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检索条件"任意字段=Conference on Parallel and Distributed Methods for Image Processing III"

共 552 条记录，以下是341-350 订阅

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3D Wave field phase retrieval from multi-plane observations

3D Wave field phase retrieval from multi-plane observations

引用

3DTV conference

作者： Artem Migukin Vladimir Katkovnik Jaakko Astola Department of Signal Processing Tampere University of Technology Tampere Finland

We reconstruct a spatially distributed three-dimensional (3D) wave field from a number of intensity observations, obtained in different sensor planes, parallel to the object plane. The proposed algorithm can be treated as a multiple plane iterative Gerchberg-Saxton algorithm [1]. It is obtained from the best linear estimate of the complex-valued object distribution derived for the complex-valued observations. This estimator is modified for the intensity measurements in the sensor planes. The algorithm is studied by numerical experiments performed for amplitude and phase object distributions. It is shown that the proposed method allows reconstructing the whole 3D wave fields for different setup parameters. This technique can be applied for 3D imaging. The comparison versus the successive iterative method [2] shows an accuracy advantage of the proposed algorithm provided that the type of modulation in the object plane is known.

关键词： Signal processing algorithms image reconstruction Iterative algorithms Phase measurement Optical imaging Optical interferometry Iterative methods Holography Reconstruction algorithms Optical scattering

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Design of high-speed vision system and algorithms based on distributed parallel processing architecture for target tracking

Design of high-speed vision system and algorithms based on d...

引用

2009 7th Asian Control conference, ASCC 2009

作者： Zhengtao, Zhang De, Xu Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9788995605691

A high-speed stereovision system based on smart cameras is presented to track table tennis ball. A distributed parallel processing architecture is developed to improve the real-time performance of the system. A set of novel target recognition and tracking algorithm is also proposed to distinguish the ball from the changing background with less computation and good robustness. It takes about 6ms to capture an image and extract the ball. The trajectory of the ball is well measured in real-time. The experimental results are provided to verify the effectiveness of the proposed methods. ©2009 ACA.

关键词： Target tracking

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Multiscale Data Reduction with Flexible Saliency Criterion for Biological image Analysis

Multiscale Data Reduction with Flexible Saliency Criterion f...

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Annual International conference of the IEEE-Engineering-in-Medicine-and-Biology-Society

作者： Bosl, William J. Harvard Mit Div Hlth Sci & Technol Childrens Hosp Boston Informat Program Boston MA 02115 USA

ISBN: (纸本)9781424432950

Analysis of biomedical images requires attention to image features that represent a small fraction of the total image size. A rapid method for eliminating unnecessary detail, analogous to pre-attentive processing in biological vision, allows computational resources to be applied where most needed for higher-level analysis. In this report we describe a method for bottom up merging of pixels into larger units based on flexible saliency criteria using a method similar to structured adaptive grid methods used for solving differential equations on physical domains. While creating a multiscale quadtree representation of the image, a saliency test is applied to prune the tree to eliminate unneeded details, resulting in an image with adaptive resolution. This method may be used as a first step for image segmentation and analysis and is inherently parallel, enabling implementation on programmable hardware or distributed memory clusters.

关键词： image segmentation

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A Scalable parallel Approach for Peptide Identification from Large-scale Mass Spectrometry Data

A Scalable Parallel Approach for Peptide Identification from...

引用

38th International conference on parallel processing

作者： Kulkarni, Gaurav Kalyanaraman, Ananth Cannon, William R. Baxter, Douglas Washington State Univ Sch Elect Engn & Comp Sci Pullman WA 99164 USA Pacific Northwest Natl Lab Richland WA USA

ISBN: (纸本)9781424449231

Identifying peptides, which are short polymeric chains of amino acid residues in a protein sequence, is of fundamental importance in systems biology research. The most popular approach to identify peptides is through database search. In this approach, an experimental spectrum ("query") generated from fragments of a target peptide using mass spectrometry is computationally compared with a database of already known protein sequences. The goal is to detect database peptides that are most likely to have generated the target peptide. The exponential growth rates and overwhelming sizes of biomolecular databases make this an ideal application to benefit from parallel computing. However, the present generation of software tools is not expected to scale to the magnitudes and complexities of data that will be generated in the next few years. This is because they are all either serial algorithms or parallel strategies that have been designed over inherently serial methods, thereby requiring high space- and time-requirements. In this paper, we present an efficient parallel approach for peptide identification through database search. Three key factors distinguish our approach from that of existing solutions: i) (space) Given p processors and a database with N residues, we provide the first space-optimal algorithm (O(N/p)) under distributed memory machine model;ii) (time) Our algorithm uses a combination of parallel techniques such as one-sided communication and masking of communication with computation to ensure that the overhead introduced due to parallelism is minimal;and iii) (quality) The run-time savings achieved using parallel processing has allowed us to incorporate highly accurate statistical models that have previously been demonstrated to ensure high quality prediction albeit on smaller scale data. We present the design and evaluation of two different algorithms to implement our approach. Experimental results using 2.65 million microbial proteins show linear scaling up

关键词： parallel peptide identification mass spectrometry

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Massively parallel electrical conductivity imaging of the subsurface: applications to hydrocarbon exploration

Massively parallel electrical conductivity imaging of the su...

