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A New Solution of the Rendering Equation with Stratified Monte Carlo Approach

AIP Conference Proceedings 2008年第1期1048卷

作者： Anton A. Penzov ivan T. Dimov Vladimir N. Koylazov Department of Parallel Algorithms Institute for Parallel Processing Bulgarian Academy of Sciences Acad. G. Bonchev Str. bl. 25 A 1113 Sofia Bulgaria ACET Centre University of Reading Whiteknights PO Box 217 Reading RG6 6AH UK Chaos Software Alexander Malinov Blvd. bl. 33 entr. B. 1729 Sofia Bulgaria

This paper is turned to the advanced Monte Carlo methods for realistic image creation. It offers a new stratified approach for solving the rendering equation. We consider the numerical solution of the rendering equation by separation of integration domain. The hemispherical integration domain is symmetrically separated into 16 parts. First 8 sub‐domains are equal size of orthogonal spherical triangles. They are symmetric each to other and grouped with a common vertex around the normal vector to the surface. The hemispherical integration domain is completed with more 8 sub‐domains of equal size spherical quadrangles, also symmetric each to other. All sub‐domains have fixed vertices and computable parameters. The bijections of unit square into an orthogonal spherical triangle and into a spherical quadrangle are derived and used to generate sampling points. Then, the symmetric sampling scheme is applied to generate the sampling points distributed over the hemispherical integration domain. The necessary transformations are made and the stratified Monte Carlo estimator is presented. The rate of convergence is obtained and one can see that the algorithm is of super‐convergent type.

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parallel contour matching and 3D partial retrieval in bio-image database

Parallel contour matching and 3D partial retrieval in bio-im...

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21st International Conference on Advanced Information Networking and ApplicationsWorkshops/Symposia, AINAW'07

作者： Li, Yong Chen, Xiujuan Belkasim, Saeid Pan, Yi Department of Computer Science Georgia State University P.O. Box 3994 Atlanta GA 30302-3994 United States

ISBN: (纸本)0769528473

parallel 3D reconstruction and partial retrieval from 2D image slices based on object contour structure are introduced. In this paper, 2D images are segmented into object contours. Related object contours on adjacent image slices are linked together to form the 3D component. parallel algorithms are designed and implemented for distributing contour matching and partial retrieval tasks among multiple processors. The methods have been implemented in MPI on an SGI Origin 2000 machine. The experimental results show good speedups for sequential object matching and partial 3D component retrieval. © 2007 IEEE.

关键词： image reconstruction

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Tissue MicroArray: a distributed Grid Approach for image Analysis

Tissue MicroArray: a Distributed Grid Approach for Image Ana...

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5th HealthGrid Conference

作者： Viti, Federica Merelli, ivan Galizia, Antonella D'Agostino, Daniele Clematis, Andrea Milanesi, Luciano CNR Inst Biomed Technol Milan Italy CNR Inst Appl Math & Informat Technol Genoa Italy

ISBN: (纸本)9781586037383

The Tissue MicroArray (TMA) technique is assuming even more importance. Digital images acquisition becomes fundamental to provide an automatic system for Subsequent analysis. The accuracy of the results depends on the image resolution, which has to be very high in order to provide as many details as possible. Lossless formats are more suitable to bring information, but data file size become a critical factor researchers have to deal with. This affects not only storage methods but also computing times and performances. Pathologists and researchers who work with biological tissues, in particular with the TMA technique, need to consider a large number of case studies to formulate and validate their hypotheses. It is clear the importance of image sharing between different institutes worldwide to increase the amount of interesting data to work with. In this context, preserving the security of sensitive data is a fundamental issue. In most of the cases copying patient data in places different from the original database is forbidden by the owner institutes. Storage, computing and security are key problems of TMA methodology. In our system we tackle all these aspects using the EGEE (Enabling Grids for E-sciencE) Grid infrastructure. The Grid platform provides good storage, performance in image processing and safety of sensitive patient information: this architecture offers hundreds of Storage and Computing Elements and enables users to handle images without copying them to physical disks other than where they have been archived by the owner giving back to end-users only the processed anonymous images. The efficiency of the TMA analysis process is obtained implementing algorithms based on functions provided by the parallel image processing Genoa Library (PIMA(GE)(2) Lib). The acquisition of remotely distributed TMA images is made using specialized I/O functions based on the Grid File Access Library (GFAL) API. In our opinion this approach may represent important contribution

