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

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parallel implementation of the adaptive neighborhood contrast enhancement technique

Parallel implementation of the adaptive neighborhood contras...

引用

Proceedings of the 1999 parallel and distributed methods for image processing iii

作者： Alto, Hilary Gavrilov, Dmitri Rangayyan, Rangaraj Univ of Calgary Calgary Canada

An adaptive neighborhood contrast enhancement (ANCE) technique was developed to improve the perceptibility of features in digitized mammographic images for use in breast cancer screening. The computationally intensive algorithm was implemented on a cluster of 30 DEC Alpha processors using the message passing interface (MPI). The parallel implementation of the ANCE technique utilizes histogram-based image partitioning with each partition consisting of pixels of the same gray-level value regardless of their location in the image. The master processor allots one set of pixels to each slave processor. The slave returns the results to the master, and the master then sends a new set of pixels to the slave for processing. This procedure continues until there are no sets of pixels left. The subdivision of the original image based on gray-level values guarantees that slave processors do not process the same pixel, and is specifically well-suited to the characteristics of the ANCE algorithm. The parallelism value of the problem is approximately 16, i.e., the performance does not improve significantly when more than 16 processors are used. The result is a substantial improvement in processing time, leading to the enhancement of 4K × 4K pixel images in the range of 20 to 60 seconds.

关键词： image enhancement

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Multi-agent system for optimizing filter coefficients in image compression

Multi-agent system for optimizing filter coefficients in ima...

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Proceedings of the 1999 parallel and distributed methods for image processing iii

作者： Shang, Yi Li, Longzhuang Univ of Missouri Columbia United States

In this paper, we present a new intelligent agent-based method to design filter banks that maximize compression quality. In this method, a multi-agent system containing cooperating intelligent agents with different roles is developed to search for filter banks that improve image compression quality. The multi-agent system consists of one generalization agent, and several problem formulation, optimization, and compression agents. The generalization agent performs problem decomposition and result collection. It distributes optimization tasks to optimization agents, and later collects results and selects one solution that works well on all training images as the final output. Problem formulation agents build optimization models that are used by the optimization agents. The optimization formulation includes both the overall performance of image compression and metrics of individual filters. The compression performance is provided by the image coding agent. Optimization agents apply various optimization methods to find the best filter bank for individual training images. Our method is modular and flexible, and is suitable for distributed processing. In experiments, we applied the proposed method to a set of benchmark images and designed filter banks that improve the compression performance of existing filter banks.

关键词： image compression

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4th International ACPC conference on parallel Computation, ACPC 1999

引用

4th International ACPC conference on parallel Computation, ACPC 1999

ISBN: (纸本)3540656413

The proceedings contain 69 papers. The special focus in this conference is on parallel Numerics, parallel Computing in image processing, Video processing, and Multimedia. The topics include: Non-standard parallel solution strategies for distributed sparse linear systems;optimal tridiagonal solvers on mesh interconnection networks;parallel pivots LU algorithm on the cray T3E;experiments with parallel one-sided and two-sided algorithms for SVD;combined systolic array for matrix portrait computation;a class of explicit two-step runge-kutta methods with enlarged stability regions for parallel computers;a parallel strongly implicit algorithm for solution of diffusion equations;a parallel algorithm for lagrange interpolation on k-ary n-cubes;long range correlations among multiple processors;a monte-carlo method with inherent parallelism for numerical solving partial differential equations with boundary conditions;blocking techniques in numerical software;HPF and numerical libraries;an object library for parallel sparse array computation;performance analysis and derived parallelization strategy for a SCF program at the hartree fock level;computational issues in optimizing ophthalmic lens;parallel finite element modeling of solidification processes;architectural approaches for multimedia processing;on parallel reconfigurable architectures for image processing;parallel multiresolution image segmentation with watershed transformation and solving irregular inter-processor data dependency in image understanding tasks.

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Dense array expressions

Dense array expressions

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Proceedings of the 1999 parallel and distributed methods for image processing iii

作者： Wilson, Joseph N. Chen, Liang Ming Univ of Florida Gainesville United States

Various researchers have realized the value of implementing loop fusion to evaluate dense (pointwise) array expressions. Recently, the method of template metaprogramming in C++ has been used to significantly speed-up the evaluation of array expressions, allowing C++ programs to achieve performance comparable to or better than FORTRAN for numerical analysis applications. Unfortunately, the template metaprogramming technique suffers from several limitations in applicability, portability, and potential performance. We present a framework for evaluating dense array expressions in object-oriented programming languages. We demonstrate how this technique supports both common subexpression elimination and threaded implementation and compare its performance to object-library and hand-generated code.

关键词： parallel processing systems

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Efficient compositing methods for the sort-last-sparse parallel volume rendering system on distributed memory multicomputers

Efficient compositing methods for the sort-last-sparse paral...

