979 resultados para numerical reconstruction


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A novel finite volume method has been presented to solve the shallow water equations. In addition to the volume-integrated average (VIA) for each mesh cell, the surface-integrated average (SIA) is also treated as the model variable and is independently predicted. The numerical reconstruction is conducted based on both the VIA and the SIA. Different approaches are used to update VIA and SIA separately. The SIA is updated by a semi-Lagrangian scheme in terms of the Riemann invariants of the shallow water equations, while the VIA is computed by a flux-based finite volume formulation and is thus exactly conserved. Numerical oscillation can be effectively avoided through the use of a non-oscillatory interpolation function. The numerical formulations for both SIA and VIA moments maintain exactly the balance between the fluxes and the source terms. 1D and 2D numerical formulations are validated with numerical experiments. Copyright (c) 2007 John Wiley & Sons, Ltd.

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A simple method to suppress the zero-order diffraction in the reconstructed image of digital holography is presented. In this method, the Laplacian of a detected hologram is used instead of the hologram itself for numerical reconstruction by computing the discrete Fresnel integral. This method can significantly improve the image quality and give better resolution and higher accuracy of the reconstructed image. The main advantages of this method are its simplicity in experimental requirements and convenience in data processing. (C) 2002 Society of Photo-optical Instrumentation Engineers.

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This paper proposes a new digital method to compensate for the aberration of an electron objective lens in electron holography. In this method, the object wavefront in the exit pupil plane is numerically reconstructed from a digitized electron hologram, and is corrected by multiplying it with the conjugated phase-error function. Then, an aberration-free image can be obtained by calculating the Fresnel integral of this corrected wavefront. In comparison with traditional methods, this method is much more convenient and accurate. Some verifying experiments are also presented in this paper. (C) 2003 Society of Photo-optical Instrumentation Engineers.