关键词： Tissue Microarray Grid platform image analysis

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Formal methods: Applications and Technology

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11th International Workshop on Formal methods for Industrial Critical Systems, FMICS 2006 and the 5th International Workshop on parallel and distributed methods in Verification, PDMC 2006

ISBN: (纸本)3540709517

The proceedings contain 23 papers. The topics discussed include: challenges for formal verification in industrial setting;an easy-to-use, efficient tool-chain to analyze the availability of telecommunication equipment;discovering symmetries;on combining partial order reduction with fairness assumptions;test coverage for loose timing annotations;heuristics for ioco-based test-based modelling;verified design of an automated parking garage;evaluating quality of service for service level agreements;simulation-based performance analysis of a medical image-processing architecture;a finite state modeling of AFDX frame management using spin;automated incremental synthesis of timed automata;SAT-based verification of LTL formulas;parallel SAT solving in bounded model checking;and parallel algorithms for finding SCCs in implicitly given graphs.

关键词： Formal methods

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Advanced high-performance computer system architectures

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NUCLEAR INSTRUMENTS & methods IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT 2007年第1-2期571卷 429-432页

作者： Vinogradov, V. I. Russian Acad Sci Inst Nucl Res Moscow 117312 Russia

Convergence of computer systems and communication technologies are moving to switched high-performance modular system architectures on the basis of high-speed switched interconnections. Multi-core processors become more perspective way to high-performance system, and traditional parallel bus system architectures (VME/VXI, cPCI/PXI) are moving to new higher speed serial switched interconnections. Fundamentals in system architecture development are compact modular component strategy, low-power processor, new serial high-speed interface chips on the board, and high-speed switched fabric for SAN architectures. Overview of advanced modular concepts and new international standards for development high-performance embedded and compact modular systems for real-time applications are described. (c) 2006 Elsevier B.V. All rights reserved.

关键词： microprocessor interface system nodule network communications multiprocessor RT-system cluster interconnect electronics information technology switches telecommunications image processing data acquisition control distributed system coherent router compact node protocol convergence supercomputer data center HPC terminal

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Increasing soft classification accuracy through the use of an ensemble of classifiers

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INTERNATIONAL JOURNAL OF REMOTE SENSING 2007年第20期28卷 4609-4623页

作者： Doan, H. T. X. Foody, G. M. Univ Southampton Sch Geog Southampton SO17 1BJ Hants England

Although soft classification analyses can reduce problems such as those associated with mixed pixels that impact negatively on conventional hard classifications their accuracy is often low. One approach to increasing the accuracy of soft classifications is the use of an ensemble of classifiers, an approach which has been successful for hard classifications but rarely applied for soft classifications. Four methods for combining soft classifications to increase soft classification accuracy were assessed. These methods were based on (i) the selection of the most accurate predictions on a class-specific basis, (ii) the average of the outputs of the individual classifications for each case, (iii) the direct combination of classifications using evidential reasoning and (iv) the adaptation of the outputs to enable the use of a conventional (hard classification) ensemble approach. These four approaches were assessed with classifications of National Oceanic and Atmospheric Administration (NOAA) Advanced Very High-Resolution Radiometer (AVHRR) imagery of Australia. The data were classified using two neural networks and a probabilistic classifier. All four ensemble approaches applied to the outputs of these three classifiers were found to increase classification accuracy. Relative to the most accurate individual classification, the increases in overall accuracy derived ranged from 2.20% to 4.45%, increases that were statistically significant at 95% level of confidence. The results highlight that ensemble approaches may be used to significantly increase soft classification accuracy.

关键词： image processing CLASSIFICATION NEURAL networks (Computer science) ADVANCED very high resolution radiometers PROBABILITIES UNITED States. National Oceanic & Atmospheric Administration

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Hybrid CPU-GPU unstructured meshes parallel volume rendering on PC clusters

Hybrid CPU-GPU unstructured meshes parallel volume rendering...

