There are two crucial, complementary, issues faced during design and implementation of practically any but a simple image processing library. First is an ability to represent a variety of image types, typically the di...
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ISBN:
(纸本)0819426377
There are two crucial, complementary, issues faced during design and implementation of practically any but a simple image processing library. First is an ability to represent a variety of image types, typically the discriminate feature being the pixel type, e.g. binary, short integer, long integer, or floating point. The second issue is implementation of image processingalgorithms that will be able to operate on each of the supported image representations. In many traditional library designs this leads to reimplementation of the same algorithm many times, once for each possible image representation. Some attempts to alleviate this problem introduce elaborate schemes of dynamic pixel representation and registration. This results in single algorithm implementation, however, due to dynamic pixel registration, efficiency of these implementations is poor. In this paper, we investigate use of parameterized algorithms and design issues involved in implementing them in C++. We permit single expression of the algorithm to be used with any concrete representation of an image. Use of advanced features of C++ and object-oriented programming allow us to use static pixel representations, where pixel types are resolved during compile time instead of run time. This approach leads to very flexible and efficient implementations. We have both advantages: single algorithm implementation for numerous image representations, and best possible speed of execution.
This conference proceeding contains 29 papers. The areas covered are: parallel processingalgorithms and architecture;parallel processing computations and methodologies;matrixprocessingimplementations;optical signal...
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ISBN:
(纸本)0892525304
This conference proceeding contains 29 papers. The areas covered are: parallel processingalgorithms and architecture;parallel processing computations and methodologies;matrixprocessingimplementations;optical signalprocessing technology. The topics discussed include: signalprocessing computations;signal flow graph computing networks;algorithms and architectures in tomography;programmable systolic chips;systolic array processors;and optical signalprocessing systems.
This conference proceeding contains 29 papers. The areas covered are: parallel processingalgorithms and architecture;parallel processing computations and methodologies;matrixprocessingimplementations;optical signal...
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ISBN:
(纸本)0892525304
This conference proceeding contains 29 papers. The areas covered are: parallel processingalgorithms and architecture;parallel processing computations and methodologies;matrixprocessingimplementations;optical signalprocessing technology. The topics discussed include: signalprocessing computations;signal flow graph computing networks;algorithms and architectures in tomography;programmable systolic chips;systolic array processors;and optical signalprocessing systems.
A number of adaptive condition number estimators have been proposed in the past to dynamically estimate the sensitivity of the coefficient matrix of a linear systems of equations. Applications of these techniques ofte...
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ISBN:
(纸本)0819416207
A number of adaptive condition number estimators have been proposed in the past to dynamically estimate the sensitivity of the coefficient matrix of a linear systems of equations. Applications of these techniques often arise in the context of signalprocessing, where the information matrix is being updated with rank-one modifications. Various schemes, such as ACE, ALE and ICE, were proposed to cope with this problem. In this paper, we will briefly review the past work, and show how the small-sample condition estimator can be used in an adaptive manner.
Adaptive array systems require the periodic solution of the well-known w = (R) over tilde (-1)v equation in order to compute optimum adaptive array weights. The covariance matrix (R) over tilde is estimated by forming...
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ISBN:
(纸本)0819441880
Adaptive array systems require the periodic solution of the well-known w = (R) over tilde (-1)v equation in order to compute optimum adaptive array weights. The covariance matrix (R) over tilde is estimated by forming a product of noise sample matrices x : (R) over tilde = (xx)-x-H. The operations-count cost of performing the required matrix inversion in real time can be prohibitively high for a high bandwidth system with a large number of sensors. Specialized hardware may be required to execute the requisite computations in real time. The choice of algorithm to perform these computations must be considered in conjunction with the hardware technology used to implement the computation engine. A systolic architecture implementation of the Givens rotation method for matrix inversion was selected to perform adaptive weight computation. The bit-level systolic approach enables a simple ASIC design and a very low power implementation. The bit-level systolic architecture must be implemented with fixed-point arithmetic to simplify the propagation of data through the computation cells. The Givens rotation approach has a highly parallel implementation and is ideally suited for a systolic implementation. Additionally, the adaptive weights are computed directly from the sample matrixx in the voltage domain, thus reducing the required dynamic range needed in carrying out the computations. An analysis was performed to determine the required fixed-point precision needed to compute the weights for an adaptive array system operating in the presence of interference. Based on the analysis results. it was determined that the precision of a floating-point computation can be well approximated with a 13-bit to 19-bit word length fixed point computation for typical system jammer-to-noise levels. This property has produced an order-of-magnitude reduction in required hardware complexity. A synthesis-based ASIC design process was used to generate preliminary layouts. These layouts were used t
Wireless sensor networks present a number of challenges to system designers, including notably the efficient use of limited resources such as bandwidth and energy. One way these challenges can be addressed is through ...
