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29th Asilomar Conference on Signals, Systems and computers, ACSSC 1995

作者： Goldstein, J. Scott Kogon, Stephen M. Reed, Irving S. Williams, Douglas B. Holder, E. Jeff USAF Rome Laboratory RL/C3BA 525 Brooks Rd. Grifilss AFBNY13441-4505 United States Statistical Signal and Image Processing Laboratory Department of Electrical Engineering University of Southern California Los AngelesCA90089-2565 United States Digital Signal Processing Laboratory School of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA30332-0250 United States

ISBN: (纸本)0818673702

This paper is concerned with reducing the rank of the adaptive weight vector in radar array signal processing. The motivation for reducing the rank is that modern space-time processing requires many more weights than can be supported on airborne and spacesegment platforms. The loss incurred in partially adaptive radar processing is that the steady-state Wiener solution of the lower rank weight vector may not perform as well as the full rank solution. Hence, this paper will be concerned with the Wiener solution of partially adaptive radar arrays and compare the performance of principal component techniques with the recently developed crossspectral technique. © 1996 IEEE.

关键词： Array processing

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Maximum-likelihood depth-from-defocus for active vision

Maximum-likelihood depth-from-defocus for active vision

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Proceedings 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots

作者： W.N. Klarquist W.S. Geisler A.C. Bovik Laboratory for Vision Systems Department of Electrical and Computer Engineering University of Texas Austin Austin TX USA Center for Vision and Image Sciences University of Texas Austin Austin TX USA

A new method for actively recovering depth information using image defocus is demonstrated and shown to support active stereo vision depth recovery by providing monocular depth estimates to guide the positioning of cameras for stereo processing. This active depth-from-defocus approach employs a spatial frequency model for image defocus which incorporates the optical transfer function of the image acquisition system and a maximum likelihood estimator to determine the amount of defocus present in a sequence of two or more images taken from the same pose. This defocus estimate is translated into a measurement of depth and associated uncertainty that is used to control the positioning of a variable baseline stereo camera system. This cooperative arrangement significantly reduces the matching uncertainty of the stereo correspondence process and increases the depth resolution obtainable with an active stereo vision platform.

关键词： Focusing Lenses Layout Cameras Robot vision systems Maximum likelihood estimation Stereo vision Laboratories Machine vision Frequency estimation

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Partially adaptive radar signal processing: the cross-spectral approach

Partially adaptive radar signal processing: the cross-spectr...

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Asilomar Conference on Signals, Systems & computers

作者： J.S. Goldstein S.M. Kogon I.S. Reed D.B. Willisms E.J. Holder USAF Rome Laboratory NY USA Statistical Signal and Image Processing LaboratoryDepartment of Electriical Engineering University of Southern California Los Angeles CA USA Digital Signal Processing LaboratorySchool of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA

This paper is concerned with reducing the rank of the adaptive weight vector in radar array signal processing. The motivation for reducing the rank is that modern space-time processing requires many more weights than can be supported on airborne and space-segment platforms. The loss incurred in partially adaptive radar processing is that the steady-state Wiener solution of the lower rank weight vector may not perform as well as the full rank solution. Hence, this paper examines the Wiener solution of partially adaptive radar arrays and compares the performance of principal component techniques with the cross-spectral technique.

关键词： Radar signal processing Laboratories Adaptive arrays Space technology Steady-state Computational complexity Adaptive filters Signal to noise ratio Signal processing algorithms Contracts

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Multiagent fault‐diagnosis expert system in power systems

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European Transactions on electrical Power 1995年第5期5卷 341-347页

作者： Wang, J.P. Trécat, J. Dr. Jianping Wang is a doctor fellow in the Faculte Polytechnique de Mons in Belgium. His current research field is parallel processing applications in power systems. Dr. Wang obtained his BS degree from Southwest Jiaotong University in P.R. Chinain 1982. From 1982 to 1990 he was appointed as an assistant lecturer. lecturer and associate professor respectively in the electrical engineering department of Southwest Jiaotong University. He obtained his Ph.D in the FacultC Polytechnique de Mons in July of 1993. (BD Dolez 3 1 FPMS B-7000 Mons Belgium T +32-65/37 41 87 Fax +32-65/37 43 00) Professor J. Trécat is a director in the power system laboratory in the Faculty Polytechnique de Mons. He obtained his Ph.D in the University of Manchester Institute of Science and Technology(UM1ST) in U.K. in 1970. He has been working in the fields of power system automation artificial intelligence application and computer vision in the Facult6 Polytechnique de Mons since 1970. He is a senior member of IEEE and he has made much contribution both in electrical engineering education and research. (BD Dolez 3 I FPMS B-7000 Mons T +32-651374185. Fax +32-6513743 00)

In order to solve the speed problem and shallow reasoning problem met in current research in fault diagnosis expert system, this paper presents a model based parallel fault diagnosis expert system for energy management systems (EMS). The Petri net model, which corresponds to the relationship between power system components and their protection systems, has been used for the inference in fault diagnosis. A multiagent parallel processing expert system, which is based on five transputers in Sun workstation, has been built for fault diagnosis purposes. The test results show that this expert system is not only fast but also has better performances. Copyright © 1995 John Wiley & Sons, Ltd.

