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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321-330 订阅

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Performance Analysis of Mammographic image Enhancement Techniques for Early Detection of Breast Cancer

Performance Analysis of Mammographic Image Enhancement Techn...

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1st International conference on Computer Science, Engineering and Information Technology (CCSEIT 2011)

作者： Singh, Shailaja Yadav, Anamika Singh, Bikesh Kumar MPCCET Dept Comp Sci & Engn Bhilai India NIT Dept Elect Engn Raipur Madhya Pradesh India

ISBN: (纸本)9783642240362;9783642240379

Mammogram breast cancer images have the ability to assist physician in detection of disease caused by cells normal growth. Developing algorithms and software to analyse these images may also assist physicians in their daily work. Micro calcifications are tiny calcium deposits in breast tissues. They appear as small bright spots on mammograms. Since micro calcifications are small and subtle abnormalities, they may he overlooked by an examining radiologist. image Enhancement and Filtering is always the root process in many medical image processing applications. It is aimed at reducing noise in images. In this paper we have made comparison between several novel and hybrid enhancement techniques. The comparison is based on the basis of performance evaluation parameters (statistical parameter) such as PSNR, and CNR. These can be used for identifying breast nodule malignancy to provide better chance of a proper treatment. These methods are tested on digital mammograms present in mini-MIAS database.

关键词： Mammograms image Enhancement Spatial Filtering Contrast to noise ratio (CNR) Signal to noise ratio (PSNR)

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parallel Implementation of Edge-Directed image Interpolation on a Graphics processing Unit

Parallel Implementation of Edge-Directed Image Interpolation...

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International conference on parallel and distributed Systems (ICPADS)

作者： Jiaji Wu Tao Li Bormin Huang School of Electronic Engineering Xidian University Xi'an China Space Science and Engineering Center University of Wisconsin-Madison Madison USA

The edge-directed interpolation scheme is a non-iterative, orientation-adaptive method to enhance image resolution with better visual effect than conventional interpolation methods. It interpolates the missing pixels based on the covariance of a high-resolution image estimated from the covariance of the low-resolution image. In spite of the impressive performance, the computational complexity of covariance-based adaptation is significantly higher than that of the conventional linear interpolation algorithms. In this paper, we propose a GPU-based massively parallel version of the edge-directed interpolation scheme. A speedup of 61.7x can be achieved with respect to its single-threaded CPU counterpart in the host computer.

关键词： Interpolation Graphics processing unit Instruction sets image edge detection Streaming media Kernel Registers

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Informatics Engineering and Information Science, Part iii 2011

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丛书名： Communications in Computer and Information Science

2011年

作者： Azizah Abd Manaf Shamsul Sahibuddin Rabiah Ahmad Salwani Mohd Daud Eyas El-Qawasmeh

ISBN: (数字)9783642254628

ISBN: (纸本)9783642254611

This 4-Volume-Set, CCIS 0251 - CCIS 0254, constitutes the refereed proceedings of the International conference on Informatics Engineering and Information Science, ICIEIS 2011, held in Kuala Lumpur, Malaysia, in November 2011. The 210 revised full papers presented together with invited papers in the 4 volumes were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on e-learning, information security, software engineering, image processing, algorithms, artificial intelligence and soft computing, e-commerce, data mining, neural networks, social networks, grid computing, biometric technologies, networks, distributed and parallel computing, wireless networks, information and data management, web applications and software systems, multimedia, ad hoc networks, mobile computing, as well as miscellaneous topics in digital information and communications.

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Phase Map Generation for Phase Shift Moire Using CUDA

Phase Map Generation for Phase Shift Moire Using CUDA

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IEEE International conference on parallel and distributed Computing, Applications and Technologies (PDCAT)

作者： Sudhakar Sah YoungJun Roh KyoungSeop Chang DaeHwa Jeong Center of Research in Engr Sciences and Tech-CREST KPIT Cummins Infosystems Limited Pune India FPG Productivity Research Institute LG Electronics Inc. South Korea

Phase shift Moiré is a very popular and one of the most successful techniques for shape measurement of 3-D objects such as PCB (printed circuit board), TFT (thin film transistor), LCD (Liquid crystal display) etc. Various implementations of phase shift moiré are available for improving accuracy and/or speed. Although, these methods contribute a lot in reducing the computation with some compromise in accuracy, there is a lot of scope of improving the performance of these algorithms with increased accuracy, especially when specialized hardware like GPU is available. GPU contains many core or processing elements that can process the same work concurrently resulting in dramatic increase in performance. In this paper, we propose the parallel implementation of the phase shift moiré method on CUDA. A novel method called image stacking method is proposed that can also be used for CUDA implementation of similar algorithms to improve performance. Using this technique, we are able to execute the application 180 times faster compared to the CPU implementation.

