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检索条件"主题词=Algorithm development"

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MENTAT: A benchmark evaluation testbed for nonlinear filtering

MENTAT: A benchmark evaluation testbed for nonlinear filteri...

引用

Conference on Signal Processing, Sensor Fusion, and Target Recognition XIV

作者： Mahler, R Hoffman, J Chen, LJ Lockheed Martin MS2 Tact Syst Eagan MN USA

ISBN: (纸本)0819457949

Many nonlinear filtering (NLF) algorithms have been proposed in recent years for application to single-an multi-target detection and tracking. A methodology for preliminary test and evaluation (PT&E) of these algorithms is becoming increasingly necessary. Under U.S. Army Research Office funding, Scientific Systems Co. Inc. and Lockheed Martin are developing a Multi-Environment NLF Racking Assessment Testbed (MENTAT) to address this need. Once completed, MENTAT is to provide a "hierarchical" series of preliminary test and evaluation (PT&E) Monte Carlo simulated environments (including benchmark problems) of increasing difficulty and realism. The simplest MENTAT environment will consist of simple 2D scenarios with simple Gaussian-noise backgrounds and simple target maneuvers. The most complicated environments will involve: (1) increasingly more realistic simulated low-SNR backgrounds;(2) increasing motion and sensor nonlinearity;(3) increasingly higher state dimensionality;(4) increasing numbers of targets;and so on.

关键词： Sensors Signal to noise ratio Monte Carlo methods Nonlinear filtering Detection and tracking algorithms Environmental sensing algorithm development Data modeling Particle filters Target detection

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Wavefront control with algorithmic differentiation on the HiCAT testbed 10

Wavefront control with algorithmic differentiation on the Hi...

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Conference on Techniques and Instrumentation for Detection of Exoplanets X

作者： Will, Scott D. Perrin, Marshall D. Por, Emiel H. Noss, James Sahoo, Ananya Petrone, Peter Laginja, Iva Pourcelot, Raphael Redmond, Susan M. Pueyo, Laurent Groff, Tyler D. Fienup, James R. Soummer, Remi Univ Rochester Inst Opt Rochester NY 14627 USA Space Telescope Sci Inst 3700 San Martin Dr Baltimore MD 21218 USA NASA Goddard Space Flight Ctr Greenbelt MD 20771 USA Hexagon Fed Chantilly VA 20151 USA Aix Marseille Univ CNRS CNES LAM Marseille France Univ Paris Saclay ONERA DOTA F-92322 Chatillon France Univ Cote Azure Observ Cote Azure CNRS Lab Lagrange Nice France Princeton Univ Dept Mech & Aerosp Engn Princeton NJ 08540 USA

ISBN: (数字)9781510644854

ISBN: (纸本)9781510644854;9781510644847

Future space-based coronagraphs will rely critically on focal-plane wavefront sensing and control with deformable mirrors to reach deep contrast by mitigating optical aberrations in the primary beam path. Until now, most focal-plane wavefront control algorithms have been formulated in terms of Jacobian matrices, which encode the predicted effect of each deformable mirror actuator on the focal-plane electric field. A disadvantage of these methods is that Jacobian matrices can be cumbersome to compute and manipulate, particularly when the number of deformable mirror actuators is large. Recently, we proposed a new class of focal-plane wavefront control algorithms that utilize gradient-based optimization with algorithmic differentiation to compute wavefront control solutions while avoiding the explicit computation and manipulation of Jacobian matrices entirely. In simulations using a coronagraph design for the proposed Large UV/Optical/Infrared Surveyor (LUVOIR), we showed that our approach reduces overall CPU time and memory consumption compared to a Jacobian-based algorithm. Here, we expand on these results by implementing the proposed algorithm on the High Contrast Imager for Complex Aperture Telescopes (HiCAT) testbed at the Space Telescope Science Institute (STScI) and present initial experimental results, demonstrating contrast suppression capabilities equivalent to Jacobian-based methods.

