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检索条件"主题词=Detection and tracking algorithms"

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Convex reduction of calibration charts

Convex reduction of calibration charts

引用

Conference on Photonics in the Automobile

作者： Alsam, A Hardeberg, JY Gjovik Univ Coll Gjovik Norway

ISBN: (纸本)0819456403

Calibration targets are widely used to characterize imaging devices and estimate optimal profiles to map the response of one device to the space of another. The question addressed in this paper is that of how many surfaces in a calibration target are needed to account for the whole target perfectly. To accurately answer this question we first note that the reflectance spectra space is closed and convex. Hence the extreme points of the convexhull of the data encloses the whole target. It is thus sufficient to use the extreme points to represent the whole set. Further, we introduce a volume projection algorithm to reduce the extremes to a user defined number of surfaces such that the remaining surfaces are more important, i.e. account for a larger number of surfaces, than the rest. When testing our algorithm using the Munsell book of colors of 1269 reflectances we found that as few as 110 surfaces were sufficient to account for the rest of the data and as few as 3 surfaces accounted for 86% of the volume of the whole set.

关键词： Calibration Reflectivity Principal component analysis Cameras Condition numbers Sensors Spectral calibration Scanners detection and tracking algorithms Imaging devices

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Kernel RX: A new nonlinear anomaly detector

Kernel RX: A new nonlinear anomaly detector

引用

Conference on algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XI

作者： Kwon, H Nasrabadi, NM USA Res Lab Adelphi MD 20783 USA

ISBN: (纸本)0819457914

In this paper we present a nonlinear version of the well-known anomaly detection method referred to as the RX-algorithm. Extending this algorithm to a feature space associated with the original input space via a certain nonlinear mapping function can provide a nonlinear version of the RX-algorithm. This nonlinear RX-algorithm, referred to as the kernel RX-algorithm, is basically intractable mainly due to the high dimensionality of the feature space produced by the non-linear mapping function. However, it is shown that the kernel RX-algorithm can easily be implemented by kernelizing it in terms of kennels which implicitly compute dot products in the nonlinear feature space. Improved performance of the kernel RX-algorithm over the conventional RX-algorithm is shown by testing hyperspectral imagery with military targets.

关键词： Target detection Data modeling detection and tracking algorithms Sensors Hyperspectral imaging Hyperspectral target detection Principal component analysis Statistical analysis Signal processing Infrared imaging

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Comparison between smoothing and auxiliary particle filter in tracking a maneuverable target in a multiple sensor network

Comparison between smoothing and auxiliary particle filter i...

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Conference on Acquisition, tracking, and Pointing XIX

作者： Kamel, H Badawy, W Univ Calgary Elect & Comp Engn Dept Calgary AB T2N 1N4 Canada

ISBN: (纸本)0819457957

tracking a maneuvering target weakens the performance of predictive-model-based Bayesian state estimators (Kalman Filter). Therefore, the particle is used to track maneuverable targets instead of Kalman filter and its extensions. The particle filter proved more efficiency compared to Kalman filter and its extensions, e.g. Extended Kalman Filter (EKF) and Interacting Multiple Model (IMM). Unfortunately, due to the highly uncertainty and incompleteness of the information in a highly-maneuverable target-tracking problem, the advantage of the particle filter is weakened. Both auxiliary and smoothing particle filter were proposed to overcome this problem. In this paper, we compare the performance of both auxiliary and smoothing particle filter in tracking a highly maneuverable target. We applied both algorithms to track a maneuverable target in a multiple-sensors network. Monte Carlo simulation showed that the smoothing particle filter has a better performance when compared to auxiliary particle filter in tracking a maneuvering target.

关键词： Particle filters Particles Filtering (signal processing) detection and tracking algorithms Sensor networks Digital filtering Monte Carlo methods Performance modeling Nonlinear filtering Switching

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Optimization of the HSTAMIDS landmine detection algorithm through genetic algorithms

Optimization of the HSTAMIDS landmine detection algorithm th...