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Es wurde ein für bodengebundene Feldmessungen geeignetes System zur digital-holographischen Abbildung luftgetragener Objekte entwickelt und konstruiert. Es ist, abhängig von der Tiefenposition, geeignet zur direkten Bestimmung der Größe luftgetragener Objekte oberhalb von ca. 20 µm, sowie ihrer Form bei Größen oberhalb von ca. 100µm bis in den Millimeterbereich. Die Entwicklung umfaßte zusätzlich einen Algorithmus zur automatisierten Verbesserung der Hologrammqualität und zur semiautomatischen Entfernungsbestimmung großer Objekte entwickelt. Eine Möglichkeit zur intrinsischen Effizienzsteigerung der Bestimmung der Tiefenposition durch die Berechnung winkelgemittelter Profile wurde vorgestellt. Es wurde weiterhin ein Verfahren entwickelt, das mithilfe eines iterativen Ansatzes für isolierte Objekte die Rückgewinnung der Phaseninformation und damit die Beseitigung des Zwillingsbildes erlaubt. Weiterhin wurden mithilfe von Simulationen die Auswirkungen verschiedener Beschränkungen der digitalen Holographie wie der endlichen Pixelgröße untersucht und diskutiert. Die geeignete Darstellung der dreidimensionalen Ortsinformation stellt in der digitalen Holographie ein besonderes Problem dar, da das dreidimensionale Lichtfeld nicht physikalisch rekonstruiert wird. Es wurde ein Verfahren entwickelt und implementiert, das durch Konstruktion einer stereoskopischen Repräsentation des numerisch rekonstruierten Meßvolumens eine quasi-dreidimensionale, vergrößerte Betrachtung erlaubt. Es wurden ausgewählte, während Feldversuchen auf dem Jungfraujoch aufgenommene digitale Hologramme rekonstruiert. Dabei ergab sich teilweise ein sehr hoher Anteil an irregulären Kristallformen, insbesondere infolge massiver Bereifung. Es wurden auch in Zeiträumen mit formal eisuntersättigten Bedingungen Objekte bis hinunter in den Bereich ≤20µm beobachtet. Weiterhin konnte in Anwendung der hier entwickelten Theorie des ”Phasenrandeffektes“ ein Objekt von nur ca. 40µm Größe als Eisplättchen identifiziert werden. Größter Nachteil digitaler Holographie gegenüber herkömmlichen photographisch abbildenden Verfahren ist die Notwendigkeit der aufwendigen numerischen Rekonstruktion. Es ergibt sich ein hoher rechnerischer Aufwand zum Erreichen eines einer Photographie vergleichbaren Ergebnisses. Andererseits weist die digitale Holographie Alleinstellungsmerkmale auf. Der Zugang zur dreidimensionalen Ortsinformation kann der lokalen Untersuchung der relativen Objektabstände dienen. Allerdings zeigte sich, dass die Gegebenheiten der digitalen Holographie die Beobachtung hinreichend großer Mengen von Objekten auf der Grundlage einzelner Hologramm gegenwärtig erschweren. Es wurde demonstriert, dass vollständige Objektgrenzen auch dann rekonstruiert werden konnten, wenn ein Objekt sich teilweise oder ganz außerhalb des geometrischen Meßvolumens befand. Weiterhin wurde die zunächst in Simulationen demonstrierte Sub-Bildelementrekonstruktion auf reale Hologramme angewandt. Dabei konnte gezeigt werden, dass z.T. quasi-punktförmige Objekte mit Sub-Pixelgenauigkeit lokalisiert, aber auch bei ausgedehnten Objekten zusätzliche Informationen gewonnen werden konnten. Schließlich wurden auf rekonstruierten Eiskristallen Interferenzmuster beobachtet und teilweise zeitlich verfolgt. Gegenwärtig erscheinen sowohl kristallinterne Reflexion als auch die Existenz einer (quasi-)flüssigen Schicht als Erklärung möglich, wobei teilweise in Richtung der letztgenannten Möglichkeit argumentiert werden konnte. Als Ergebnis der Arbeit steht jetzt ein System zur Verfügung, das ein neues Meßinstrument und umfangreiche Algorithmen umfaßt. S. M. F. Raupach, H.-J. Vössing, J. Curtius und S. Borrmann: Digital crossed-beam holography for in-situ imaging of atmospheric particles, J. Opt. A: Pure Appl. Opt. 8, 796-806 (2006) S. M. F. Raupach: A cascaded adaptive mask algorithm for twin image removal and its application to digital holograms of ice crystals, Appl. Opt. 48, 287-301 (2009) S. M. F. Raupach: Stereoscopic 3D visualization of particle fields reconstructed from digital inline holograms, (zur Veröffentlichung angenommen, Optik - Int. J. Light El. Optics, 2009)

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We present a FORTRAN 77 code for evaluation of resonance pole positions and residues of a numerical scattering matrix element in the complex energy (CE) as well as in the complex angular momentum (CAM) planes. Analytical continuation of the S-matrix element is performed by constructing a type-II Pade approximant from given physical values (Bessis et al. (1994) [421: Vrinceanu et al. (2000) [24]; Sokolovski and Msezane (2004) [23]). The algorithm involves iterative 'preconditioning' of the numerical data by extracting its rapidly oscillating potential phase component. The code has the capability of adding non-analytical noise to the numerical data in order to select 'true' physical poles, investigate their stability and evaluate the accuracy of the reconstruction. It has an option of employing multiple-precision (MPFUN) package (Bailey (1993) [451) developed by D.H. Bailey wherever double precision calculations fail due to a large number of input partial waves (energies) involved. The code has been successfully tested on several models, as well as the F + H-2 -> HE + H, F + HD : HE + D, Cl + HCI CIH + Cl and H + D-2 -> HD + D reactions. Some detailed examples are given in the text.