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AN INVESTIGATION OF JPEG image AND VIDEO COMPRESSION USING PARALLEL processing

AN INVESTIGATION OF JPEG IMAGE AND VIDEO COMPRESSION USING P...

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1994 IEEE International Conference on Acoustics, Speech and Signal processing

作者： COOK, GW DELP, EJ Computer Vision Ond Image Processing Laboratory School of Electrical Engineering Purdue University West Lafayette IN 47907-1285 United States

The problem inherent with any digital image (or digital video) system is the large amount of bandwidth required for transmission or storage. This has driven the research area of image compression to develop more complex algorithms that compress images to lower data rates with better fidelity. One approach that can be used to increase the execution speed of these complex algorithms is through the use of parallel processing. In this paper we address one aspect of the parallel implementation of the JPEG still image compression standard on the MasPar MP-1, a massively parallel SIMD computer. We develop a novel byte alignment algorithm used to efficiently output compressed data from the parallel system. © 1994 IEEE.

关键词： image compression

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Velocity tuned generalized Sobel operators for multiresolution computation of optical flow

Velocity tuned generalized Sobel operators for multiresoluti...

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The 1994 1st IEEE International Conference on image processing

作者： Gökstorp, M. Danielsson, P.-E. Image Processing Laboratory Computer Engineering Division Department of Electrical Engineering Linköping University LinköpingS-581 83 Sweden

Optical flow computation may be divided into four processing steps where the first is extraction of image features suitable for flow estimation. Using a generalization of the basic flow constraint it is possible to estimate flow vectors from a set of feature images obtained from the input image sequence. Generalized Sobel operators provide a suitable set of feature extraction operators. The set of five filters up to second order provides good approximations of ideal edge and line detectors. A review of spatial and frequency constraints on optical flow suggests a multiresolution approach to optical flow where the initial feature extractors consists of velocity tuned operators. We show that two-dimensional generalized Sobel operators may be extended to spatio-temporal velocity tuned filters for optical flow estimation. Experimental results compare well to existing methods. © 1994 IEEE.

关键词： Optical flows

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An investigation of JPEG image and video compression using parallel processing

An investigation of JPEG image and video compression using p...

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

作者： G.W. Cook E.J. Delp Computer Vision and Image Processing Laboratory School of Electrical Engineering Purdue University West Lafayette IN USA

关键词： Transform coding Video compression Parallel processing image coding image storage Digital images Concurrent computing Parallel algorithms image processing Bandwidth

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Parameter estimation and segmentation of noisy or textured images using the EM algorithm and MPM estimation

Parameter estimation and segmentation of noisy or textured i...

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IEEE International Conference on image processing

作者： M.L. Comer E.J. Delp Computer Vision and Image Processing Laboratory School of Electrical Engineering Purdue University West Lafayette IN USA

Presents a new algorithm for segmentation of noisy or textured images using the expectation-maximization (EM) algorithm for estimating parameters of the probability mass function of the pixel class labels and the maximization of the posterior marginals (MPM) criterion for the segmentation operation. A Markov random field (MRF) model is used for the pixel class labels. The authors present experimental results demonstrating the use of the new algorithm on synthetic images and medical imagery.< >

关键词： Parameter estimation image segmentation Pixel Markov random fields Probability computer vision image processing Laboratories Tellurium Biomedical imaging

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Correspondence of coplanar features through P2-invariant representations 2nd

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2nd Joint European–US Workshop on Applications of Invariance in computer vision, 1993

作者： Meer, Peter Ramakrishna, Sudhir Lenz, Reiner Department of Electrical and Computer Engineering Rutgers University P.O. Box 909 PiscatawayNJ08855-0909 United States Image Processing Laboratory Department of Electrical Engineering Linköping University LinköpingS-58183 Sweden

ISBN: (纸本)9783540582403

An algorithm for establishing the correspondence between two projectively transformed sets of coplanar points (or lines) is proposed and its performance analyzed. Five-tuples of features are represented by projective/permutation (P2) invariants which are insensitive to the order of the features in the computation. Matched five-tuples yield feature correspondence hypotheses accumulated in a contingency table. The final correspondence is extracted from the table by a greedy algorithm. Positional uncertainties of up to five pixels and the presence of outliers are tolerated. © 1994, Springer Verlag. All rights reserved.

关键词： computers

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Computing depth from out-of-focus blur using a local frequency representation

Computing depth from out-of-focus blur using a local frequen...

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International Conference on Pattern Recognition

作者： M. Gokstorp Image Processing Laboratory Computer Engineering Division Department of Electrical Engineering Linkoping University Sweden

We present a method to compute depth from the amount of defocus in two images obtained from the same view-point but with different camera parameter settings. The change in defocus (blur) between the two images is proportional to the depth in the scene. We introduce a novel method to estimate the blur using a multiresolution local frequency representation of the input image pair. A confidence measure is used to discriminate between high error and low error blur estimates. Quantitative experimental results are shown for both real and synthetic images.

关键词： Layout Cameras Frequency estimation Robustness Lenses Focusing Optical imaging Geometry image processing Laboratories

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