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

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The JPDAF in Practical Systems: Approximations

The JPDAF in Practical Systems: Approximations

引用

Conference on Signal and Data Processing of Small Targets 2010

作者： Romeo, Kevin Crouse, David F. Bar-Shalom, Yaakov Willett, Peter Univ Connecticut Dept Elect & Comp Engn Storrs CT 06269 USA

ISBN: (纸本)9780819481627

In this paper we look at various algorithms for approximating the target-measurement association probabilities of the Joint Probabilistic Data Association Filter (JPDAF). We consider their computational complexity and compare their performance with respect to the Mean Optimal Subpattern Assignment (MOSPA) statistic in a scenario involving closely-spaced targets.

关键词： detection and tracking algorithms Target detection Monte Carlo methods Computer simulations Error analysis Time metrology Algorithm development Computing systems Data processing Signal processing

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Enhancement of satellite VLBI tracking system with capability of correlator model parameters prediction

Enhancement of satellite VLBI tracking system with capabilit...

引用

International Conference on Space Information Technology 2009

作者： Shu Feng-chun Yu Yun Zheng Wei-min Zhang Xiu-zhong Chinese Acad Sci Shanghai Astron Observ Shanghai 200030 Peoples R China

ISBN: (纸本)9780819480798

Chinese VLBI Network has been successfully applied for the tracking of the earth satellite Tance-1, the lunar satellites Smart-1 and Chang'E-1. However, in the case that the orbit of the satellite has the large predicted errors, the correlator model will not be precise enough that the tracking system can not produce good fringes and VLBI observables. Based on the blind fringe-searching results by taking advantages of satellite telemetry signals, we developed an algorithm to predict correlator model parameters. In the process of model parameters prediction, the model delay polynomials are calculated from the predicted orbit, followed by the comparisons with delays obtained from the blind fringe-searching results. The delayed differences which vary much slower and smaller than the model delay is then used to form the observation equation, and finally the correction of the model parameters are predicted with the least square method. The algorithm has been implemented in the software of correlation sub-system, which worked smoothly and successfully in the real time VLBI tracking of Chang'E-1 satellite.

关键词： Satellites Optical correlators detection and tracking algorithms Algorithm development Data modeling Wavefronts Process modeling Astronomy Interferometry Motion models

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Quantitative Image Restoration

Quantitative Image Restoration

引用

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

作者： Gladkova, Irina Grossberg, Michael Shahriar, Fazlul CUNY City Coll NOAA CREST New York NY 10031 USA

ISBN: (纸本)9780819481597

Even with the most extensive precautions and careful planning, space based imagers will inevitably experience problems resulting in partial data corruption and possible loss. Such a loss occurs, for example, when individual image detectors are damaged. For a scanning imager this results in missing lines in the image. Images with missing lines can wreak havoc since algorithms not typically designed to handle missing pixels. Currently the metadata stores the locations of missing data, and naive spatial interpolation is used to fill it in. Naive interpolation methods can create image artifacts and even statistically or physically implausible image values. We present a general method, which uses non-linear statistical regression to estimate the values of the missing data in a principled manner. A statistically based estimate is desirable because it will preserve the statistical structure of the uncorrupted data and avoid the artifacts of naive interpolation. It also means that the restored images are suitable as input for higher-level statistical products. Previous methods replaced the missing values with those of a single closely related band, by applying a function or lookup table. We propose to use the redundant information in multiple bands to restore the lost information. The estimator we present in this paper uses values in a neighborhood of the pixel to be estimated, and propose a value based on training data from the uncorrupted pixels. Since we use the spatial variations in other channels, we avoid the blurring inherent spatial interpolation, which have implicit smoothness priors.

关键词： Sensors Image restoration Clouds MODIS detection and tracking algorithms Image processing Imaging systems Statistical analysis Solids Image sensors

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Bayesian SAR Imaging

Bayesian SAR Imaging

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Conference on algorithms for Synthetic Aperture Radar Imagery XVII

作者： Chen, Zhaofu Tan, Xing Xue, Ming Li, Jian Univ Florida Dept Elect & Comp Engn Gainesville FL 32611 USA

ISBN: (纸本)9780819481634

We introduce a maximum a posteriori (MAP) algorithm and a sparse learning via iterative minimization (SLIM) algorithm to synthetic aperture radar (SAR) imaging. Both MAP and SLIM are sparse signal recovery algorithms with excellent sidelobe suppression and high resolution properties. The former cyclically maximizes the a posteriori probability density function for a given sparsity promoting prior, while the latter cyclically minimizes a regularized least squares cost function. We show how MAP and SLIM can be adapted to the SAR imaging application and used to enhance the image quality. We evaluate the performance of MAP and SLIM using the simulated complex-valued backscattered data from a backhoe vehicle. The numerical results show that both MAP and SLIM satisfactorily suppress the sidelobes and yield higher resolution than the conventional matched filter or delay-and-sum (DAS) approach. MAP and SLIM outperform the widely used compressive sampling matching pursuit (CoSaMP) algorithm, which requires the delicate choice of user parameters. Compared with the recently developed iterative adaptive approach (IAA), MAP and SLIM are computationally more efficient, especially with the help of fast Fourier transform (FFT). Also, the a posteriori distribution given by the algorithms provides us with a basis for the analysis of the statistical properties of the SAR image pixels.