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7th Eurographics Symposium on parallel Graphics and Visualization, EGPGV 2007

作者： Juliachs, M. Carrard, T. Nominé, J.-P. Laboratoire PRiSM Université de Versailles France CEA/DIF Bruyères-le-Châtel France

ISBN: (纸本)9783905673500

Large-scale numerical simulation produces datasets with ever-growing size and complexity. In particular, unstructured meshes are encountered in many applications. Volume rendering provides a way to efficiently analyze such datasets. Recent advances in graphics hardware have enabled the implementation of efficient unstructured volume rendering algorithms on the GPU. However, GPU architecture limitations make these methods difficultly amenable to a parallel implementation, which is necessary to render very large datasets at interactive speeds and high resolutions. Many previous parallel approaches have focused on software-based algorithms. In this paper, we present a hybrid object-space/image-space CPU-GPU distributed parallel volume rendering method, taking advantage of the flexibility afforded by the CPU, including SIMD processing capabilities, and using GPUs to perform repetitive tasks like depth-sorting and compositing. We present the impact of the different phases on the overall rendering time as a function of node number. © The Eurographics Association 2007.

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Numerical Simulation of a Difference Scheme Applied in image processing Based on Four-Order PDEs

Numerical Simulation of a Difference Scheme Applied in Image...

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ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and parallel/distributed Computing (SNPD)

作者： Lijie Zhang Hui Liu Yan Wang School of Sciences Qingdao Technological University Qingdao Shandong China

A difference scheme for noise removal based on four-order partial differential equations is suggested. It can approximate actual image while preserving edges and avoiding blocky effects in image processing. Numerical ... 详细信息

关键词： Numerical simulation image processing Partial differential equations Smoothing methods Software engineering Artificial intelligence distributed computing Anisotropic magnetoresistance image sensors Noise reduction

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Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and parallel/distributed Computing-Title

Eighth ACIS International Conference on Software Engineering...

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ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and parallel/distributed Computing (SNPD)

The following topics were dealt with: information assurance; cryptography and network security; component-based software engineering; software specification and architecture; software testing; requirements engineering; user-centered design methods; embedded systems; operating systems; image, speech, and signal processing; data mining and knowledge discovery; Internet technology and applications; artificial intelligence; natural language processing; neural networks and genetic algorithms; parallel and distributed computing; voice-over-IP; communication systems and networks; mobile/wireless/ad-hoc networks; collaborative computing; algorithms; visual and multimedia computing; web-based applications; E-commerce and its applications.

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Modeling and Estimation in Gaussian Graphical Models: Maximum-Entropy methods and Walk-Sum Analysis

Modeling and Estimation in Gaussian Graphical Models: Maximu...

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作者： Venkat Chandrasekaran Massachusetts Institute of Technology

学位级别：硕士

Graphical models provide a powerful formalism for statistical signal processing. Due to their sophisticated modeling capabilities, they have found applications in a variety of fields such as computer vision, image processing, and distributed sensor networks. In this the- sis we study two central signal processing problems involving Gaussian graphical models, namely modeling and estimation. The modeling problem involves learning a sparse graphi- cal model approximation to a specified distribution. The estimation problem in turn exploits this graph structure to solve high-dimensional estimation problems very efficiently. We propose a new approach for learning a thin graphical model approximation to a specified multivariate probability distribution (e. g., the empirical distribution from sample data). The selection of sparse graph structure arises naturally in our approach through the solution of a convex optimization problem, which differentiates our procedure from stan- dard combinatorial methods. In our approach, we seek the maximum entropy relaxation (MER) within an exponential family, which maximizes entropy subject to constraints that marginal distributions on small subsets of variables are close to the prescribed marginals in relative entropy. We also present a primal-dual interior point method that is scalable and tractable provided the level of relaxation is sufficient to obtain a thin graph. A crucial ele- ment of this algorithm is that we exploit sparsity of the Fisher information matrix in models defined on chordal graphs. The merits of this approach are investigated by recovering the graphical structure of some simple graphical models from sample data. Next, we present a general class of algorithms for estimation in Gaussian graphical models with arbitrary structure. These algorithms involve a sequence of inference prob- lems on tractable subgraphs over subsets of variables. This framework includes parallel iterations such as Embedded Trees, serial iterati

关键词： Electrical Engineering and Computer Science.

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