关键词： Graphics processing unit Instruction sets Kernel Three dimensional displays Computer architecture Pipeline processing Stacking

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FPGA Design of an Automatic Target Generation Process for Hyperspectral image Analysis

FPGA Design of an Automatic Target Generation Process for Hy...

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International conference on parallel and distributed Systems (ICPADS)

作者： Sergio Bernabe Sebasti´n Lopez Antonio Plaza Roberto Sarmiento Pablo Garcia Rodriguez Hyperspectral Computing Laboratory Department of Technology of Computers and Communications University of Extremadura Caceres Spain Institute for Applied Microelectronics (IUMA) University of Las Palmas de Gran Canaria Tafira Baja Spain Grupo de Ingeniería de Medios (GIM) University of Extremadura Caceres Spain

Onboard processing of remotely sensed hyper spectral data is a highly desirable goal in many applications. For this purpose, compact reconfigurable hardware modules such as field programmable gate arrays (FPGAs) are widely used. In this paper, we develop a new implementation of an automatic target generation process (ATGP) for hyper spectral images. Our implementation is based on a design methodology that starts from a high-level description in Matlab (or alternative C/C++) and obtains a register transfer level (RTL) description that can be ported to FPGAs. In order to validate our new implementation, we develop a quantitative and comparative study using two different FPGA architectures: Xilinx Virtex-5 and Altera Stratix-iii Altera. Experimental results have been obtained in the context of a real application focused on the detection of mineral components over the Cup rite mining district (Nevada), using hyper spectral data collected by NASA's Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS). Our experimental results indicate that the proposed implementation can achieve peak frequency designs above 200MHz in the considered FPGAs, in addition to satisfactory results in terms of target detection accuracy and parallel performance. This represents a step forward towards the design of real-time onboard implementations of hyper spectral image analysis algorithms.

关键词： Field programmable gate arrays Hyperspectral imaging Algorithm design and analysis Hardware Vectors image analysis

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Architecture-Aware Mapping and Optimization on a 1600-Core GPU

Architecture-Aware Mapping and Optimization on a 1600-Core G...

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International conference on parallel and distributed Systems (ICPADS)

作者： Mayank Daga Thomas Scogland Wu-chun Feng Department of Computer Science Virginia Tech USA USA

The graphics processing unit (GPU) continues to make in-roads as a computational accelerator for high-performance computing (HPC). However, despite its increasing popularity, mapping and optimizing GPU code remains a difficult task, it is a multi-dimensional problem that requires deep technical knowledge of GPU architecture. Although substantial literature exists on how to map and optimize GPU performance on the more mature NVIDIA CUDA architecture, the converse is true for OpenCL on an AMD GPU, such as the 1600-core AMD Radeon HD 5870 GPU. Consequently, we present and evaluate architecture-aware mapping and optimizations for the AMD GPU. The most prominent of which include (i) explicit use of registers, (ii) use of vector types, (iii) removal of branches, and (iv) use of image memory for global data. We demonstrate the efficacy of our AMD GPU mapping and optimizations by applying each in isolation as well as in concert to a large-scale, molecular modeling application called GEM. Via these AMD-specific GPU optimizations, our optimized OpenCL implementation on an AMD Radeon HD 5870 delivers more than a four-fold improvement in performance over the basic OpenCL implementation. In addition, it outperforms our optimized CUDA version on an NVIDIA GTX280 by 12%. Overall, we achieve a speedup of 371-fold over a serial but hand-tuned SSE version of our molecular modeling application, and in turn, a 46-fold speedup over an ideal scaling on an 8-core CPU.

关键词： Graphics processing unit Optimization Kernel Instruction sets Computer architecture Vectors Registers

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distributed TARGET DETECTION IN CENTRALIZED WIRELESS SENSOR NETWORKS WITH COMMUNICATION CONSTRAINTS

DISTRIBUTED TARGET DETECTION IN CENTRALIZED WIRELESS SENSOR ...

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European Signal processing conference

作者： Jose Luis Barbosa David Luengo EXPAL S.A. Dpto. de Teoria de la Senal y Comunicaciones Universidad Carlos III de Madrid

distributed inference is an important and challenging problem in wireless sensor networks (WSNs). In this paper we consider distributed detection of a target in centralized WSNs (i.e. WSNs with a fusion centre) subject to communication constraints. We focus on the parallel network topology, where the sensors can only exchange information with the fusion centre, and consider conditionally dependent observations. We develop two types of local decision rules for the sensors (binary and binary with abstention), based on the Neyman-Pearson criterion, and a fusion rule based on a support vector machine (SVM). Under these circumstances we show empirically that, even when individual sensors with very poor performance are used, both local configurations are able to provide very good detection rates as the number of nodes increases.

