The medical routine of the future is strongly influenced by medical information technology. The quality and efficiency of medicine are at higher standards due to the image-based methods and the increase in computation...
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A reconfigurable network termed as the reconfigurable multi-ring network (RMRN) is described. The RMRN is shown to be a truly scalable network in that each node in the network has a fixed degree of connectivity and th...
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A reconfigurable network termed as the reconfigurable multi-ring network (RMRN) is described. The RMRN is shown to be a truly scalable network in that each node in the network has a fixed degree of connectivity and the reconfiguration mechanism ensures a network diameter of O(log(2) N) for an N-processor network. Algorithms for the two-dimensional mesh and the SIMD or SPMD n-cube are shown to map very elegantly onto the RMRN. Basic message passing and reconfiguration primitives for the SIMD/SPMD RMRN are designed for use as building blocks for more complex parallel algorithms. The RMRN is shown to be a viable architecture for imageprocessing and computer vision problems using the parallel computation of the stereocorrelation imaging operation as an example. Stereocorrelation is one of the most computationally intensive imaging tasks. It is used as a visualization tool in many applications, including remote sensing, geographic information systems and robot vision.
The rapidly increasing popularity of the discrete wavelet transform (DWT) as an effective tool in many signal processing and data compression applications, and its integration into JPEG 2000 has given rise to various ...
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ISBN:
(纸本)0819437638
The rapidly increasing popularity of the discrete wavelet transform (DWT) as an effective tool in many signal processing and data compression applications, and its integration into JPEG 2000 has given rise to various DWT algorithms and their VLSI implementations to reduce complexity and enhance performance, In this paper, we present an efficient hardware implementation of the discrete wavelet transform and its deployment on a reconfigurable FPGA based platform. Our implementation is a novel architecture based on the lifting factorization of the wavelet filter banks. This factorization leads to a block based parallel DWT architecture suitable for hard-ware implementation. To overcome the communication overhead associated with the DWT block transform, we utilize the new Overlap-State(1,2) technique to compute the DWT near block boundaries. A VHDL description of the lifting polyphase factorization architecture was developed and ported to an FPGA hardware platform that was chosen to allow partial and full reconfigurability to accommodate Various applications with different filter banks. Our hardware implementation improves the performance by better than twofold speed up when compared to an efficient pipelined FPGA based implementation.
In this paper we consider a new form of connectivity in binary images, called k -width connectivity. Two pixels a and b of value “1” are in the same k -width component if and only if there exists a path of width k s...
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In this paper we consider a new form of connectivity in binary images, called k -width connectivity. Two pixels a and b of value “1” are in the same k -width component if and only if there exists a path of width k such that a is one of the k start pixels and b is one of the k end pixels of this path. We present characterizations of the k -width components and show how to determine the k -width components of an n × n image in O(n) and O (log 2 n ) time on a mesh of processors and hypercube, respectively, when the image is stored with one pixel per processor. Our methods use a reduction of the k -width-connectivity problem to the 1-width-connectivity problem. A distributed, space-efficient encoding of the k -width components of small size allows us to represent the solution using O (1) registers per processor. Our hypercube algorithm also implies an algorithm for the shuffle-exchange network.
We proposed a distributedimageprocessing environment VIOS. In this paper, the third version, VIOS III is proposed. In VIOS III, a new parallelprocessing language VPE-p which has flexible syntax for describing paral...
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ISBN:
(纸本)0818685123
We proposed a distributedimageprocessing environment VIOS. In this paper, the third version, VIOS III is proposed. In VIOS III, a new parallelprocessing 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 parallelimageprocessing algorithms and processing performance using workstation clusters and multi processor system are investigated by several imageprocessing and recognition algorithms.
Kernel density estimation is nowadays very popular tool for nonparametric probabilistic density estimation. One of its most important disadvantages is computational complexity of computations needed, especially for la...
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ISBN:
(纸本)9780769549392;9781467353212
Kernel density estimation is nowadays very popular tool for nonparametric probabilistic density estimation. One of its most important disadvantages is computational complexity of computations needed, especially for large data sets. One way for accelerating these computations is to use the parallel computing with multi-core platforms. In this paper we parallelize two kernel estimation methods such as the univariate and multivariate kernel estimation from the field of the computational econometrics on multi-core platform using different programming frameworks such as Pthreads, OpenMP, Intel Cilk++, Intel TBB, SWARM and FastFlow. The purpose of this paper is to present an extensive quantitative (i.e., performance) and qualitative (i.e., the ease of programming effort) study of the multi-core programming frameworks for these two kernel estimation methods.
This paper presents an overview of low level parallelimageprocessing algorithms and their implementation for active vision systems. Authors have demonstrated novel low level imageprocessing algorithms for point ope...
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ISBN:
(纸本)9781424429271
This paper presents an overview of low level parallelimageprocessing algorithms and their implementation for active vision systems. Authors have demonstrated novel low level imageprocessing 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 Toolbox (TM) (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
Using parallel Geographic imageprocessing System, the flooding disaster will be monitoring and evaluating in time. Using ParGIP to establish background database and process RS images, we can get the losses of the dis...
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ISBN:
(纸本)0780378407
Using parallel Geographic imageprocessing System, the flooding disaster will be monitoring and evaluating in time. Using ParGIP to establish background database and process RS images, we can get the losses of the disaster by overlaying operation in 24 hours. According to the experiment in the Poyang Lake region, this method can promote the speed and the efficiency of the monitoring and evaluating of flooding disaster to several times.
The proceedings contain 67 papers. The topics discussed include: designing parallel sparse matrix algorithms beyond data dependence analysis;run-time characterization of irregular accesses applied to parallelization o...
ISBN:
(纸本)0769512607
The proceedings contain 67 papers. The topics discussed include: designing parallel sparse matrix algorithms beyond data dependence analysis;run-time characterization of irregular accesses applied to parallelization of irregular reductions;solution of computational fluid dynamics problems on parallel computers with distributed memory;a data and task parallelimageprocessing' environment for distributed memory systems;parallel implementation of wavelet transforms on distributed-memory multicomputers;performance comparison of parallel finite element and Monte Carlo methods in optical tomography;parallel ray tracing using processor farming model;parallel domain decomposition methods for dam problem;an efficient parallel algorithm for solving unsteady nonlinear equations;partial stabilization of large-scale discrete-time linear control systems;and modular construction of model partitioning processes for parallel logic simulation.
Simulation has become an indispensable tool for researchers to explore systems without having recourse to real experiments. In this context multi-agent systems are often used to model and simulate complex systems. Dep...
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ISBN:
(纸本)9781467387767
Simulation has become an indispensable tool for researchers to explore systems without having recourse to real experiments. In this context multi-agent systems are often used to model and simulate complex systems. Depending on the characteristics of the modelled system, methods used to represent the system may vary. Whatever the modelling techniques used, increasing the size and the precision of a model increases the amount of computation needed, requiring the use of parallel systems when it becomes too large. Usually, to efficiently run on parallel resources, the model must be adapted to be distributed. In this paper, we propose a new modelling approach, based on nested graphs, that allows the design of large, complex and multi scale multi-agent models which can be efficiently distributed on parallel resources. A PDMAS (parallel and distributed Multi Agent Platform) that supports this approach and efficiently run parallel multi-agent models is introduced.
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