402 research outputs found
Riflessioni sulla localizzazione della battaglia di Zama
No full textAnalisi delle ipotesi sulla localizzazione della Battaglia di Zama (18 ottobre 202 a.C.)
Medioevo latino. Bollettino bibliografico della cultura europea da Boezio a Erasmo (secoli VI - XV) - Volume 29
No full textResoconto bibliografico, con particolare attenzione a settori significativi della cultura mediolatina. Fondato nel 1980 da Claudio Leonardi, R. Avesani, F. Bertini, G. Cremascoli, G. Orlandi e G. Scalia e pubblicato ogni anno, è diventato un punto di riferimento per gli studiosi di medievistica. Diviso in grandi sezioni (Autori e testi, Fortleben, argomenti, generi letterari, istituzioni, scienze della storia, opere di consultazione, congressi e miscellanee), è corredato di un ricco apparato di indici. Il frutto del lavoro nasce dalla collaborazione fra numerose redazioni, nazionali e internazionali. La redazione bolognese è composta da F. Foschi, V. Lunardini, R. Parmeggiani, F. Tinti, A. Zama, coordinati da G. Cremascoli e impegnati in un intenso lavoro di spoglio e schedatura di riviste e volumi, per un paio di mesi all’anno
A variational approach to Gibbs artifacts removal in MRI
No full textGibbs ringing is a feature of MR images caused by the finite sampling of the acquisition space (k-space). It manifests itself with ringing patterns around sharp edges which become increasingly significant for low-resolution acquisitions. In this paper, we model the Gibbs artefact removal as a constrained variational problem where the data discrepancy, represented in denoising and convolutive form, is balanced to sparsity-promoting regularization functions such as Total Variation, Total Generalized Variation and L1 norm of the Wavelet transform. The efficacy of such models is evaluated by running a set of numerical experiments both on synthetic data and real acquisitions of brain images. The Total Generalized Variation penalty coupled with the convolutive data discrepancy term yields, in general, the best results both on synthetic and real data
A domain decomposition technique for spline image restoration on distributed memory systems
No full textThe problem of image restoration is considered when the point spread function is Space Variant Non Separable. The algorithm determines a continuous approximation of the original object, following the continuous object-discrete image approach. The image spatial domain is decomposed into subdomains and the local approximants are computed on a distributed memory environment. The continuity of the solution across the image subdomains is obtained by adding a suitable overlapping area to the sides of the subdomains. Numerical experiments have been carried out on a Hypercube Intel iPSC/860 and the most interesting results are reported
The conjugate gradient regularization method in Computed Tomography problems
No full textIn this work we solve inverse problems coming from the area of Computed Tomography by means of regularization methods based on conjugate gradient iterations. We develop a stopping criterion which is efficient for the computation of a regularized solution for the least-squares normal equations. The stopping rule can be suitably applied also to the Tikhonov regularization method. We report computational experiments based on different physical models and with different degrees of noise. We compare the results obtained with those computed by other currently used methods such as Algebraic Reconstruction Techniques (ART) and Backprojection
An experiment in image restoration using transputer networks
No full textThe problem of image restoration, with a blurring function linear, space-variant and nonseparable, has been solved on a transputer network, using primitives of Parasoft express environment and A.C.S. Arnia Library. A domain decomposition strategy has been introduced to split the problem among the processors. Some interesting computational results are reported. © 1995, Taylor & Francis Group, LLC. All rights reserved
An iterative algorithm for large size least-squares constrained regularization problems
No full textIn this paper we propose an iterative algorithm to solve large size linear inverse ill posed
problems. The regularization problem is formulated as a constrained optimization problem.
The dual Lagrangian problem is iteratively solved to compute an approximate solution.
Before starting the iterations, the algorithm computes the necessary smoothing
parameters and the error tolerances from the data.
The numerical experiments performed on test problems show that the algorithm gives
good results both in terms of precision and computational efficiency
Computation of Regularization Parameters using the Fourier Coefficients
No full textIn the solution of ill-posed problems by means of regularization
methods, a crucial issue is the computation of the regularization
parameter. In this work we focus on the Truncated Singular Value
Decomposition (TSVD) and Tikhonov method and we define a method for
computing the regularization parameter based on the behavior of
Fourier coefficients. We compute a safe index for truncating the
TSVD and consequently a value for the regularization parameter of
the Tikhonov method. An extensive numerical experimentation is
carried out on the Hansen's Regtool test problems and
the results confirm the effectiveness and robustness of the method
proposed
Parallel image restoration with domain decomposition
No full textIn this paper we present parallel algorithms to solve the problem of image restoration when the Point Spread Function is Space Variant. The problem has a very high computational complexity and it is very hard to solve it on scalar computers. The algorithms are based on the decomposition of the image spatial domain and on the solution of both constrained and unconstrained restoration subproblems of size smaller than the original. The main results can be summarized as follows: (a) the quality of restorations do not depend on the number of subdomains; (b) the unconstrained restoration is scalable and efficient even with a large number of processors while the constrained restoration is efficient for subdomains of more than 50×50 pixels. The numerical tests have been executed on a Cray T3E with 128 processors and on a network of workstations
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