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Wireless sensor networks present a number of challenges to system designers, including notably the efficient use of limited resources such as bandwidth and energy. One way these challenges can be addressed is through the application of signalprocessing principles in the design, deployment and operation of sensor networks. After a discussion of general issues arising in this context, this talk will describe several recent developments in this area. These include the effects of receiver choice on energy efficiency, collaborative beam-forming, sensor scheduling, and distributed learning. Some of the work described in this talk can be found in Refs. 1-8.
A two-sided (or complete) orthogonal decomposition of an m × n matrix A is a product of an orthogonal matrix, a triangular matrix, and another orthogonal matrix. Two examples are the URV and ULV decompositions. I...
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ISBN:
(纸本)0819416207
A two-sided (or complete) orthogonal decomposition of an m × n matrix A is a product of an orthogonal matrix, a triangular matrix, and another orthogonal matrix. Two examples are the URV and ULV decompositions. In this paper we present and analyze URV and ULV algorithms that are efficient whenever the numerical rank k of the matrix is much less than min(m,n). We also prove that good estimates of the singular vectors, needed in the algorithms, lead to good approximations of the singular subspaces of A.
Sensor network technology can revolutionize the study of animal ecology by providing a means of non-intrusive, simultaneous monitoring of interaction among multiple animals. In this paper, we investigate design, analy...
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Sensor network technology can revolutionize the study of animal ecology by providing a means of non-intrusive, simultaneous monitoring of interaction among multiple animals. In this paper, we investigate design, analysis, and testing of acoustic arrays for localizing acorn woodpeckers using their vocalizations.1,2 Each acoustic array consists of four microphones arranged in a square. All four audio channels within the same acoustic array are finely synchronized within a few micro seconds. We apply the approximate maximum likelihood (AML) method3 to synchronized audio channels of each acoustic array for estimating the direction-of-arrival (DOA) of woodpecker vocalizations. The woodpecker location is estimated by applying least square (LS) methods to DOA bearing crossings of multiple acoustic arrays. We have revealed the critical relation between microphone spacing of acoustic arrays and robustness of beamforming of woodpecker vocalizations. Woodpecker localization experiments using robust array element spacing in different types of environments are conducted and compared. Practical issues about calibration of acoustic array orientation are also discussed.
It is not uncommon for remote sensing systems to produce in excess of 100 Mbytes/sec. Los Alamos National Laboratory designed a reconfigurable computer to tackle the signal and image processing challenges of high band...
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It is not uncommon for remote sensing systems to produce in excess of 100 Mbytes/sec. Los Alamos National Laboratory designed a reconfigurable computer to tackle the signal and image processing challenges of high bandwidth sensors. Reconfigurable computing, based on field programmable gate arrays, offers ten to one hundred times the performance of traditional microprocessors for certain algorithms. This paper discusses the architecture of the computer and the source of performance gains, as well as an example application. The calculation of multiple matched filters applied to multispectral imagery, showing a performance advantage of forty-five over Pentium II (450 MHz), is presented as an exemplar of algorithms appropriate for this technology.
This paper describes research into a high speed image processing system using parallel digital signal processors for the processing of electro-optic images. The objective of the system is to reduce the processing time...
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ISBN:
(纸本)0819416207
This paper describes research into a high speed image processing system using parallel digital signal processors for the processing of electro-optic images. The objective of the system is to reduce the processing time of non-contact type inspection problems including industrial and medical applications. A single processor can not deliver sufficient processing power required for the use of applications hence, a MIMD system is designed and constructed to enable fast processing of electro-optic images. The Texas Instruments TMS320C40 digital signal processor is used due to its high speed floating point CPU and the support for the parallel processing environment. A custom designed VISION bus is provided to transfer images between processors. The system is being applied for solder joint inspection of high technology printed circuit boards.
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