关键词： Actuators Coronagraphy Optimization (mathematics) Wavefronts algorithm development Point spread functions Wavefront sensors Adaptive optics algorithms Control systems Exoplanets Space telescopes

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Shape completion for automatic inspection

Shape completion for automatic inspection

引用

Conference on Vision Systems - Applications

作者： Preston, A Forte, P KINGSTON UNIV SCH COMP SCI & ELECT SYSTKINGSTON THAMES KT1 2EESURREYENGLAND

ISBN: (纸本)0819421723

In this paper we outline an approach to a fast low-cost system for the inspection and evaluation of surface-mount assemblies and solder joints, giving particular focus to the need for robustness in such a system. We describe the software modules involved in extracting features, and shape analysis for the purpose of inspection. A common problem during the early stages of image processing is the loss of information about the edges of shape because of noise, weak contrast, or occlusion, which often increases the amount of incorrect interpretations of a given image when presented to higher levels of processing. An algorithm is described which significantly reduces the effect of such problems before information is passed to later stages of the vision process. The algorithm, which uses information about contour to correct dropouts is generic, employing no application specific information and is therefore applicable to vision systems in general.

关键词： Inspection Image processing Computing systems Image segmentation algorithm development Gaussian filters Optical inspection Reliability Sensors Shape analysis

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NUMERICAL EXPERIMENTS FOR COULOMB'S LAW PARTICLE FLOW FOR NONLINEAR FILTERS

NUMERICAL EXPERIMENTS FOR COULOMB'S LAW PARTICLE FLOW FOR NO...

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Conference on Signal and Data Processing of Small Targets

作者： Daum, Fred Huang, Jim Noushin, Arjang Raytheon Co Waltham MA 02451 USA

ISBN: (纸本)9780819487476

We show numerical results for a new nonlinear filtering algorithm that is analogous to Coulomb's law. We have invented a new theory of exact particle flow for nonlinear filters. The flow of particles corresponding to Bayes' rule is computed from the gradient of the solution of Poisson's equation, and it is analogous to Coulomb's law. Our theory is a radical departure from other particle filters in several ways: (1) we compute Bayes' rule using a flow of particles rather than as a pointwise multiplication;(2) we never resample particles;(3) we do not use a proposal density;(4) we do not use importance sampling or any other MCMC algorithm;and (5) our filter is roughly 6 to 8 orders of magnitude faster than standard particle filters for the same accuracy.

关键词： Particles Nonlinear filtering Particle filters algorithm development Signal processing Signal to noise ratio algorithms Interference (communication) Electronic filtering Filtering (signal processing)

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Comparative analysis of hyperspectral adaptive matched filter detectors

Comparative analysis of hyperspectral adaptive matched filte...

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Conference on algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI

作者： Manolakis, D Shaw, G Keshava, N MIT Lincoln Lab Lexington MA 02420 USA

ISBN: (纸本)0819436755

Real-time detection and identification of military and civilian targets from airborne platforms using hyperspectral sensors is of great interest. Relative to multispectral sensing, hyperspectral sensing can increase the detectability of pixel and subpixel size targets by exploiting finer detail in the spectral signatures of targets and natural backgrounds. A multitude of adaptive detection algorithms for resolved or subpixel targets, with known or unknown spectral characterization, in a background with known or unknown statistics, theoretically justified or ad hoc, with low or high computational complexity, have appeared in the literature or have found their way into software packages and end-user systems. The purpose of this paper is threefold. First, we present a unified mathematical treatment of most adaptive matched filter detectors using common notation, and we state clearly the underlying theoretical assumptions. Whenever possible, we express existing ad hoc algorithms as computationally simpler versions of optimal methods. Second, we assess the computational complexity of the various algorithms. Finally, we present a comparative performance analysis of the basic algorithms using theoretically obtained performance characteristics. We focus on algorithms characterized by theoretically desirable properties, practically desired features, or implementation simplicity. Sufficient detail is provided for others to verify and expand this evaluation and framework. A primary goal is to identify best-of-class algorithms for detailed performance evaluation.