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This paper compares the performances of two different optimisation techniques for solving inverse problems; the first one deals with the Hierarchical Asynchronous Parallel Evolutionary Algorithms software (HAPEA) and the second is implemented with a game strategy named Nash-EA. The HAPEA software is based on a hierarchical topology and asynchronous parallel computation. The Nash-EA methodology is introduced as a distributed virtual game and consists of splitting the wing design variables - aerofoil sections - supervised by players optimising their own strategy. The HAPEA and Nash-EA software methodologies are applied to a single objective aerodynamic ONERA M6 wing reconstruction. Numerical results from the two approaches are compared in terms of the quality of model and computational expense and demonstrate the superiority of the distributed Nash-EA methodology in a parallel environment for a similar design quality.

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The foliage of a plant performs vital functions. As such, leaf models are required to be developed for modelling the plant architecture from a set of scattered data captured using a scanning device. The leaf model can be used for purely visual purposes or as part of a further model, such as a fluid movement model or biological process. For these reasons, an accurate mathematical representation of the surface and boundary is required. This paper compares three approaches for fitting a continuously differentiable surface through a set of scanned data points from a leaf surface, with a technique already used for reconstructing leaf surfaces. The techniques which will be considered are discrete smoothing D2-splines [R. Arcangeli, M. C. Lopez de Silanes, and J. J. Torrens, Multidimensional Minimising Splines, Springer, 2004.], the thin plate spline finite element smoother [S. Roberts, M. Hegland, and I. Altas, Approximation of a Thin Plate Spline Smoother using Continuous Piecewise Polynomial Functions, SIAM, 1 (2003), pp. 208--234] and the radial basis function Clough-Tocher method [M. Oqielat, I. Turner, and J. Belward, A hybrid Clough-Tocher method for surface fitting with application to leaf data., Appl. Math. Modelling, 33 (2009), pp. 2582-2595]. Numerical results show that discrete smoothing D2-splines produce reconstructed leaf surfaces which better represent the original physical leaf.

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Realistic virtual models of leaf surfaces are important for a number of applications in the plant sciences, such as modelling agrichemical spray droplet movement and spreading on the surface. In this context, the virtual surfaces are required to be sufficiently smooth to facilitate the use of the mathematical equations that govern the motion of the droplet. While an effective approach is to apply discrete smoothing D2-spline algorithms to reconstruct the leaf surfaces from three-dimensional scanned data, difficulties arise when dealing with wheat leaves that tend to twist and bend. To overcome this topological difficulty, we develop a parameterisation technique that rotates and translates the original data, allowing the surface to be fitted using the discrete smoothing D2-spline methods in the new parameter space. Our algorithm uses finite element methods to represent the surface as a linear combination of compactly supported shape functions. Numerical results confirm that the parameterisation, along with the use of discrete smoothing D2-spline techniques, produces realistic virtual representations of wheat leaves.

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Diffuse optical tomographic image reconstruction uses advanced numerical models that are computationally costly to be implemented in the real time. The graphics processing units (GPUs) offer desktop massive parallelization that can accelerate these computations. An open-source GPU-accelerated linear algebra library package is used to compute the most intensive matrix-matrix calculations and matrix decompositions that are used in solving the system of linear equations. These open-source functions were integrated into the existing frequency-domain diffuse optical image reconstruction algorithms to evaluate the acceleration capability of the GPUs (NVIDIA Tesla C 1060) with increasing reconstruction problem sizes. These studies indicate that single precision computations are sufficient for diffuse optical tomographic image reconstruction. The acceleration per iteration can be up to 40, using GPUs compared to traditional CPUs in case of three-dimensional reconstruction, where the reconstruction problem is more underdetermined, making the GPUs more attractive in the clinical settings. The current limitation of these GPUs in the available onboard memory (4 GB) that restricts the reconstruction of a large set of optical parameters, more than 13, 377. (C) 2010 Society of Photo-Optical Instrumentation Engineers. DOI: 10.1117/1.3506216]