引用

5th Annual conference of Scientific Discovery through Advanced Computing (SciDAC 2009)

作者： Newman, Gregory A. Commer, Michael Univ Calif Berkeley Lawrence Berkeley Lab Berkeley CA 94720 USA

Three-dimensional (3D) geophysical imaging is now receiving considerable attention for electrical conductivity mapping of potential offshore oil and gas reservoirs. The imaging technology employs controlled source electromagnetic (CSEM) and magnetotelluric (MT) fields and treats geological media exhibiting transverse anisotropy. Moreover when combined with established seismic methods, direct imaging of reservoir fluids is possible. Because of the size of the 3D conductivity imaging problem, strategies are required exploiting computational parallelism and optimal meshing. The algorithm thus developed has been shown to scale to tens of thousands of processors. In one imaging experiment, 32,768 tasks/processors on the IBM Watson Research Blue Gene/L supercomputer were successfully utilized. Over a 24 hour period we were able to image a large scale field data set that previously required over four months of processing time on distributed clusters based on Intel or AMD processors utilizing 1024 tasks on an InfiniBand fabric. Electrical conductivity imaging using massively parallel computational resources produces results that cannot be obtained otherwise and are consistent with timeframes required for practical exploration problems.

关键词： Supercomputers

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Real Time Low Level parallel image processing For Active Vision Systems

Real Time Low Level Parallel Image Processing For Active Vis...

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IEEE International Advance Computing conference, IACC

作者： Ashish Tanwer Rattandeep Singh Parminder Singh Reel Electronics and Communication Engineering Department Thapar University Patiala Patiala India

This paper presents an overview of low level parallel image processing algorithms and their implementation for active vision systems. Authors have demonstrated novel low level image processing algorithms for point operators, local operators, dithering, smoothing, edge detection, morphological operators, image segmentation and image compression. The algorithms have been prepared & described as pseudo codes. These algorithms have been simulated using parallel Computing Toolboxtrade (PCT) of MATLAB. The PCT provides parallel constructs in the MATLAB language, such as parallel for loops, distributed arrays and message passing & enables rapid prototyping of parallel code through an interactive parallel MATLAB session.

关键词： Real time systems image processing Machine vision MATLAB Smoothing methods image edge detection image segmentation image coding Computational modeling parallel processing

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[Title page iii]

[Title page iii]

引用

International conference on Computer Modeling and Simulation, UKSIM

The following topics are dealt: hybrid intelligent systems; biomedical simulation; bioinformatics; image processing; speech processing; signal processing; human factors; social issues; virtual reality; computer games; linear matrix control systems; power system; distributed architectures; parallel systems; Internet modelling; semantic Web; ontologies; and E-science.

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[Title page iii]

[Title page iii]

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Asia International conference on Modeling & Simulation

The following topics are dealt with: modelling; simulation; intelligent systems; soft computing; operations research; bioinformatics; biomedical simulation; discrete event systems; real-time systems; image processing; speech processing; signal processing; human factors; social sciences; economic sciences; engineering; supply chain simulation; Internet; semantic Web; ontologies; parallel architecture; distributed architecture; virtual reality; data visualization; and computer games.

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Bayesian sparse image reconstruction for MRFM

Bayesian sparse image reconstruction for MRFM

引用

International conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Nicolas Dobigeon Alfred O. Hero Jean-Yves Tourneret Department of EECS University of Michigan Ann Arbor MI USA IRIT/INP-ENSEEIHT University of Toulouse III Toulouse France

In this paper, we propose a Bayesian model and a Monte Carlo Markov chain (MCMC) algorithm for reconstructing images that consist of only few non-zero pixels. An appropriate distribution that promotes sparsity is proposed as prior distribution for the pixel values. The hyperparameters involved in the modeling are also assigned prior distributions, resulting in a hierarchical model. A Gibbs sampler allows us to draw samples distributed according the full posterior of interest. These samples are then used to approximate standard maximum a posteriori (MAP) estimator. By conducting some simulations, we show that the proposed estimator clearly outperforms previous estimators proposed in the literature.

关键词： Bayesian methods image reconstruction Monte Carlo methods Pixel Magnetic force microscopy Deconvolution Convolution Magnetic resonance Atomic force microscopy Layout

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A Scalable parallel Approach for Peptide Identification from Large-Scale Mass Spectrometry Data

A Scalable Parallel Approach for Peptide Identification from...

引用

International conference on parallel processing Workshops (ICPPW)

作者： Gaurav Kulkarni Ananth Kalyanaraman William R. Cannon Douglas Baxter School of Electrical Engineering and Computer Science Washington State University Pullman WA USA Pacific Northwest National Laboratory Richland WA USA

Identifying peptides, which are short polymeric chains of amino acid residues in a protein sequence, is of fundamental importance in systems biology research. The most popular approach to identify peptides is through database search. In this approach, an experimental spectrum ("query'') generated from fragments of a target peptide using mass spectrometry is computationally compared with a database of already known protein sequences. The goal is to detect database peptides that are most likely to have generated the target peptide. The exponential growth rates and overwhelming sizes of biomolecular databases make this an ideal application to benefit from parallel computing. However, the present generation of software tools is not expected to scale to the magnitudes and complexities of data that will be generated in the next few years. This is because they are all either serial algorithms or parallel strategies that have been designed over inherently serial methods, thereby requiring high space- and time- requirements. In this paper, we present an efficient parallel approach for peptide identification through database search. Three key factors distinguish our approach from that of existing solutions: (i) (space) Given p processors and a database with N residues, we provide the first space-optimal algorithm (O(N/p)) under distributed memory machine model; (ii) (time) Our algorithm uses a combination of parallel techniques such as one-sided communication and masking of communication with computation to ensure that the overhead introduced due to parallelism is minimal; and (iii) (quality) The run-time savings achieved using parallel processing has allowed us to incorporate highly accurate statistical models that have previously been demonstrated to ensure high quality prediction albeit on smaller scale data. We present the design and evaluation of two different algorithms to implement our approach. Experimental results using 2.65 million microbial proteins show linear sca

关键词： Peptides Large-scale systems Mass spectroscopy Databases parallel processing Proteins Algorithm design and analysis Predictive models Polymers Amino acids

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