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2010 IEEE International Symposium on parallel and distributed processing, Workshops and Phd Forum, IPDPSW 2010

作者： Byrd, Jonathan M. R. Jarvis, Stephen A. Bhalerao, Abhir H. Department of Computer Science University of Warwick Coventry CV4 7AL United Kingdom

ISBN: (纸本)9781424465347

The increasing availability of multi-core and multi-processor architectures provides new opportunities for improving the performance of many computer simulations. Markov Chain Monte Carlo (MCMC) simulations are widely used for approximate counting problems, Bayesian inference and as a means for estimating very high-dimensional integrals. As such MCMC has found a wide variety of applications in fields including computational biology and physics, financial econometrics, machine learning and image processing. Whilst divide and conquer is an obvious means to simplify image processing tasks, "naively" dividing an image into smaller images to be processed separately results in anomalies and breaks the statistical validity of the MCMC algorithm. We present a method of grouping the spatially local moves and temporarily partitioning the image to allow those moves to be processed in parallel, reducing the runtime whilst conserving the properties of the MCMC method. We calculate the theoretical reduction in runtime achievable by this method, and test its effectiveness on a number of different architectures. Experiments are presented that show reductions in runtime of 38% using a dual-core dual-processor machine. In circumstances where absolute statistical validity are not required, an algorithm based upon, but not strictly adhering to, MCMC may suffice. For such situation two additional algorithms are presented for partitioning of images to which MCMC will be applied. Assuming preconditions are met, these methods may be applied with minimal risk of anomalous results. Although the extent of the runtime reduction will be data dependent, the experiments performed showed the runtime reduced to 27% of its original value.© 2010 IEEE.

关键词： image processing

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Novel wavelength diversity technique for high speed atmospheric turbulence compensation

Novel wavelength diversity technique for high speed atmosphe...

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Conference on Sensors, and Command, Control, Communications, and Intelligence (C31) Technologies for Homeland Security and Homeland Defense IX

作者： Arrasmith, William W. Sullivan, Sean F. Florida Inst Technol Melbourne FL 32901 USA

ISBN: (纸本)9780819481306

The defense, intelligence, and homeland security communities are driving a need for software dominant, real-time or near-real time atmospheric turbulence compensated imagery. The development of parallel processing capabilities are finding application in diverse areas including image processing, target tracking, pattern recognition, and image fusion to name a few. A novel approach to the computationally intensive case of software dominant optical and near infrared imaging through atmospheric turbulence is addressed in this paper. Previously, the somewhat conventional wavelength diversity method has been used to compensate for atmospheric turbulence with great success. We apply a new correlation based approach to the wavelength diversity methodology using a parallel processing architecture enabling high speed atmospheric turbulence compensation. methods for optical imaging through distributed turbulence are discussed, simulation results are presented, and computational and performance assessments are provided.

关键词： horizontal path imaging adaptive optics image reconstruction deconvolution autocorrelation turbulence compensation image processing.

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Optimizing algebraic and neural methods for information processing in distributed fiber-optical measuring systems

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Optical Memory and Neural Networks (Information Optics) 2010年第3期19卷 237-247页

作者： Kulchin, Yu.N. Zakasovskaya, E.V. Institute for Automation and Control Processes FEB RAS ul. Radio 5 Vladivostok 690041 Russia Far-Eastern State University 8 Suhanova st. 690000 Vladivostok Russia

The paper discusses tomography reconstruction of distributed physical fields by means of fiber optical measuring systems (FOMN) [1] for parallel setup of measuring lines with a small number of scanning directions. The approach whose novelty involves measuring network geometry optimization for further application of neural or algebraic technologies to restore a full image of the functions studied is presented. An alternative to choose and apply an appropriate neural network from the set of several, previously trained neural networks of radial-basic type is investigated [2]. © 2010 Allerton Press, Inc.

关键词： Radial basis function networks

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The Java image Science Toolkit (JIST) for Rapid Prototyping and Publishing of Neuroimaging Software

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NEUROINFORMATICS 2010年第1期8卷 5-17页

作者： Lucas, Blake C. Bogovic, John A. Carass, Aaron Bazin, Pierre-Louis Prince, Jerry L. Pham, Dzung L. Landman, Bennett A. Johns Hopkins Univ Dept Biomed Engn Baltimore MD 21218 USA Johns Hopkins Univ Dept Elect & Comp Engn Baltimore MD 21218 USA NIA NIH Baltimore MD 21224 USA Johns Hopkins Univ Dept Radiol & Radiol Sci Baltimore MD 21218 USA Vanderbilt Univ Dept Elect Engn Nashville TN 37235 USA Vanderbilt Univ Dept Radiol & Radiol Sci Nashville TN 37235 USA

