With advances in remote-sensing technology, the large volumes of data cannot be analyzed efficiently and rapidly, especially with arrival of high-resolution images. The development of image-processing technology is an...
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With advances in remote-sensing technology, the large volumes of data cannot be analyzed efficiently and rapidly, especially with arrival of high-resolution images. The development of image-processing technology is an urgent and complex problem for computer and geo-science experts. It involves, not only knowledge of remote sensing, but also of computing and networking. Remotely sensed images need to be processed rapidly and effectively in a distributed and parallelprocessing environment. Grid computing is a new form of distributed computing, providing an advanced computing and sharing model to solve large and computationally intensive problems. According to the basic principle of grid computing, we construct a distributedprocessing system for processing remotely sensed images. This paper focuses on the implementation of such a distributed computing and processing model based on the theory of grid computing. Firstly, problems in the field of remotely sensed imageprocessing are analyzed. Then, the distributed (and parallel) computing model design, based on grid computing, is applied. Finally, implementation methods with middleware technology are discussed in detail. From a test analysis of our system, ***, the whole image-processing system is evaluated, and the results show the feasibility of the model design and the efficiency of the remotely sensed imagedistributed and parallelprocessing system. (C) 2006 Elsevier Inc. All rights reserved.
An image algebra has been defined which is capable of expressing a wide variety of gray-level image-to-image transformations. The purpose of this paper is fourfold: (1) to introduce the reader to the basic concepts of...
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An image algebra has been defined which is capable of expressing a wide variety of gray-level image-to-image transformations. The purpose of this paper is fourfold: (1) to introduce the reader to the basic concepts of the image algebra; (2) to show how it suggests a general-purpose cellular pyramid array processor for real time imageprocessing tasks; (3) to demonstrate how the image algebra can be used to formulate the problem of mapping algorithms to specific hardware; and (4) to show how algebraic techniques can be used to develop systematic methods for deriving parallel algorithms.
A high-performance systolic machine, called Warp, is operational at Carnegie Mellon. The machine has a programmable systolic array of linearly connected cells, each capable of performing 10 million floating-point oper...
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A high-performance systolic machine, called Warp, is operational at Carnegie Mellon. The machine has a programmable systolic array of linearly connected cells, each capable of performing 10 million floating-point operations per second. Many imageprocessing operations have been programmed on the machine. This programming experience has yielded new insights in the mapping of imageprocessing operations onto a parallel computer. This paper identifies three major mapping methods that are particularly suited to a Warp-like parallel machine using a linear array of processing elements. These mapping methods correspond to partitioning of input dataset, partitioning of output dataset, and partitioning of computation along the time domain (pipelining). parallel implementations of several important imageprocessing operations are presented to illustrate the mapping methods. These operations include the Fast Fourier transform (FFT), connected component labelling, Hough transform image warping and relaxation.
In this paper, we present the design and implementation of a parallelimageprocessing software library (the parallelimageprocessing Toolkit). The Toolkit not only supplies a rich set of imageprocessing routines, i...
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ISBN:
(纸本)0819429074
In this paper, we present the design and implementation of a parallelimageprocessing software library (the parallelimageprocessing Toolkit). The Toolkit not only supplies a rich set of imageprocessing routines, it is designed principally as an extensible framework containing generalized parallel computational kernels to support imageprocessing. Users can easily add their own imageprocessing 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 parallelimageprocessing Toolkit in a typical workstation cluster with some common imageprocessing tasks.
We describe a general purpose environment for the development of parallelimageprocessing/computer vision algorithms: PRIME (parallelimage Media processing Environment). ''General purpose'' here mean...
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ISBN:
(纸本)0819425885
We describe a general purpose environment for the development of parallelimageprocessing/computer vision algorithms: PRIME (parallelimage Media processing Environment). ''General purpose'' here means that the environment is designed so as to be used on a variety of multi-processor systems ranging from tightly-coupled computers to loosely-coupled computers. The key point of the system is that it provides an architecture-independent programming environment for imageprocessing and computer vision. We show the outline of PRIME, its implementation, and its preliminary performance evaluation.
This paper describes a PC-cluster system for real-time parallel video imageprocessing. The PC-cluster consists of seven PCs connected by a very high speed network. The key issue of this system is synchronization of d...
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ISBN:
(纸本)0819429074
This paper describes a PC-cluster system for real-time parallel video imageprocessing. The PC-cluster consists of seven PCs connected by a very high speed network. The key issue of this system is synchronization of distributed video data. Frame synchronization block is introduced to realize three kinds of synchronization: forward synchronization, barrier synchronization and backward synchronization. Forward synchronization is to notify of timing to start processing. Barrier synchronization is to wait for all data that are processed at the same time. Backward synchronization is to cancel processing and transferring useless data. Experimental results are also shown to confirm the performance of the PC-cluster.
Spiral Architecture is a relatively new and powerful approach to general-purpose machine vision system. n this novel architecture, Spiral Addition and Multiplication achieve imageprocessing. As we all nown, fractal i...
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ISBN:
(纸本)1932415610
Spiral Architecture is a relatively new and powerful approach to general-purpose machine vision system. n this novel architecture, Spiral Addition and Multiplication achieve imageprocessing. As we all nown, fractal image compression methods have maximal image compression ratio, at the cost Of slow coding speed. This paper presents an algorithm to achieve high image compression ratio without slow coding speed on Spiral Architecture, which also improves the Spiral Architecture s usage in imageprocessing.
SIMD parallel systems have been employed for imageprocessing and computer vision applications since their inception. This paper describes a system in which parallel programs are implemented using a machine-independen...
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ISBN:
(纸本)0819425885
SIMD parallel systems have been employed for imageprocessing and computer vision applications since their inception. This paper describes a system in which parallel programs are implemented using a machine-independent, retargetable object library that provides SIMD execution on the Lockheed Mar-tin PAL-I SIMD parallel processor. Programs' performance on this machine is improved through on-the-fly execution analysis and scheduling. We describe the relevant elements of the system structure, the general scheme for execution analysis, and the current cost model for scheduling.
Chromosome image segmentation is an important step toward automatic karyotyping that involves visualization and interpretation of chromosomes. In this paper, we analyze the characteristics of chromosome images that ca...
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ISBN:
(纸本)0819425885
Chromosome image segmentation is an important step toward automatic karyotyping that involves visualization and interpretation of chromosomes. In this paper, we analyze the characteristics of chromosome images that can be effectively used for segmenting chromosomes and can be efficiently extracted on the Lockheed-Martin PAL parallelimage processor. We design and implement a parallel algorithm that uses local features to split touching chromosomes.
This paper presents a system for dynamic intelligent scheduling and control of reconfigurable parallel processors. The purpose of the system is to provide a rapid prototyping capability for computer vision/image proce...
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This paper presents a system for dynamic intelligent scheduling and control of reconfigurable parallel processors. The purpose of the system is to provide a rapid prototyping capability for computer vision/imageprocessing tasks. The scheduler particularly addresses the problems of algorithms with execution times that depend on the image data and processing scenarios that vary dynamically based on the input image. Since conventional scheduling methods cannot produce schedules for most tasks of this type, a dynamic controller is used to schedule the task and reconfigure the machine “on the fly.” This dynamic scheduling system attempts to balance the overall processing scenario with the needs of the individual routines that make up the task. This paper discusses the implementation of the DISC ( D ynamic I ntelligent S cheduling and C ontrol) system. Emphasis is on the scheduling heuristics as they apply to a reconfigurable parallel processor, the information in the system database, and the use of the system for prototyping computer vision/imageprocessing tasks on a partitionable parallel system.
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