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Conference on detection and Remediation Technologies for Mines and Minelike Targets X

作者： Konduri, R Solomon, G McCoy, R Duvoisin, H Bartosz, E CyTerra Corp Orlando FL 32809 USA

ISBN: (纸本)0819457795

CyTerra's dual sensor HSTAMIDS system has demonstrated promising landmine detection capabilities in extensive government-run field tests. Further optimization of the successful PentAD algorithm is desirable to maintain the high probability of detection (Pd) while lowering the false alarm rate (FAR). PentAD contains several input parameters, making such optimization using standard Monte-Carlo techniques too computationally intensive. Genetic algorithm techniques, which formerly provided substantial improvement in the detection performance of the metal detector sensor algorithm alone, have been applied to further optimize the numerical values of the dual-sensor algorithm parameters in more practical time frames. Genetic algorithm techniques have also been applied to choose among several submodels and fusion techniques to potentially train the HSTAMIDS system in new ways. An analysis of genetic algorithm results has indicated that ground type may have a significant impact on the optimal parameter set. In this presentation we discuss the performance of the resulting ground-type based genetic algorithm as applied to field data.

关键词： Genetic algorithms Land mines detection and tracking algorithms Sensors Optimization (mathematics) Genetics Principal component analysis Metals Mining Palladium

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Advanced on FPA and near FPA image processing for infrared sensors

Advanced on FPA and near FPA image processing for infrared s...

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Conference on Infrared Technology and Applications XXXI

作者： Caulfield, JT Ovod, VI Coussa, RA Baxter, CR Massie, MA Cyan Syst Santa Barbara CA 93105 USA

ISBN: (纸本)081945768X

Cyan Systems has developed algorithms and architectures capable of performing temporal and spatial filtering near or on the FPA. Cyan is performing research into more advanced techniques to allow functional target detection near/on the FPA. The goals of this work is to perform image processing near or on the FPA to improve the size and power requirements for existing IR sensor systems which require larger board sets and hardware enclosures. We use representations of the biological vision system as models for the algorithm development. We report measured data on the near/on FPA target detection performance.

关键词： Staring arrays Sensors Target detection Image processing Infrared sensors detection and tracking algorithms Algorithm development Image filtering Data processing Spatial filters

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A study of factors affecting multiple target tracking with a pixelized sensor - art. no. 59130L

A study of factors affecting multiple target tracking with a...

引用

17th Conference on Signal and Data Processing of Small Targets

作者： Morelande, MR Kreucher, CM Kastella, K Univ Melbourne Dept Elect & Elect Engn Parkville Vic 3010 Australia

ISBN: (纸本)0819459186

Factors affecting the performance of an algorithm for tracking multiple targets observed using a pixelized sensor are studied. A pixelized sensor divides the surveillance region into a grid of cells with targets generating returns on the grid according to some known probabilistic model. In previous work an efficient particle filtering algorithm was developed for multiple target tracking using such a sensor. This algorithm is the focus of the study. The performance of the algorithm is affected by several considerations. The pixelized sensor model can be used with either thresholded or non-thresholded measurements. While it is known that information is lost when measurements are thresholded, quantitative results have not been established. The development of a tractable algorithm requires that closely-spaced targets are processed jointly while targets which are far apart are processed separately. Selection of the clustering distance involves a trade-off between performance and computational expense. A final issue concerns the computation of the proposal density used in the particle filter. Variations in a certain parameter enable a trade-off between performance and computational expense. The various issues are studied using a mixture of theoretical results and Monte Carlo simulations.

关键词： Particles detection and tracking algorithms Signal to noise ratio Sensors Algorithm development Monte Carlo methods Surveillance Particle filters Target detection Solids

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Fast interpolation operations in non-rigid image registration

Fast interpolation operations in non-rigid image registratio...

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Medical Imaging 2005 Conference

作者： Jacobson, MW Fessler, JA Univ Michigan Dept EECS Ann Arbor MI 48109 USA

ISBN: (纸本)0819457213

Much literature on image registration(1-3) has worked with purely geometric image deformation models. For such models, interpolation/resampling operations are often the computationally intensive steps when iteratively minimizing the deformation cost function. This article discusses some techniques for efficiently implementing and accelerating these operations. To simplify presentation, we discuss our ideas in the context of 2D imaging. However, the concepts readily generalize to 3D. Our central technique is a table-lookup scheme that makes somewhat liberal use of RAM, but should not strain the resources of modern processors if certain design parameters are appropriately selected. The technique works by pre-interpolating and tabulating the grid values of the reference image onto a finer grid along one of the axes of the image. The lookup table can be rapidly constructed using FFTs. Our results show that this technique reduces iterative computation by an order of magnitude. When a minimization algorithm employing coordinate block alternation is used, one can obtain still faster computation by storing certain intermediate quantities as state variables. We refer to this technique as state variable hold-over. When combined with table-lookup, state variable hold-over reduces CPU time by about a factor two, as compared to table-lookup alone.