关键词： Target detection Detection and tracking algorithms Sensors Antimony Digital filtering Hyperspectral target detection Statistical analysis algorithm development Picosecond phenomena algorithms

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SEGMENTATION EVALUATION AND COMPARISON - A STUDY OF VARIOUS algorithmS

SEGMENTATION EVALUATION AND COMPARISON - A STUDY OF VARIOUS ...

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Meeting on Visual Communications and Image Communication 93

作者： ZHANG, YJ DELFT UNIV TECHNOL DEPT APPL PHYSDELFTNETHERLANDS

ISBN: (纸本)0819413690

An objective and quantitative study of several representative segmentation algorithms is presented. In this study, the measurement accuracy of object features from the segmented images is taken to judge the quality of segmentation results and to assess the performance of applied algorithms. Moreover, some synthetic images are specially generated and used in test experiments. This evaluation and comparison study reveals the behavior of those algorithms within various situations, provides their performance ranking under real-like conditions, gives some limits and/or constraints for employing those algorithms in different applications, as well as indicates several potential directions for improving their performance and initiating new developments. Since the investigated algorithms are selected from different technique groups, this study also shows that the presented approach would be valid and effective for treating a wide range of segmentation algorithms.

关键词： Image segmentation Image processing algorithms and systems Signal to noise ratio algorithm development Edge detection Image processing Detection and tracking algorithms Image analysis Image filtering Linear filtering

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Fast Recovery of Compressed Multi-Contrast Magnetic Resonance Images

Fast Recovery of Compressed Multi-Contrast Magnetic Resonanc...

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Conference on Medical Imaging - Image Processing

作者： Gungor, Alper Kopanoglu, Emre Cukur, Tolga Guven, H. Emre ASELSAN Res Ctr Ankara Turkey Ihsan Dogramaci Bilkent Elect & Elect Engn Dept Ankara Turkey

ISBN: (数字)9781510607125

ISBN: (纸本)9781510607118;9781510607125

In many settings, multiple Magnetic Resonance Imaging (MRI) scans are performed with different contrast characteristics at a single patient visit. Unfortunately, MRI data-acquisition is inherently slow creating a persistent need to accelerate scans. Multi-contrast reconstruction deals with the joint reconstruction of different contrasts simultaneously. Previous approaches suggest solving a regularized optimization problem using group sparsity and/or color total variation, using composite-splitting denoising and FISTA. Yet, there is significant room for improvement in existing methods regarding computation time, ease of parameter selection, and robustness in reconstructed image quality. Selection of sparsifying transformations is critical in applications of compressed sensing. Here we propose using non-convex p-norm group sparsity (with p < 1), and apply color total variation (CTV). Our method is readily applicable to magnitude images rather than each of the real and imaginary parts separately. We use the constrained form of the problem, which allows an easier choice of data-fidelity error-bound (based on noise power determined from a noise-only scan without any RF excitation). We solve the problem using an adaptation of Alternating Direction Method of Multipliers (ADMM), which provides faster convergence in terms of CPU-time. We demonstrated the effectiveness of the method on two MR image sets (numerical brain phantom images and SRI24 atlas data) in terms of CPU-time and image quality. We show that a non-convex group sparsity function that uses the p-norm instead of the convex counterpart accelerates convergence and improves the peak-Signal-to-Noise-Ratio (pSNR), especially for highly undersampled data.

关键词： Magnetic resonance imaging Reconstruction algorithms Compressed sensing Image quality Image restoration Brain Image compression Magnetism algorithm development Denoising

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Adaptive Graph Construction for Isomap Manifold Learning 13

Adaptive Graph Construction for Isomap Manifold Learning

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Conference on Image Processing - algorithms and Systems XIII

作者： Loc Tran Zheng, Zezhong Zhou, Guoqing Li, Jiang Old Dominion Univ Dept Elect & Comp Engn Norfolk VA 23529 USA Univ Elect Sci & Technol China Sch Resources & Environm Chengdu 610054 Peoples R China Guilin Univ Technol Guangxi Key Lab Spatial Informat & Geomat Guilin Peoples R China