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Purpose: The authors aim at developing a pseudo-time, sub-optimal stochastic filtering approach based on a derivative free variant of the ensemble Kalman filter (EnKF) for solving the inverse problem of diffuse optical tomography (DOT) while making use of a shape based reconstruction strategy that enables representing a cross section of an inhomogeneous tumor boundary by a general closed curve. Methods: The optical parameter fields to be recovered are approximated via an expansion based on the circular harmonics (CH) (Fourier basis functions) and the EnKF is used to recover the coefficients in the expansion with both simulated and experimentally obtained photon fluence data on phantoms with inhomogeneous inclusions. The process and measurement equations in the pseudo-dynamic EnKF (PD-EnKF) presently yield a parsimonious representation of the filter variables, which consist of only the Fourier coefficients and the constant scalar parameter value within the inclusion. Using fictitious, low-intensity Wiener noise processes in suitably constructed ``measurement'' equations, the filter variables are treated as pseudo-stochastic processes so that their recovery within a stochastic filtering framework is made possible. Results: In our numerical simulations, we have considered both elliptical inclusions (two inhomogeneities) and those with more complex shapes (such as an annular ring and a dumbbell) in 2-D objects which are cross-sections of a cylinder with background absorption and (reduced) scattering coefficient chosen as mu(b)(a)=0.01mm(-1) and mu('b)(s)=1.0mm(-1), respectively. We also assume mu(a) = 0.02 mm(-1) within the inhomogeneity (for the single inhomogeneity case) and mu(a) = 0.02 and 0.03 mm(-1) (for the two inhomogeneities case). The reconstruction results by the PD-EnKF are shown to be consistently superior to those through a deterministic and explicitly regularized Gauss-Newton algorithm. We have also estimated the unknown mu(a) from experimentally gathered fluence data and verified the reconstruction by matching the experimental data with the computed one. Conclusions: The PD-EnKF, which exhibits little sensitivity against variations in the fictitiously introduced noise processes, is also proven to be accurate and robust in recovering a spatial map of the absorption coefficient from DOT data. With the help of shape based representation of the inhomogeneities and an appropriate scaling of the CH expansion coefficients representing the boundary, we have been able to recover inhomogeneities representative of the shape of malignancies in medical diagnostic imaging. (C) 2012 American Association of Physicists in Medicine. [DOI: 10.1118/1.3679855]

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A novel approach that can more effectively use the structural information provided by the traditional imaging modalities in multimodal diffuse optical tomographic imaging is introduced. This approach is based on a prior image-constrained-l(1) minimization scheme and has been motivated by the recent progress in the sparse image reconstruction techniques. It is shown that the proposed framework is more effective in terms of localizing the tumor region and recovering the optical property values both in numerical and gelatin phantom cases compared to the traditional methods that use structural information. (C) 2012 Optical Society of America

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The sparse recovery methods utilize the l(p)-normbased regularization in the estimation problem with 0 <= p <= 1. These methods have a better utility when the number of independent measurements are limited in nature, which is a typical case for diffuse optical tomographic image reconstruction problem. These sparse recovery methods, along with an approximation to utilize the l(0)-norm, have been deployed for the reconstruction of diffuse optical images. Their performancewas compared systematically using both numerical and gelatin phantom cases to show that these methods hold promise in improving the reconstructed image quality.

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Recently, it has been shown that fusion of the estimates of a set of sparse recovery algorithms result in an estimate better than the best estimate in the set, especially when the number of measurements is very limited. Though these schemes provide better sparse signal recovery performance, the higher computational requirement makes it less attractive for low latency applications. To alleviate this drawback, in this paper, we develop a progressive fusion based scheme for low latency applications in compressed sensing. In progressive fusion, the estimates of the participating algorithms are fused progressively according to the availability of estimates. The availability of estimates depends on computational complexity of the participating algorithms, in turn on their latency requirement. Unlike the other fusion algorithms, the proposed progressive fusion algorithm provides quick interim results and successive refinements during the fusion process, which is highly desirable in low latency applications. We analyse the developed scheme by providing sufficient conditions for improvement of CS reconstruction quality and show the practical efficacy by numerical experiments using synthetic and real-world data. (C) 2013 Elsevier B.V. All rights reserved.