Non-invasive neuroimaging techniques enable extraordinarily sensitive and specific in vivo study of the structure, functional response and connectivity of biological mechanisms. With these advanced methods comes a heavy reliance on computer-based processing, analysis and interpretation. While the neuroimaging community has produced many excellent academic and commercial tool packages, new tools are often required to interpret new modalities and paradigms. Developing custom tools and ensuring interoperability with existing tools is a significant hurdle. To address these limitations, we present a new framework for algorithm development that implicitly ensures tool interoperability, generates graphical user interfaces, provides advanced batch processing tools, and, most importantly, requires minimal additional programming or computational overhead. Java-based rapid prototyping with this system is an efficient and practical approach to evaluate new algorithms since the proposed system ensures that rapidly constructed prototypes are actually fully-functional processing modules with support for multiple GUI's, a broad range of file formats, and distributed computation. Herein, we demonstrate MRI image processing with the proposed system for cortical surface extraction in large cross-sectional cohorts, provide a system for fully automated diffusion tensor image analysis, and illustrate how the system can be used as a simulation framework for the development of a new image analysis method. The system is released as open source under the Lesser GNU Public License (LGPL) through the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC).

关键词： parallel processing Pipeline Rapid prototyping image processing MRI

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Scalability in privacy-preserving data aggregation for wireless sensor networks

Scalability in privacy-preserving data aggregation for wirel...

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IEEE International Symposium on parallel and distributed processing With Applications

作者： Bista, Rabindra Shin, Young-Sung Chang, Jae-Woo Dept. of Computer Engineering Center for Advanced Image and Information Technology Chonbuk National University Chonju Chonbuk 561-756 Korea Republic of

ISBN: (纸本)9780769541907

In this paper, we propose a new privacy preserving data aggregation scheme for WSNs. Our scheme applies additive property of complex numbers in order to combine sensor data and preserve data privacy during transmission to the sink node. In addition, for supporting scalability, we propose a novel mechanism in which a special set of real numbers are assigned to sensor nodes as their IDs so that a single bit is sufficient to hold ID of a sensor node during transmission of aggregated data to the sink node. For this, we, first, generate fixed size signatures for the IDs of all sensor nodes and then superimpose the signatures during data aggregation phase. By analytical evaluations, we show that our scheme is more scalable and energy efficient than the existing methods to achieve data privacy and transmit IDs of sensor nodes along with the aggregated data to the sink node. © 2010 IEEE.

关键词： Sensor nodes

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Low cost VLSI discrete wavelet transform and FIR filters architectures for very high-speed signal and image processing

Low cost VLSI discrete wavelet transform and FIR filters arc...

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作者： Maamoun, Mountassar Bradai, Rafik Meraghni, Abdelhamid Beguenane, Rachid Department of Electronics University of Blida Blida Algeria Kouba Algeria Department of Electrical Computer Engineering Royal Military College of Canada Kingston Canada

ISBN: (纸本)9781424490233

This paper presents new VLSI architectures for finite impulse response (FIR) filters and discrete wavelet transform, intended for very high-speed signal and image processing. The proposed architectures, based on combining pipeline and parallel arithmetic methods, provide a new and very fast convolution approach with a reduced critical path. The key to this is a clever use of D-latches and multipliers which are efficiently distributed. Furthermore, an advanced discrete wavelet transform (DWT) approach, with an area-efficient architecture, is designed to produce one output in every clock cycle. As a result, a very high-speed is attained. The proposed structure can increase the work frequency (85%) at a low cost of additional hardware elements (55%). The systems are verified, using JPEG2000 coefficients filters, on Xilinx Field Programmable Gate Array (FPGA) devices. © 2010 IEEE.

关键词： FIR filters

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Integration of gpgpu methods into a pet reconstruction system

Integration of gpgpu methods into a pet reconstruction syste...

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9th IASTED International Conference on parallel and distributed Computing and Networks, PDCN 2010

作者： Schaetz, Sebastian Kucera, Markus Department of Computer Science and Mathematics University of Applied Sciences Regensburg Germany

ISBN: (纸本)9780889868205

Positron emission tomography (PET) is a medical imaging modality that allows the detection of tissue with particular properties or the observation of metabolic processes in living organisms over time. It plays a vital role in cancer diagnosis and heart examination and represents a promising method for early diagnosis of dementia. With the advancement of scanner technology as well as an ever increasing demand for higher quality images and higher patient throughput the image reconstruction system can become a bottleneck of a PET system. To meet this demand for more computing power in the reconstruction system a novel way to speed up the image reconstruction process for modern PET systems is presented. A common graphics processing device in conjunction with the Compute Unified Device Architecture (CUDA) is used to speed up existing algorithms for the CPU. Projectors for full 3D reconstruction are ported to the CUDA device and new algorithms are implemented where necessary. The main focus of this port is to speed up the calculation and to maintain the numerical accuracy of the result. On the basis of the CPU reconstruction system a new system that uses GPU projectors is implemented. With this modification a two-fold speed up is achieved compared to the highly optimized CPU implementation running on 4 CPU cores. Different optimization methods are explored and applied where suitable. The results calculated by GPU and CPU projectors are numerically identical allowing them to be interchanged. The system is validated and the algorithms are integrated into the reconstruction system of Siemens Healthcare Molecular Imaging PET scanners.