关键词： Wireless sensor networks Support vector machines Sensor fusion Noise Training Approximation methods

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Acceleration of Two Point Correlation Function Calculation for Pathology image Segmentation

Acceleration of Two Point Correlation Function Calculation f...

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IEEE International conference on Healthcare Informatics, Imaging and Systems Biology (HISB)

作者： Lee A.D. Cooper Joel H. Saltz Umit Catalyurek Kun Huang Center of Comprehensive Informatics Emory University Atlanta GA USA Department of Biomedical Informatics Ohio State University Columbus OH USA

The segmentation of tissue regions in high-resolution microscopy is a challenging problem due to both the size and appearance of digitized pathology sections. The two point correlation function (TPCF) has proved to be an effective feature to address the textural appearance of tissues. However the calculation of the TPCF functions is computationally burdensome and often intractable in the gigapixel images produced by slide scanning devices for pathology application. In this paper we present several approaches for accelerating deterministic calculation of point correlation functions using theory to reduce computation, parallelization on distributed systems, and parallelization on graphics processors. Previously we show that the correlation updating method of calculation offers an 8-35x speedup over frequency domain methods and decouples efficient computation from the select scales of Fourier methods. In this paper, using distributed computation on 64 compute nodes provides a further 42x speedup. Finally, parallelization on graphics processors (GPU) results in an additional 11-16x speedup using an implementation capable of running on a single desktop machine.

关键词： Correlation Graphics processing unit parallel processing Instruction sets image segmentation Interpolation

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Labeling skin tissues in ultrasound images using a generalized Rayleigh mixture model

Labeling skin tissues in ultrasound images using a generaliz...

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

作者： Marcelo Pereyra Nicolas Dobigeon Hadj Batatia Jean-Yves Tourneret IRIT/INP-ENSEEIHT University of Toulouse III Toulouse France

This paper addresses the problem of estimating the statistical distribution of multiple-tissue non-stationary ultrasound images of skin. The distribution of multiple-tissue images is modeled as a finite mixture of Heavy-Tailed Rayleigh distributions. An original Bayesian algorithm combined with a Markov chain Monte Carlo method is then derived to jointly estimate the mixture parameters and a label vector associating each voxel to a tissue. Precisely, a hybrid Metropolis-within-Gibbs sampler is proposed to draw samples that are asymptotically distributed according to the posterior distribution of the Bayesian model. These samples are then used to compute the Bayesian estimators of the model parameters. Simulation results are conducted on synthetic data to illustrate the performance of the proposed estimation strategy. The method is then successfully applied to the detection of an in-vivo skin lesion in a high frequency 3D ultrasound image.

关键词： Ultrasonic imaging Skin Bayesian methods Markov processes Lesions Biological system modeling Manganese

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Research on Acquisition methods of High-Precision DEM for distributed Hydrological Model

Research on Acquisition Methods of High-Precision DEM for Di...

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Computer and Computing Technologies in Agriculture IV——4th IFIP TC 12 conference(CCTA2010) Part iii

作者： Li Deng Yong Liang Chengming Zhang School of Information Science and Engineering Shandong Agricultural University

Compared with the traditional lumped hydrological models,distributed hydrological model,considering the effects of the uneven spatial distribution of watershed land surface on the hydrological cycle,has the characteristic of physical *** from overall structure,there are two types of distributed hydrological model,which are runoff and *** establishment of convergence network is on the basis of calculating reservoir routing convergence,at present,converged networks are constructed on the grounds of DEM,the resolution of DEM directly affects the result of convergence network construction,for now,due to confidentiality rules,it is very difficult to obtain high-resolution *** the development of GIS and RS,it is more convenient to acquire data from distributed hydrological model,which has been developing *** is completed by the National Aeronautics and Space Administration(NASA),National image Mapping Agency(NIMA) and the German and Italian space *** current publicly available data resolution is 3 arc seconds(1 /1200 of longitude and latitude),and its length is equivalent to90 *** publication of this data set is an important breakthrough in geographical science and application,which has important application ***,because of the limitations on using radar technology to obtain surface elevation data,there are many problems in the original SRTM DEM data,such as missing more regional data,existing many abnormal points,and so *** article,which takes Xue Ye reservoir area as example,studies the methods of processing SRTM data and obtained high-resolution DEM data of the region.

关键词： DEM Research on Acquisition methods of High-Precision DEM for distributed Hydrological Model

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