods. The main goal of the project has been to analyse the performance of an analysis scheme for absolute shape measurements called temporal phase unwrapping. This method permits the user to determine the absolute distance from the detector (usually a CCD-detector) to the object. A generalised version of the temporal phase unwrapping scheme is called reduced temporal phase unwrapping. The scheme uses an arbitrary number of fringe maps with varied fringe pitch, to calculate phase (shape). A thorough investigation is made of the performance of this algorithm. A single channel and a multi channel approach is considered. Expressions are found that relates the physical quantities to phase errors. In these simulations the single channel approach was found to be the most robust one. Expressions that relate the measurement accuracy and the unwrapping reliability, respectively, to the reduction of the fringe sequence were also found. As expected the measurement accuracy is not affected by a shorter fringe sequence while a significant reduction in the unwrapping reliability is found, as compared to the complete negative exponential sequence. The strength of reduced temporal phase unwrapping is demonstrated experimentally, in a projected fringe three-channel system. Instead of letting each channel carry phase-stepped images each channel can carry images with a change in fringe pitch. This significantly reduces noise, but at least three images needs to be acquired. It is also shown that the temporal phase unwrapping analysis scheme can be used to evaluate experimental data from wavelength scanning interferometry. Two unwrapping strategies are considered: fitting to a reversed exponential sequence and complex Fourier-transform ranging. The achievable accuracy for both methods ultimately depend on the tuning width, the speckle correlation, and random noise in the optical setup.
Godkänd; 2000; 20070318 (ysko)
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Moran, Jodi. "Quantitative Testing of Probabilistic Phase Unwrapping Methods." Thesis, University of Waterloo, 2001. http://hdl.handle.net/10012/1107.

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The reconstruction of a phase surface from the observed principal values is required for a number of applications, including synthetic aperture radar (SAR) and magnetic resonance imaging (MRI). However, the process of reconstruction, called
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Guddingsmo, Erik. "Unwrapping assumptions : A dialogical approach to communication." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for voksnes læring og rådgivningsvitenskap, 2012. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-20218.

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This thesis investigates how David Bohm’s idea of dialogue could function as means to prompt awareness of hidden assumptions, and how this impacts communication for people involved. This is explored through the research question: "Can dialogue be a leverage to prompt awareness of underlying assumptions? And by extension: Would people experience this to benefit their communication?" To answer this question a dialogical workshop with four participants was conducted in the business environment. The project utilized a qualitative methodology, and data was gathered by the use of semi-structured interviews with the four participants’ from the workshop. Data from these interviews were analyzed by using the constant comparative method, which led to the categories "views on communication", "impact", "the workshop" and "time". The discussion of these categories are mainly grounded in the ideas of David Bohm, which is supported and extended by amongst Chris Argyris, Thomas Jordan, Jack Mezirow and Michael Poutiane. Findings in this suggest dialogue to hold the potential of being a leverage to prompt awareness of underlying assumptions, while also proposing that more extensive research is needed to say something substantial on how this impact peoples communication. Based on the findings there is also presented a model of how such processes plays out.
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Kinell, Lars. "Optical shape measurements using temporal phase unwrapping /." Luleå, 2003. http://epubl.luth.se/1402-1544/2003/31/index.html.

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Goldstein, Goldie L. "Smart Temporal Phase Unwrapping for Biological Objects." Diss., The University of Arizona, 2013. http://hdl.handle.net/10150/311573.

