A new type of coded aperture configuration that enables fast decoding of the coded aperture shadowgram data is presented. Based on the products of incidence vectors generated from the Singer difference sets, we call t...
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A new type of coded aperture configuration that enables fast decoding of the coded aperture shadowgram data is presented. Based on the products of incidence vectors generated from the Singer difference sets, we call these Singer product apertures. For a range of aperture dimensions, we compare experimentally the performance of three decoding methods: standard decoding, induction decoding and direct vector decoding. In all cases the induction and direct vector methods are several orders of magnitude faster than the standard method, with direct vector decoding being significantly faster than induction decoding. For apertures of the same dimensions the increase in speed offered by direct vector decoding over induction decoding is better for lower throughput apertures.
Modelling signals as being periodic is common in many applications. Such periodic signals can be represented by a weighted sum of sinusoids with frequencies being an integer multiple of the fundamental frequency. Due ...
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Modelling signals as being periodic is common in many applications. Such periodic signals can be represented by a weighted sum of sinusoids with frequencies being an integer multiple of the fundamental frequency. Due to its widespread use, numerous methods have been proposed to estimate the fundamental frequency, and the maximum likelihood (ML) estimator is the most accurate estimator in statistical terms. When the noise is assumed to be white and Gaussian, the ML estimator is identical to the non-linear least squares (NLS) estimator. Despite being optimal in a statistical sense, the NLS estimator has a high computational complexity. In this paper, we propose an algorithm for lowering this complexity significantly by showing that the NLS estimator can be computed efficiently by solving two Toeplitz-plus-Hankel systems of equations and by exploiting the recursive-in-order matrix structures of these systems. Specifically, the proposed algorithm reduces the time complexity to the same order as that of the popular harmonic summation method which is an approximate NLS estimator. The performance of the proposed algorithm is assessed via Monte Carlo and timing studies. These show that the proposed algorithm speeds up the evaluation of the NLS estimator by a factor of 50-100 for typical scenarios.
An algorithm is presented for computing the Hartree-Fock exchange matrix using concentric atomic density fitting with data and instruction count complexities. The algorithm exploits the asymptotic distance dependence ...
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An algorithm is presented for computing the Hartree-Fock exchange matrix using concentric atomic density fitting with data and instruction count complexities. The algorithm exploits the asymptotic distance dependence of the three-centre Coulomb integrals along with the rapid decay of the density matrix to accelerate the construction of the exchange matrix. The new algorithm is tested with computations on systems with up to 1536 atoms and a quadruple-zeta basis set (up to 15585 basis functions). Our method handles screening of high angular momentum contributions in a particularly efficient manner, allowing the use of larger basis sets for large molecules without a prohibitive increase in cost. [GRAPHICS] .
Purpose: Iterative image reconstruction algorithms are commonly used to optimize an objective function, especially when the objective function is nonquadratic. Generally speaking, the iterative algorithms are computat...
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Purpose: Iterative image reconstruction algorithms are commonly used to optimize an objective function, especially when the objective function is nonquadratic. Generally speaking, the iterative algorithms are computationally inefficient. This paper presents a fast algorithm that has one backprojection and no forward projection. Methods: This paper derives a new method to solve an optimization problem. The nonquadratic constraint, for example, an edge-preserving denoising constraint is implemented as a nonlinear filter. The algorithm is derived based on the POCS (projections onto projections onto convex sets) approach. A windowed FBP (filtered backprojection) algorithm enforces the data fidelity. An iterative procedure, divided into segments, enforces edge-enhancement denoising. Each segment performs nonlinear filtering. Results: The derived iterative algorithm is computationally efficient. It contains only one backprojection and no forward projection. Low-dose CT data are used for algorithm feasibility studies. The nonlinearity is implemented as an edge-enhancing noise-smoothing filter. Conclusions: The patient studies results demonstrate its effectiveness in processing low-dose x ray CT data. This fast algorithm can be used to replace many iterative algorithms. (C) 2017 American Association of Physicists in Medicine
In this paper we propose a new fast Weighted Total Variation denoising approach, where we introduce edge driven weights in the standard TV discrete regularizer and a non Euclidean metric in the discrepancy term, induc...
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In this paper we propose a new fast Weighted Total Variation denoising approach, where we introduce edge driven weights in the standard TV discrete regularizer and a non Euclidean metric in the discrepancy term, induced by a positive definite matrix B, strictly related to the weights. In this way the fidelity constraint is adapted according to "edge-ness" of each pixel. The corresponding minimization problem is iteratively solved by using the Split-Bregman strategy, in which, due to the particular choice of the structure of the positive definite matrix involved in the measure of the fidelity term, the optimality conditions imposed for the computation of the minimum are reduced to simple assignments, since all variables are decoupled. For its solution we propose a fast Weighted Total Variation (FWTV) algorithm and, moreover, we prove its convergence. Several experiments demonstrate that the FWTV algorithm outperforms, both in terms of accuracy and execution times, the performance of the Weighted Split-Bregman denoising approach, where the l(2)-norm isused in order to measure the fidelity term. In the case of synthetic images, the proposed algorithm is better respect to the best-state-of-art algorithms, but the methods not based on TV minimization give better performances with respect to our proposal in the case of natural images. (C) 2016 Elsevier Inc. All rights reserved.
