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On the accuracy and efficiency of point-value multiresolution algorithms for solving scalar wave and Euler equations

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JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS 2017年 323卷 159-175页

作者： Soni, V. Roussel, O. Hadjadj, A. Normandie Univ INSA Rouen CNRS CORIA F-76000 Rouen France Umea Univ Dept Phys S-90187 Umea Sweden

This paper concerns the use of a point-value multiresolution algorithm and its extension to three-dimensional hyperbolic conservation laws. The proposed method is applied to a high-order finite-differences discretization with an explicit time integration. The fluxes are evaluated on the adaptive grid using a fifth-order high-resolution shock capturing scheme based on a WENO solver, while the time is advanced using a third-order Runge-Kutta scheme. The multiresolution prediction operators are presented for one-, two- and three-dimensional problems. To assess the efficiency and the accuracy of the method, a new tolerance-scale diagram is introduced. This diagram enables to properly choose the adequate value of the tolerance in order to maintain an optimal multiresolution quality. Numerical examples based on advection and Euler equations are carried out to show that the proposed method yields accurate results. (C) 2017 Elsevier B.V. All rights reserved.

关键词： multiresolution algorithm Grid adaption Finite differences method Shock waves

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multiresolution and hybrid Bayesian algorithms for automatic detection of change points

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IEE PROCEEDINGS-VISION IMAGE AND SIGNAL PROCESSING 1998年第4期145卷 280-286页

作者： MacDougall, S Nandi, AK Chapman, R Univ Strathclyde Dept Elect & Elect Engn Glasgow G1 1XW Lanark Scotland

Two methods for detection of step changes in noise corrupted piecewise-constant univariate datasets are presented. The aim is to determine automatically the number and position of any discontinuities in the mean. This problem is commonly known as the change-point problem. The multiresolution method presented involves performing a discrete wavelet transform, shrinking the coefficients via soft thresholding, and then correlating across scales. Also Bayesian algorithms have long been available;they yield good results but they are impossible to apply in many cases due to huge computational complexity. The technique is compared with previously published hybrid Bayesian algorithms. It is essential in any technique that the probability of false detections is low while retaining a sufficiently high probability of detection for correct change points. To this end the Student's t-test is introduced as a final stage after both methods. This eliminates most, if not all, false detections while retaining most correct ones. Simulation results are presented for each algorithm demonstrating that good performance is obtained for datasets with different characteristics.

关键词： change points Bayesian algorithms multiresolution algorithm

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multiresolution approach to the estimation of the shape of a 3D compact object from its radiographic data

Multiresolution approach to the estimation of the shape of a...

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Conference on Mathematical Modeling, Bayesian Estimation, and Inverse Problems

作者： Soussen, C Mohammad-Djafari, A Supelec Signaux & Syst Lab F-91192 Gif Sur Yvette France

ISBN: (纸本)0819433020

We consider the estimation of a 3D compact homogeneous object from a few number of its gamma ray tomographic projections. This problem is encountered in nondestructive testing applications, in which the number of projections is very limited. We model this shape by a deformable polyhedron, which we estimate directly from the data. The coordinates of the vertices of the polyhedral shape are modeled as a first order vectorial Markov random field and estimated in the Bayesian MAP estimation framework. The energy functional is not convex, hence its minimization requires the use of a stochastic scheme strategy. To reduce the computational cost of the estimation and to propose a practical method, a multiresolution approach is considered in which the number of vertices of the polyhedron is increased as the resolution becomes finer and finer. The algorithm is initialized by a convex polyhedron at a very coarse resolution. Then, at each finer resolution the Bayesian criterion is optimized in the neighborhood of the solution obtained previously. Some simulation results in 2D and 3D cases illustrate the performances of the proposed method.

关键词： computed tomography shape reconstruction multiresolution algorithm deformable polyhedral template

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Improving segmentation accuracy for detecting deforestation using texture feature derived from Landsat 8 OLI multispectral imagery

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EUROPEAN JOURNAL OF REMOTE SENSING 2015年第1期48卷 169-181页

作者： Menaka, E. Kumar, Suresh S. Vivekanandha Inst Engn & Technol Women Dept Comp Sci & Engn Namakkal 637205 Tamil Nadu India Vivekanandha Coll Technol Women Namakkal 637205 Tamil Nadu India

For the identification of deforestation, numerous techniques and features have been developed and used to maximize the segmentation accuracy. Choosing appropriate texture features and extraction methods are one of the most significant issues in remote sensing image applications. This work proposes a Modified Sum of Difference using diagonal texture feature extraction with multiresolution segmentation algorithm to maximize the segmentation accuracy. First, the Modified Sum of Difference using diagonal matrix (MSODDM) algorithm is applied to the input image;this divides the image into a number of coarse objects. Secondly, the multiresolution algorithm with the threshold value of 200 is applied to the coarse image produced by MSODDM for getting finer segmentation result. Finally, the accuracy of the segmented image is compared with the sample input image used in the experimental study. Thus, the proposed method generates more promising result of reaching 97.02% of segmentation accuracy, which results in better classification of remote sensing images in detecting deforestation.