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The development of a quantitative phase microscope (QPM) has allowed the ability to acquire real-time phase movies of biological processes. The image processing of the data is critical to the system's ability to measure relative changes. The phase data must be consistent throughout a measurement and background fluctuations must be minimized. The research presented in this work discusses methods to effectively process sequences of phase data such that it can be used to quantify changes within real-time studies of living cells. This work begins by exploring two-dimensional phase unwrapping to determine the most effective ways to estimate the measured phase surface. Conventional methods of comparing unwrapping performance will be used. In addition, a novel method will be introduced that can characterize accuracy using continuity of derivatives. It will be shown that the most accurate phase estimates are made using modulation data with quality-guided phase unwrapping. After two-dimensionally unwrapping all frames of data within a measurement, there are background fluctuations due to residual surface shape as well as mean phase value fluctuations. Traditionally, manual background removal methods are implemented. Due to the large streams of data that need to be analyzed for the QPM, an automated background removal method is introduced that automatically discriminates the background from features of interest and characterizes and removes the background shape from all frames within a sequence of data. No user intervention is required and the performance rivals manual methods. The final step in processing data from a QPM is to ensure consistent phase unwrapping over an entire dataset. This is a previously undiscussed topic within the field of quantitative phase microscopy. The two-dimensional phase unwrapping methods result in reasonable phase estimates of the measured sample however there are often inconsistencies in local regions amongst sequential frames of data. This work introduces a new method, Smart Temporal unwrapping that minimizes temporal inconsistencies. The image processing methods presented in this work combine to allow phase data acquired using a QPM to quantify relative changes in biological samples. These processing steps effectively minimize errors due to system vibration, residual measurement aberration, and phase unwrapping inconsistencies.
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Abdul-Rahman, Hussein. "Three-dimensional Fourier fringe analysis and phase unwrapping." Thesis, Liverpool John Moores University, 2007. http://researchonline.ljmu.ac.uk/5846/.

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Books on the topic "Unwrapping"

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Dunaway, Michele. Unwrapping Mr. Wright. Toronto: Harlequin Books, 2004.

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Hubbard, David Allan. Unwrapping your spiritual gifts. Waco, Tex: Word Books, 1985.

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Mummies: Unwrapping the past. London: Weidenfeld & Nicolson, 1997.

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Masking strategies: Unwrapping the French paratext. Oxford: New York, Peter Lang, 2011.

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Garant, Sandra Schuck. A grateful heart: Unwrapping life's gifts. Boston: Pauline Books & Media, 2000.

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Carol, Marinelli, ed. Playing the Playboy's Sweetheart / Unwrapping Her Italian Doc. Richmond: Mills & Boon, 2014.

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D, Pritt Mark, ed. Two-dimensional phase unwrapping: Theory, algorithms, and software. New York: Wiley, 1998.

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Zhang, H. Unwrapping the phase response functions for nonlinear systems. Sheffield: University ofSheffield, Dept. of Automatic Control and Systems Engineering, 1992.

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Unwrapping the greatest gift: A family celebration of Christmas. Carol Stream, Illinois: Tyndale House Publishers, Inc., 2014.

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Unwrapping wonder: Finding hope in the gift of nature. Greeley, Colorado: Cladach Publishing, 2013.

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Book chapters on the topic "Unwrapping"

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Jones, Theresa. "Unwrapping." In Raising the Dust, 1–29. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8420-1_1.

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Hammer, Øyvind. "Unwrapping Mummies." In The Perfect Shape, 183–87. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47373-4_44.

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Pearson, Clive Robert. "Unwrapping Theodicy." In Theologies from the Pacific, 181–92. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-74365-9_13.

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Kumar, Abhishek. "Unwrapping the Models." In VR Integrated Heritage Recreation, 133–52. Berkeley, CA: Apress, 2020. http://dx.doi.org/10.1007/978-1-4842-6077-7_6.

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Fatnassi, C., R. Boucenna, and H. Zaidi. "Unwrapping highly wrapped phase using Nonlinear Multi Echo phase unwrapping." In IFMBE Proceedings, 115–18. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19387-8_29.

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Minuchin, Salvador, Michael D. Reiter, and Charmaine Borda. "Unwrapping Family Member Identities." In The Craft of Family Therapy, 32–55. 2nd ed. Second edition. | New York, NY: Routledge, 2021.: Routledge, 2021. http://dx.doi.org/10.4324/9781003110996-4.

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Hughes, Alex, and Richard C. Wilson. "Scale Descriptors through Phase Unwrapping." In Lecture Notes in Computer Science, 530–37. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-27868-9_57.

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Baldi, Antonio, Filippo Bertolino, and Francesco Ginesu. "Phase Unwrapping Algorithms: A Comparison." In Interferometry in Speckle Light, 483–90. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-642-57323-1_59.