ISBN: (纸本)9781628414899

Isomap is a classical manifold learning approach that preserves geodesic distance of nonlinear data sets. One of the main drawbacks of this method is that it is susceptible to leaking, where a shortcut appears between normally separated portions of a manifold. We propose an adaptive graph construction approach that is based upon the sparsity property of the l(1) norm. The l(1) enhanced graph construction method replaces k-nearest neighbors in the classical approach. The proposed algorithm is first tested on the data sets from the UCI data base repository which showed that the proposed approach performs better than the classical approach. Next, the proposed approach is applied to two image data sets and achieved improved performances over standard Isomap.

关键词： Databases algorithm development Detection and tracking algorithms Lithium Principal component analysis Computer engineering Current controlled current source Geomatics Image processing Machine vision

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Unsupervised learning of a steerable basis for invariant image representations

Unsupervised learning of a steerable basis for invariant ima...

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Conference on Human Vision and Electronic Imaging XII

作者： Bethge, Matthias Gerwinn, Sebastian Macke, Jakob H. Max Planck Inst Biol Cybernet Spemannstr 38 D-72076 Tubingen Germany

ISBN: (纸本)9780819466051

There are two aspects to unsupervised learning of invariant representations of images: First, we can reduce the dimensionality of the representation by finding an optimal trade-off between temporal stability and informativeness. We show that the answer to this optimization problem is generally not unique so that there is still considerable freedom in choosing a suitable basis. Which of the many optimal representations should be selected? Here, we focus on this second aspect, and seek to find representations that are invariant under geometrical transformations occuring in sequences of natural images. We utilize ideas of 'steerability' and Lie groups, which have been developed in the context of filter design. In particular, we show how an anti-symmetric version of canonical correlation analysis can be used to learn a full-rank image basis which is steerable with respect to rotations. We provide a geometric interpretation of this algorithm by showing that it finds the two-dimensional eigensubspaces of the average bivector. For data which exhibits a variety of transformations, we develop a bivector clustering algorithm, which we use to learn a basis of generalized quadrature pairs (i.e. 'complex cells') from sequences of natural images.

关键词： Matrices Principal component analysis Independent component analysis Machine learning Signal to noise ratio Transform theory algorithm development Data modeling Canonical correlation analysis Electronic filtering

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SUPERVISED INTERPRETATION OF ECHOCARDIOGRAMS WITH A PSYCHOLOGICAL MODEL OF EXPERT SUPERVISION

SUPERVISED INTERPRETATION OF ECHOCARDIOGRAMS WITH A PSYCHOLO...

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CONF ON BIOMEDICAL IMAGE PROCESSING AND BIOMEDICAL VISUALIZATION

作者： REVANKAR, S SHER, D SHALIN, VL RAMAMURTHY, M SUNY/Buffalo (United States)

ISBN: (纸本)0819411388

We have developed a collaborative scheme that facilitates active human supervision of the binary segmentation of an echocardiogram. The scheme complements the reliability of a human expert with the precision of segmentation algorithms. In the developed system, an expert user compares the computer generated segmentation with the original image in a user friendly graphics environment, and interactively indicates the incorrectly classified regions either by pointing or by circling. The precise boundaries of the indicated regions are computed by studying original image properties at that region, and a human visual attention distribution map obtained from the published psychological and psychophysical research. We use the developed system to extract contours of heart chambers from a sequence of two dimensional echocardiograms. We are currently extending this method to incorporate a richer set of inputs from the human supervisor, to facilitate multi-classification of image regions depending on their functionality. We are integrating into our system the knowledge related constraints that cardiologists use, to improve the capabilities of our existing system. This extension involves developing a psychological model of expert reasoning, functional and relational models of typical views in echocardiograms, and corresponding interface modifications to map the suggested actions to image processing algorithms.

关键词： Image segmentation Visualization Heart Human-machine interfaces Image analysis Image processing algorithm development Telecommunications Image processing algorithms and systems Binary data

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