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International conference on parallel processing (ICPP)

作者： Don-Lin Yang Jen-Chih Yu Yeh-Ching Chung Department of Information Engineering Feng Chia University FCU Taichung Taiwan

ISBN: (纸本)0769503500

In the sort-last-sparse parallel volume rendering system on distributed memory multicomputers, as the number of processors increases, in the rendering phase, we can get a good speedup because each processor renders images locally without communicating with other processors. However, in the compositing phase, a processor has to exchange local images with other processors. When the number of processors is over a threshold, the image compositing time becomes a bottleneck. In this paper, we proposed three compositing methods, the binary-swap with bounding rectangle method, the binary-swap with run-length encoding and static load-balancing method, and the binary-swap with bounding rectangle and run-length encoding method, to efficiently reduce the compositing time in the sort-last-sparse parallel volume rendering system on distributed memory multicomputers. The proposed methods were implemented on an SP2 parallel machine along with the binary-swap compositing method. The experimental results show that the binary-swap with bounding rectangle and run-length encoding method has the best performance among the four methods.

关键词： Rendering (computer graphics) Data visualization Encoding Partitioning algorithms Computer graphics Multiprocessing systems Ray tracing Merging

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Efficient techniques for distributed implementation of search-based AI systems

Efficient techniques for distributed implementation of searc...

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International conference on parallel processing (ICPP)

作者： G. Gupta E. Pontelli Laboratory for Logic Databases and Advanced Programming Department of Computer Science New Mexico State University Las Cruces NM USA

We study the problem of exploiting parallelism from search-based AI systems on distributed machines. We propose stack-splitting, a technique for implementing or-parallelism, which when coupled with appropriate scheduling strategies leads to: (i) reduced communication during distributed execution; and, (ii) distribution of larger grain- sized work to processors. The modified technique can also be implemented on shared memory machines and should be quite competitive with existing methods. Indeed, an implementation has been carried out on shared memory machines, and the results are reported here.

关键词： Artificial intelligence parallel processing Logic programming Laboratories Databases Computer science Read only memory Artificial neural networks Tree graphs image recognition

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Connected component labeling on a one dimensional DSP array

Connected component labeling on a one dimensional DSP array

引用

IEEE Region 10 International conference TENCON

作者： M.F. Ercan Yu-Fai Fung Department of Electrical Engineering Singapore polytechnics Singapore Department of Electrical Engineering Hong Kong Polytechnic University Hong Kong China

This paper presents a parallel implementation of connected component labeling algorithms for gray and binary images on a one-dimensional DSP array. The system is a distributed memory MIMD and all the algorithms are developed considering this platform. Performance results of several parallel connected component labeling methods are evaluated. The multi-DSP system has demonstrated a viable performance.

关键词： Labeling Digital signal processing image segmentation Merging parallel algorithms Memory architecture Partitioning algorithms Computer vision Application software Global communication

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Dynamic query re-optimization

Dynamic query re-optimization

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International Working conference on Scientific and Statistical Database Management

作者： K.W. Ng Zhenghao Wang R.R. Muntz S. Nittel Computer Science Department University of California Los Angeles CA USA

Very long running queries in database systems are not uncommon in non traditional application domains such as image processing or data warehousing analysis. Query optimization, therefore, is important. However, estimates of the query characteristics before query execution are usually inaccurate. Further, system configuration and resource availability may change during long evaluation period. As a result, queries are often evaluated with sub-optimal plan configurations. To remedy this situation, we have designed a novel approach to re-optimize suboptimal query plan configurations on-the-fly with Conquest, an extensible and distributed query processing system. A dynamic optimizer considers reconfiguration cost as well as execution cost in determining the best query plan configuration. Experimental results are presented.

关键词： Query processing parallel processing Availability Optimization methods Database systems Cost function Workstations Runtime Cyclones Sea surface

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A distributed image processing environment VIOS iii and its performance evaluation

A distributed image processing environment VIOS III and its ...

引用

14th International conference on Pattern Recognition

作者： Matsuo, H Nakada, K Iwata, A Nagoya Inst Technol Dept Elect & Comp Engn Showa Ku Nagoya Aichi 4668555 Japan

ISBN: (纸本)0818685123

We proposed a distributed image processing environment VIOS. In this paper, the third version, VIOS iii is proposed. In VIOS iii, a new parallel processing language VPE-p which has flexible syntax for describing parallel algorithms has been developed. And the new programmable buffer for accessing global variable through local area network is also proposed. The description ability for parallel image processing algorithms and processing performance using workstation clusters and multi processor system are investigated by several image processing and recognition algorithms.

关键词： Clustering algorithms

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A toolkit for parallel image processing

A toolkit for parallel image processing

引用

SPIE conference on parallel and distributed methods for image processing II

作者： Squyres, JM Lumsdaine, A Stevenson, RL Univ Notre Dame Dept Comp Sci & Engn Notre Dame IN 46556 USA

ISBN: (纸本)0819429074

In this paper, we present the design and implementation of a parallel image processing software library (the parallel image processing Toolkit). The Toolkit not only supplies a rich set of image processing routines, it is designed principally as an extensible framework containing generalized parallel computational kernels to support image processing. Users can easily add their own image processing routines without knowledge or explicit use of the underlying data distribution mechanisms or parallel computing model. Shared memory and multi-level memory hierarchies are exploited to achieve high performance on each node, thereby minimizing overall parallel execution time. Multiple load balancing schemes have been implemented within the parallel framework that transparently distribute the computational load evenly on a distributed memory computing environment. Inside the Toolkit, a message-passing model of parallelism is designed around the Message Passing Interface (MPI) standard. Experimental results are presented to demonstrate the parallel speedup obtained with the parallel image processing Toolkit in a typical workstation cluster with some common image processing tasks.

关键词： parallel image toolkit library MPI processing extensible load-balancing

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