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Bioucas-Dias, José M., and Gonçalo Valadão. "Phase Unwrapping via Graph Cuts." In Pattern Recognition and Image Analysis, 360–67. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11492429_44.

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Adrian, Lin, and Solfrid Mykland. "Unwrapping Court-Connected Mediation Agreements." In Nordic Mediation Research, 83–103. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73019-6_6.

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Conference papers on the topic "Unwrapping"

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Shaker, Matineh, Jonas N. Myhre, M. Devrim Kaba, and Deniz Erdogmus. "Invertible nonlinear cluster unwrapping." In 2014 IEEE 24th International Workshop on Machine Learning for Signal Processing (MLSP). IEEE, 2014. http://dx.doi.org/10.1109/mlsp.2014.6958878.

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Gierloff, Jeffrey J. "Phase Unwrapping By Regions." In 31st Annual Technical Symposium. SPIE, 1987. http://dx.doi.org/10.1117/12.967466.

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Spagnolini, Umberto. "2‐D phase unwrapping." In SEG Technical Program Expanded Abstracts 1991. Society of Exploration Geophysicists, 1991. http://dx.doi.org/10.1190/1.1889105.

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Barabadi, Bardia, Matthew Gara, Ali Jooya, Amirali Baniasadi, and Nikitas Dimopoulos. "Dual-Stage Phase Unwrapping." In 2019 IEEE Nordic Circuits and Systems Conference (NORCAS): NORCHIP and International Symposium of System-on-Chip (SoC). IEEE, 2019. http://dx.doi.org/10.1109/norchip.2019.8906916.

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Qian, Kemao, Wenjing Gao, and Haixia Wang. "Filtering-based phase unwrapping." In Optical Engineering + Applications, edited by Joanna Schmit, Katherine Creath, and Catherine E. Towers. SPIE, 2008. http://dx.doi.org/10.1117/12.797390.

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Huntley, Jonathan M., and C. R. Coggrave. "Progress in phase unwrapping." In International Conference on Applied Optical Metrology, edited by Pramod K. Rastogi and Ferenc Gyimesi. SPIE, 1998. http://dx.doi.org/10.1117/12.323298.

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Su, Xianyu, Anand K. Asundi, and M. R. Sajan. "Phase unwrapping in photoelasticity." In Intl. Conf. on Experimental Mechanics: Advances and Applications, edited by Fook S. Chau and C. T. Lim. SPIE, 1997. http://dx.doi.org/10.1117/12.269839.

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Chartrand, Rick, Matthew T. Calef, and Michael S. Warren. "Exploiting Sparsity for Phase Unwrapping." In IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2019. http://dx.doi.org/10.1109/igarss.2019.8898567.

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Shaker, Matineh, M. Devrim Kaba, and Deniz Erdogmus. "Manifold unwrapping using critical surfaces." In 2015 IEEE 25th International Workshop on Machine Learning for Signal Processing (MLSP). IEEE, 2015. http://dx.doi.org/10.1109/mlsp.2015.7324367.

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Flynn, T. J. "Phase unwrapping using discontinuity optimization." In IGARSS '98. Sensing and Managing the Environment. 1998 IEEE International Geoscience and Remote Sensing. Symposium Proceedings. (Cat. No.98CH36174). IEEE, 1998. http://dx.doi.org/10.1109/igarss.1998.702805.

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Reports on the topic "Unwrapping"

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Bambha, Neal K., Justin R. Bickford, Jr Klett, and Karl K. Two-dimensional Phase Unwrapping for Digital Holography. Fort Belvoir, VA: Defense Technical Information Center, September 2012. http://dx.doi.org/10.21236/ada570152.

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Carter, William H. Unwrapping Two-Dimensional Phase Data in Contour Maps. Fort Belvoir, VA: Defense Technical Information Center, March 1992. http://dx.doi.org/10.21236/ada250187.

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Carter, William H. Unwrapping Two-Dimensional Phase Data in Contour Maps. Fort Belvoir, VA: Defense Technical Information Center, November 1991. http://dx.doi.org/10.21236/ada249988.

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