64 resultados para Joint reconstruction
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The development and tests of an iterative reconstruction algorithm for emission tomography based on Bayesian statistical concepts are described. The algorithm uses the entropy of the generated image as a prior distribution, can be accelerated by the choice of an exponent, and converges uniformly to feasible images by the choice of one adjustable parameter. A feasible image has been defined as one that is consistent with the initial data (i.e. it is an image that, if truly a source of radiation in a patient, could have generated the initial data by the Poisson process that governs radioactive disintegration). The fundamental ideas of Bayesian reconstruction are discussed, along with the use of an entropy prior with an adjustable contrast parameter, the use of likelihood with data increment parameters as conditional probability, and the development of the new fast maximum a posteriori with entropy (FMAPE) Algorithm by the successive substitution method. It is shown that in the maximum likelihood estimator (MLE) and FMAPE algorithms, the only correct choice of initial image for the iterative procedure in the absence of a priori knowledge about the image configuration is a uniform field.
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In this paper we present a Bayesian image reconstruction algorithm with entropy prior (FMAPE) that uses a space-variant hyperparameter. The spatial variation of the hyperparameter allows different degrees of resolution in areas of different statistical characteristics, thus avoiding the large residuals resulting from algorithms that use a constant hyperparameter. In the first implementation of the algorithm, we begin by segmenting a Maximum Likelihood Estimator (MLE) reconstruction. The segmentation method is based on using a wavelet decomposition and a self-organizing neural network. The result is a predetermined number of extended regions plus a small region for each star or bright object. To assign a different value of the hyperparameter to each extended region and star, we use either feasibility tests or cross-validation methods. Once the set of hyperparameters is obtained, we carried out the final Bayesian reconstruction, leading to a reconstruction with decreased bias and excellent visual characteristics. The method has been applied to data from the non-refurbished Hubble Space Telescope. The method can be also applied to ground-based images.
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This paper describes the development and applications of a super-resolution method, known as Super-Resolution Variable-Pixel Linear Reconstruction. The algorithm works combining different lower resolution images in order to obtain, as a result, a higher resolution image. We show that it can make significant spatial resolution improvements to satellite images of the Earth¿s surface allowing recognition of objects with size approaching the limiting spatial resolution of the lower resolution images. The algorithm is based on the Variable-Pixel Linear Reconstruction algorithm developed by Fruchter and Hook, a well-known method in astronomy but never used for Earth remote sensing purposes. The algorithm preserves photometry, can weight input images according to the statistical significance of each pixel, and removes the effect of geometric distortion on both image shape and photometry. In this paper, we describe its development for remote sensing purposes, show the usefulness of the algorithm working with images as different to the astronomical images as the remote sensing ones, and show applications to: 1) a set of simulated multispectral images obtained from a real Quickbird image; and 2) a set of multispectral real Landsat Enhanced Thematic Mapper Plus (ETM+) images. These examples show that the algorithm provides a substantial improvement in limiting spatial resolution for both simulated and real data sets without significantly altering the multispectral content of the input low-resolution images, without amplifying the noise, and with very few artifacts.
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Els dies 11 i 12 d'agost va tenir lloc a Copenhaguen, Dinamarca, el seminari de treball Library and Information Science Education in Europe: ¿Issues in joint curriculum development and Bologna perspectives¿. Aquest seminari, que va estar coordinat per la Royal School of Library and Information Science de Dinamarca, amb la col·laboració de l'European Association for Library and Information Education and Research (EUCLID), es va organitzar en el marc d'un projecte europeu subvencionat pel programa Sòcrates. La Facultat de Biblioteconomia i Documentació de la Universitat de Barcelona, present entre 2001 i 2005 en la Junta de Govern de l'EUCLID, va participar-hi com a soci del projecte. L'objectiu del seminari era aplegar una cinquantena d'experts europeus de l'àrea de Biblioteconomia i Documentació ¿tots ells professors d'escoles i de facultats d'universitats europees¿ per discutir qüestions relacionades amb els plans d'estudis dels ensenyaments des de la perspectiva del procés de Bolonya. El seminari consistí en dues conferències i en les reunions de treball de dotze grups formats per experts que examinaren dotze grans temes ¿prèviament acordats pels organitzadors de l'esdeveniment¿ relacionats amb els plans d'estudis d'aquells ensenyaments.