作者:
Popovic, JelenaRunborg, OlofKTH
Dept Numer Anal CSC S-10044 Stockholm Sweden KTH
Dept Math S-10044 Stockholm Sweden KTH
Swedish E Sci Res Ctr SeRC S-10044 Stockholm Sweden
In this paper, we present a fast time adaptive numerical method for interface tracking. The method uses an explicit multiresolution description of the interface, which is represented by wavelet vectors that correspond...
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In this paper, we present a fast time adaptive numerical method for interface tracking. The method uses an explicit multiresolution description of the interface, which is represented by wavelet vectors that correspond to the details of the interface on different scale levels. The complexity of standard numerical methods for interface tracking, where the interface is described by N marker points, is 0 (N/Delta t),when a time step At is used. The methods that we propose in this paper have 0 (TOL-1/P log N + N log N) computational cost, at least for uniformly smooth problems, where TOL is some given tolerance and p is the order of the time stepping method that is used for time advection of the interface. The adaptive method is robust in the sense that it can handle problems with both smooth and piecewise smooth interfaces (e.g. interfaces with corners) while keeping a low computational cost. We show numerical examples that verify these properties. (C) 2017 Elsevier Inc. All rights reserved.
An efficient fast algorithm for accelerating the time-domain integral equation discontinuous Galerkin (TDIEDG) method for analyzing the transient scattering from electrically large complex objects is proposed. The TDI...
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An efficient fast algorithm for accelerating the time-domain integral equation discontinuous Galerkin (TDIEDG) method for analyzing the transient scattering from electrically large complex objects is proposed. The TDIEDG is discretized using the monopolar Rao-Wilton-Glisson (RWG) function and shifted Lagrange polynomial function in spatial and time domain, respectively. The final system of equations can be solved iteratively using the classical marching-on-in-time scheme. Taking advantage of the approximate evaluation of the vector and scalar potential terms combined with the Taylor series expansion of the transient far field, the computational burden of the TDIEDG solver has been significantly reduced. In addition, it is flexible and convenient to analyze object with nonconformal discretization due to the employment of the monopolar RWG functions.
In this paper, we introduce a fast algorithm for computing cosine transforms over fields of characteristic 2 (FFCT). Such transforms, which were recently proposed in the literature, are analogous to real-valued discre...
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In this paper, we introduce a fast algorithm for computing cosine transforms over fields of characteristic 2 (FFCT). Such transforms, which were recently proposed in the literature, are analogous to real-valued discrete cosine transforms in the same sense in which the finite field Fourier transform (FFFT) is analogous to the discrete Fourier transform. The referred algorithm is based on fast algorithms for computing cyclic convolutions over fields of characteristic 2. In particular, we present an algorithm for an 8-point FFCT over GF(28) and show how such a transform can be used as the basis of an image encryption scheme. We highlight the advantages of this scheme compared to that based on cosine transforms over fields of odd characteristic
We consider the mass matrix arising from Bernstein polynomials as finite element shape functions. In particular, we give an explicit formula for its eigenvalues and exact characterization of the eigenspaces in terms o...
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We consider the mass matrix arising from Bernstein polynomials as finite element shape functions. In particular, we give an explicit formula for its eigenvalues and exact characterization of the eigenspaces in terms of the Bernstein representation of orthogonal polynomials. We then derive a fast algorithm for solving linear systems involving the element mass matrix. After establishing these results, we describe the application of Bernstein techniques to the discontinuous Galerkin finite element method for hyperbolic conservation laws, obtaining optimal complexity algorithms. Finally, we present numerical results investigating the accuracy of the mass inversion algorithms and the scaling of total run-time for the function evaluation needed in DG time-stepping.
The discrete Pascal transform (DPT) is a relatively recently introduced spectral transform based on the concept of the Pascal triangle which has been known for centuries. It is used in digital image processing, digita...
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ISBN:
(纸本)9781509054954
The discrete Pascal transform (DPT) is a relatively recently introduced spectral transform based on the concept of the Pascal triangle which has been known for centuries. It is used in digital image processing, digital filtering, pattern recognition, watermarking, and related areas. Its applicability is limited by the O(N-2) asymptotical time complexity of best current algorithms for its computation, where N is the size of the function to be processed. In this paper, we propose a method for the efficient computation of the DPT in O(N logN) time, based on the factorization of its transform matrix into a product of three matrices with special structure - two diagonal matrices and a Toeplitz matrix. The Toeplitz matrix is further embedded into a circulant matrix of order 2N. The diagonalization of the circulant matrix by the Fourier matrix permits the use of the fast Fourier transform (FFT) for performing the computations, leading to an algorithm with the overall computational complexity of O(N logN). Since the entries in the Toeplitz matrix have very different magnitudes, the numerical stability of this algorithm is also discussed. We also consider the issues in implementing the proposed algorithm for highly-parallel computation on graphics processing units (GPUs). The experiments show that computing the DPT using the proposed algorithm processed on GPUs is orders of magnitude faster than the best current approach. As a result, the proposed method can significantly extend the practical applicability of the discrete Pascal transform.
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