关键词： Three dimensional

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parallel processing for Secret image Sharing

Parallel Processing for Secret Image Sharing

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International Symposium on parallel and distributed processing with Applications, ISPA

作者： Wen-Pinn Fang Department of Computer Science and Information Engineering Yuanpei University Hsinchu Taiwan

Secret image sharing is a method to transmit and store an image safely. The security of secret image sharing is based on the fact that the values are operated in the finite field and the number of pixels is high enough to ensure security. However, the time complexity to encode and decode a secret image is not acceptable in real-time application. There are some papers discussing how to upgrade the efficiency of encoding phase while few papers exploring how to decrease the decoding phase time. This paper proposes a method to achieve to speed up decoding phase by parallel processing.

关键词： Decoding Cryptography Complexity theory parallel processing Pixel Finite element methods Conferences

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Size-fractionated characterization and quantification of nanoparticle release rates from a consumer spray product containing engineered nanoparticles

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JOURNAL OF NANOPARTICLE RESEARCH 2010年第7期12卷 2481-2494页

作者： Hagendorfer, Harald Lorenz, Christiane Kaegi, Ralf Sinnet, Brian Gehrig, Robert Goetz, Natalie V. Scheringer, Martin Ludwig, Christian Ulrich, Andrea EMPA Swiss Fed Labs Mat Testing & Res CH-8600 Dubendorf Switzerland ETHZ Swiss Fed Inst Technol Zurich CH-8093 Zurich Switzerland EAWAG Swiss Fed Inst Aquat Sci & Technol CH-8600 Dubendorf Switzerland Paul Scherrer Inst CH-5232 Villigen Switzerland Ecole Polytech Fed Lausanne Swiss Fed Inst Technol Lausanne CH-1015 Lausanne Switzerland

This study describes methods developed for reliable quantification of size- and element-specific release of engineered nanoparticles (ENP) from consumer spray products. A modified glove box setup was designed to allow controlled spray experiments in a particle-minimized environment. Time dependence of the particle size distribution in a size range of 10-500 nm and ENP release rates were studied using a scanning mobility particle sizer (SMPS). In parallel, the aerosol was transferred to a size-calibrated electrostatic TEM sampler. The deposited particles were investigated using electron microscopy techniques in combination with image processing software. This approach enables the chemical and morphological characterization as well as quantification of released nanoparticles from a spray product. The differentiation of solid ENP from the released nano-sized droplets was achieved by applying a thermo-desorbing unit. After optimization, the setup was applied to investigate different spray situations using both pump and gas propellant spray dispensers for a commercially available water-based nano-silver spray. The pump spray situation showed no measurable nanoparticle release, whereas in the case of the gas spray, a significant release was observed. From the results it can be assumed that the homogeneously distributed ENP from the original dispersion grow in size and change morphology during and after the spray process but still exist as nanometer particles of size < 100 nm. Furthermore, it seems that the release of ENP correlates with the generated aerosol droplet size distribution produced by the spray vessel type used. This is the first study presenting results concerning the release of ENP from spray products.

关键词： Nanoparticle release Nano-silver Engineered nanoparticles Propellant gas spray Pump spray Consumer products SMPS Electrostatic TEM sampler Electron microscopy image analysis Environment, health and safety (EHS)

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On the parallelisation of MCMC-based image processing

On the parallelisation of MCMC-based image processing

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IEEE International Symposium on parallel and distributed processing Workshops and Phd Forum (IPDPSW)

作者： Jonathan M. R. Byrd Stephen A. Jarvis Abhir H. Bhalerao Department of Computer Science University of Warwick Coventry UK

ISBN: (纸本)9781424465330

The increasing availability of multi-core and multiprocessor architectures provides new opportunities for improving the performance of many computer simulations. Markov Chain Monte Carlo (MCMC) simulations are widely used for approximate counting problems, Bayesian inference and as a means for estimating very high-dimensional integrals. As such MCMC has found a wide variety of applications in fields including computational biology and physics, financial econometrics, machine learning and image processing. Whilst divide and conquer is an obvious means to simplify image processing tasks, "naively" dividing an image into smaller images to be processed separately results in anomalies and breaks the statistical validity of the MCMC algorithm. We present a method of grouping the spatially local moves and temporarily partitioning the image to allow those moves to be processed in parallel, reducing the runtime whilst conserving the properties of the MCMC method. We calculate the theoretical reduction in runtime achievable by this method, and test its effectiveness on a number of different architectures. Experiments are presented that show reductions in runtime of 38% using a dual-core dual-processor machine. In circumstances where absolute statistical validity are not required, an algorithm based upon, but not strictly adhering to, MCMC may suffice. For such situation two additional algorithms are presented for partitioning of images to which MCMC will be applied. Assuming preconditions are met, these methods may be applied with minimal risk of anomalous results. Although the extent of the runtime reduction will be data dependent, the experiments performed showed the runtime reduced to 27% of its original value.

关键词： image processing Runtime Partitioning algorithms Availability Computer architecture Computer simulation Monte Carlo methods Biological system modeling Computational modeling Bayesian methods

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