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A systematic assessment of global neural network connectivity through direct electrophysiological assays has remained technically infeasible, even in simpler systems like dissociated neuronal cultures. We introduce an improved algorithmic approach based on Transfer Entropy to reconstruct structural connectivity from network activity monitored through calcium imaging. We focus in this study on the inference of excitatory synaptic links. Based on information theory, our method requires no prior assumptions on the statistics of neuronal firing and neuronal connections. The performance of our algorithm is benchmarked on surrogate time series of calcium fluorescence generated by the simulated dynamics of a network with known ground-truth topology. We find that the functional network topology revealed by Transfer Entropy depends qualitatively on the time-dependent dynamic state of the network (bursting or non-bursting). Thus by conditioning with respect to the global mean activity, we improve the performance of our method. This allows us to focus the analysis to specific dynamical regimes of the network in which the inferred functional connectivity is shaped by monosynaptic excitatory connections, rather than by collective synchrony. Our method can discriminate between actual causal influences between neurons and spurious non-causal correlations due to light scattering artifacts, which inherently affect the quality of fluorescence imaging. Compared to other reconstruction strategies such as cross-correlation or Granger Causality methods, our method based on improved Transfer Entropy is remarkably more accurate. In particular, it provides a good estimation of the excitatory network clustering coefficient, allowing for discrimination between weakly and strongly clustered topologies. Finally, we demonstrate the applicability of our method to analyses of real recordings of in vitro disinhibited cortical cultures where we suggest that excitatory connections are characterized by an elevated level of clustering compared to a random graph (although not extreme) and can be markedly non-local.
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We propose a method to obtain a single centered correlation with use of a joint transform correlator. We analyze the required setup to carry out the whole process optically, and we also present experimental results.
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It is possible to improve the fringe binarization method of joint transform correlation by choosing a suitable threshold level.
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In multiobject pattern recognition the height of the correlation peaks should be controlled when the power spectrum of ajoint transform correlator is binarized. In this paper a method to predetermine the value of detection peaks is demonstrated. The technique is based on a frequency-variant threshold in order to remove the intraclass terms and on a suitable factor to normalize the binary joint power spectrum. Digital simulations and experimental hybrid implementation of this method were carried out.
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The use of different kinds of nonlinear filtering in a joint transform correlator are studied and compared. The study is divided into two parts, one corresponding to object space and the second to the Fourier domain of the joint power spectrum. In the first part, phase and inverse filters are computed; their inverse Fourier transforms are also computed, thereby becoming the reference in the object space. In the Fourier space, the binarization of the power spectrum is realized and compared with a new procedure for removing the spatial envelope. All cases are simulated and experimentally implemented by a compact joint transform correlator.
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We report the study of the influence of optical aberrations in a joint-transform correlator: The wave aberration of the optical system is computed from data obtained by ray tracing. Three situations are explored: We consider the aberration only in the first diffraction stage (generation of power spectrum), then only in the second (transformation of the power spectrum into correlation), and finally in both stages simultaneously. The results show that the quality of the correlation is determined mostly by the aberrations of the first diffraction stage and that we can optimize the setup by moving the cameras along the optical axis to a suitable position. The good agreement between the predicted data and the experimental results shows that the method explains well the behavior of optical diffraction systems when aberrations are taken into account.
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Los restos fecales están compuestos mayoritariamente por materia orgánica, la cual se degrada con el tiempo despareciendo finalmente del registro arqueológico. Sin embargo, estos restos fecales también contienen ciertos elementos resistentes al paso del tiempo y a los efectos postdeposicionales. Las esferulitas son cristales de carbonato cálcico formadas en los intestinos de ciertos animales herbívoros, principalmente rumiantes y que posteriormente son depositados en los restos fecales. Los fitolitos de sílice, aunque se forman en las plantas, son también comúnmente identificados en los restos fecales de animales herbívoros. Su número y morfología dependerá de la dieta vegetal de estos animales. El estudio que aquí se presenta se centra en el análisis microscópico de ambos elementos, fitolitos y esferulitas, identificados en restos fecales, de varios animales herbívoros, recolectados durante la estación seca en la Garganta de Olduvai en Tanzania. Los fitolitos y las esferulitas fueron identificados y analizados siguiendo un método morfológico y cuantitativo. Los fitolitos fueron luego comparados con una colección de referencia de plantas modernas de la misma zona geográfica con el propósito de estudiar la dieta de cada uno de los animales analizados. Finalmente los resultados fueron relacionados con los obtenidos del estudio de esferulitas, con el propósito de analizar la relación entre morfología y número de fitolitos y morfología y número de esferulitas para cada uno de los restos fecales analizados. El objetivo de este trabajo consiste en evaluar la utilidad de combinar ambas técnicas para identificar restos fecales en el registro arqueológico y, consecuentemente, responder a cuestiones relacionadas con el animal productor de estos restos, su dieta y movimientos migratorios y, paralelamente, la paleovegetación y el paleopaisaje en una región determinada.