关键词： Image registration Matrices Dielectrophoresis Lung 3D modeling Convolution detection and tracking algorithms Medical imaging Imaging arrays Surgery

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Utilization of redundancy in ROI reconstruction with backprojection filtration from fan-beam truncated data

Utilization of redundancy in ROI reconstruction with backpro...

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Medical Imaging 2005 Conference

作者： Zou, Y Pan, XC Xia, D Univ Chicago Dept Radiol Chicago IL 60637 USA

ISBN: (纸本)0819457213

In fan-beam computed tomography (CT), one may be interested in image reconstruction in a region of interest (ROI) from truncated data acquired over an angular range less than half-scan data. We developed recently a backprojection filtration (BPF) algorithm to reconstruct an ROI image from reduced scan data containing data truncations. In a reduced scan., the truncated data may still contain redundancy. In this work, we describe a new algorithm that can exploit data redundancy in truncated data for potentially suppressing the aliasing and noise artifacts in reconstructed images. We have performed numerical studies to demonstrate the BPF algorithm.

关键词： Reconstruction algorithms Image segmentation Algorithm development CT reconstruction Detector arrays Data acquisition Image restoration Computed tomography Image quality detection and tracking algorithms

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Effects of registration errors on multi-look averaged data

Effects of registration errors on multi-look averaged data

引用

Conference on detection and Remediation Technologies for Mines and Minelike Targets X

作者： Ranney, K Tran, C USA Res Lab Adelphi MD 20783 USA

ISBN: (纸本)0819457795

Multi-look processing provides a straightforward method for enhancing the quality of grainy (speckle-filled) synthetic aperture radar (SAR) imagery. This improvement in quality results from a reduction in variability of the individual pixel values brought about by non-coherent averaging of multiple, statistically independent views of the same scene. That is, the variance of the average of independent, identically distributed random variables is inversely proportional to the number of independent looks that are averaged. Of course, the quality of the averaged image depends heavily on the accuracy of the algorithm used to align the individual looks prior to averaging. The Army Research Laboratory (ARL) has recently applied multi-look processing techniques to sets of images from independent views to generate look-averaged images. In the course of this processing, we have identified the need to quantify any degradation in multi-look image quality resulting from mismatches in registration of the individual looks used to form the look-averaged image. Since these degradations can affect the performance of automatic target detection algorithms, we have also identified the need to quantify the effects of look-averaged image degradation on the performance of such algorithms. In this paper, we use X-Band SAR data to determine the extent to which translational and rotational errors in the registration of individual looks degrade the quality of the resulting multi-look averaged image. We then examine how this degradation in image quality impacts the automatic detection of small targets in the final, look-averaged image. Finally, we introduce variations in target-to-clutter ratio within each of the individual looks and analyze how these changes affect the resulting look-averaged image.

关键词： Image quality Synthetic aperture radar detection and tracking algorithms Image processing Target detection Image registration Palladium Monte Carlo methods Algorithm development X band

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Registration techniques for speckle suppression in 2-D LADAR image sequences

Registration techniques for speckle suppression in 2-D LADAR...

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Conference on Image Processing - algorithms and Systems IV

作者： Sabo, MD Cain, S USAF Inst Technol Wright Patterson AFB OH 45433 USA

ISBN: (纸本)0819456454

Air Force Research Labs, Sensors Directorate has constructed and tested a coherent imaging system. The Laservision coherent imaging system resolution goals arc compatible with long range target identification based on the image characteristics of the target. The system received reflected coherent light from the laser using an optical telescope, which fed a CCD detector to collect the scene intensity. Registration of individual images remains a significant problem in the generation of accurate images collected using coherent imaging systems. An investigation of the performance of an image registration algorithm was conducted using dates collected from a, coherent optical imaging. The algorithm under study was implemented on a general-purpose computer running the MATLAB simulation environment. This paper documents the performance of the proposed technique compared to that of the cross-correlation algorithm.

关键词： Image registration Imaging systems Signal to noise ratio Speckle detection and tracking algorithms LIDAR Computer simulations Algorithm development Coherence imaging Laser systems engineering

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