关键词： Deforestation sum of difference modified sum of difference using diagonal multiresolution algorithm

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Object matching using deformable templates

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IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 1996年第3期18卷 267-278页

作者： Jain, AK Zhong, Y Lakshmanan, S UNIV MICHIGAN DEPT ELECT & COMP ENGN DEARBORN MI 48128 USA

We propose a general object localization and retrieval scheme based on object shape using deformable templates. Prior knowledge of an object shape is described by a prototype template which consists of the representative contour/edges, and a set of probabilistic deformation transformations on the template. A Bayesian scheme, which is based on this prior knowledge and the edge information in the input image, is employed to find a match between the deformed template and objects in the image. Computational efficiency is achieved via a coarse-to-fine implementation of the matching algorithm. Our method has been applied to retrieve objects with a variety of shapes from images with complex background. The proposed scheme is invariant to location, rotation, and moderate scale changes of the template.

关键词： object matching deformable templates image database image segmentation Bayesian optimization multiresolution algorithm

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Scalable and portable visualization of large atomistic datasets

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COMPUTER PHYSICS COMMUNICATIONS 2004年第1期163卷 53-64页

作者： Sharma, A Kalia, RK Nakano, A Vashishta, P Univ So Calif Dept Mat Sci & Engn Dept Phys & Astron Dept Comp Sci Los Angeles CA 90089 USA

A scalable and portable code named Atomsviewer has been developed to interactively visualize a large atomistic dataset consisting of up to a billion atoms. The code uses a hierarchical view frustum-culling algorithm based on the octree data structure to efficiently remove atoms outside of the user's field-of-view. Probabilistic and depth-based occlusion-culling algorithms then select atoms, which have a high probability of being visible. Finally a multiresolution algorithm is used to render the selected subset of visible atoms at varying levels of detail. Atomsviewer is written in C++ and OpenGL, and it has been tested on a number of architectures including Windows, Macintosh, and SGI. Atomsviewer has been used to visualize tens of millions of atoms on a standard desktop computer and, in its parallel version, up to a billion atoms.

关键词： visualization hierarchical view frustum culling probabilistic occlusion culling multiresolution algorithm molecular dynamics

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BAYESIAN ANALYSIS OF AMBULATORY BLOOD PRESSURE DYNAMICS WITH APPLICATION TO IRREGULARLY SPACED SPARSE DATA

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ANNALS OF APPLIED STATISTICS 2015年第3期9卷 1601-1620页

作者： Lu, Zhao-Hua Chow, Sy-Miin Sherwood, Andrew Zhu, Hongtu Univ N Carolina Dept Biostat Chapel Hill NC 27599 USA Penn State Univ Dept Human Dev & Family Studies University Pk PA 16803 USA Duke Univ Dept Psychol & Neurosci Durham NC 27708 USA

Ambulatory cardiovascular (CV) measurements provide valuable in-sights into individuals' health conditions in "real-life," everyday settings. Current methods of modeling ambulatory CV data do not consider the dynamic characteristics of the full data set and their relationships with covariates such as caffeine use and stress. We propose a stochastic differential equation (SDE) in the form of a dual nonlinear Ornstein-Uhlenbeck (OU) model with person-specific covariates to capture the morning surge and night-time dipping dynamics of ambulatory CV data. To circumvent the data analytic constraint that empirical measurements are typically collected at irregular and much larger time intervals than those evaluated in simulation studies of SDEs, we adopt a Bayesian approach with a regularized Brownian Bridge sampler (RBBS) and an efficient multiresolution (MR) algorithm to fit the proposed SDE. The MR algorithm can produce more efficient MCMC samples that is crucial for valid parameter estimation and inference. Using this model and algorithm to data from the Duke Behavioral Investigation of Hypertension Study, results indicate that age, caffeine intake, gender and race have effects on distinct dynamic characteristics of the participants' CV trajectories.

关键词： Irregularly spaced longitudinal data population estimation nonlinear process latent process Markov chain Monte Carlo multiresolution algorithm

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Digital Image Processing for Visual Prosthesis: Filtering Implications

Digital Image Processing for Visual Prosthesis: Filtering Im...

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33rd Annual International Conference of the IEEE Engineering-in-Medicine-and-Biology-Society (EMBS)

作者： Barriga-Rivera, Alejandro Suaning, Gregg J. Univ New S Wales Grad Sch Biomed Engn Sydney NSW 2052 Australia

ISBN: (纸本)9781424441228

Investigators around the world are working on retinal neurostimulation as it may restore functional vision to the blind. The image is captured by a camera and after being processed, a series of electrical stimuli are applied to the surviving ganglion cells of the retina. This visual perception is expected to have low resolution. Therefore, there is a need of new algorithms that present the information contained in a visual scene understandable to humans. This study presents a novel multi-resolution algorithm based on wavelet analysis to extract the useful features of an image. Participants in this experiment were able to configure a filter bank to complete a set of everyday tasks. This study shows that wavelet-based algorithms may facilitate improved functional performance in prosthetic vision.

关键词： algorithm design and analysis Image resolution Pattern recognition Retina Visual prosthesis Visualization blind camera digital image processing eye filtering ganglion cells medical image processing multiresolution algorithm prosthetics retinal neurostimul

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