关键词： Synthetic aperture radar Data acquisition detection and tracking algorithms Image resolution Fourier transforms Image quality Data modeling Radar Algorithm development Statistical analysis

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Moving Target detection for a Multi-Band Pushbroom Sensor

Moving Target Detection for a Multi-Band Pushbroom Sensor

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Conference on Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications VII

作者： Cheng, Beato T. Goodrich ISR Syst Chelmsford MA 01824 USA

ISBN: (纸本)9780819481320

A pushbroom MSI sensor collects image data from the ground, parallel to the flight path, at a specific point angle. Images taken at two instances of time while the scanner moves with the platform usually have a spatial offset, and need to be registered before they can be compared for any changes between the two images. Moving target detection is a special case of change detection that requires the time between frames be small enough that a moving vehicle remains in close proximity on the two frames. We propose an algorithm for the detection of moving targets in a multi-band line scanning pushbroom sensor. Ideally, change detection works best when images have the same spectral bandwidth and are perfectly registered to one another, since differencing the two images automatically removes most of the common background signal. However, this is not always the case. For example, the sensor considered here has different bandwidths for its component bands, and since it is a line-scanner it is much more challenging regarding image registration than a framed-based scanner. In this study, we will use simulated data of the same bandwidth to demonstrate the fundamental algorithm of detection and velocity calculation. The velocity calculation is that of distance divided by time;but, depending on the focal plane layout and other operating considerations and conversion between image space to physical units, this calculation is not as simple as it seems. We will also discuss our effort in applying our algorithm to real line-scan imagery, of different bandwidths in the two channels. We will show the extra image processing efforts needed to make it work, and show some of the test results.

关键词： Image segmentation Sensors detection and tracking algorithms Target detection Image processing Image quality Raster graphics Image registration Image processing algorithms and systems Image sensors

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Joint Segmentation and Spiculation detection for Ill-defined and Spiculated Mammographic Masses

Joint Segmentation and Spiculation Detection for Ill-defined...

引用

Conference on Medical Imaging 2010 - Computer-Aided Diagnosis

作者： Tao, Yimo Lo, Shih-Chung B. Freedman, Matthew T. Xuan, Jianhua Virginia Tech Dept Elect & Comp Engn Arlington VA 22203 USA Georgetown Univ Med Ctr Dept Radiol Washington DC 20007 USA Georgetown Univ Med Ctr Dept Oncol Washington DC 20057 USA

ISBN: (纸本)9780819480255

A learning-based approach integrating the use of pixel level statistical modeling and spiculation detection is presented for the segmentation of mammographic masses with ill-defined margins and spiculations. The algorithm involves a multi-phase pixel-level classification, using a comprehensive group of regional features, to generate a pixel level mass-conditional probability map (PM). Then, mass candidate along with background clutters are extracted from the PM by integrating the prior knowledge of shape and location of masses. A multi-scale steerable ridge detection algorithm is employed to detect spiculations. Finally, all the object level findings, including mass candidate, detected spiculations, and clutters, along with the PM are integrated by graph cuts to generate the final segmentation mask. The method was tested on 54 masses (51 malignant and 3 benign), all with ill-defined margins and irregular shape or spiculations. The ground truth delineations were provided by five experienced radiologists. Area overlap ratio of 0.766 (+/- 0.144) and 0.642 (+/- 0.173) were obtained for segmenting the whole mass and only the margin portion, respectively. Williams index of area and contour based measurements indicated that segmentation results of the algorithm well agreed with the radiologists' delineation. Most importantly, the proposed approach is capable of including mass margin and its extension which are considered as key features for breast lesion analyses.

关键词： Image segmentation Phase modulation Image processing algorithms and systems Tissues detection and tracking algorithms Image enhancement Ridge detection Expectation maximization algorithms Binary data Breast

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Automatic Counterfeit Protection System Code Classification

Automatic Counterfeit Protection System Code Classification

引用

Conference on Media Forensics and Security II

作者： van Beusekom, Joost Schreyer, Marco Breuel, Thomas M. German Res Ctr Artificial Intelligence DFKI GmbH D-67663 Kaiserslautern Germany Tech Univ Kaiserslautern Dept Comp Sci D-67663 Kaiserslautern Germany

ISBN: (纸本)9780819479341

Wide availability of cheap high-quality printing techniques make document forgery an easy task that can easily be done by most people using standard computer and printing hardware. To prevent the use of color laser printers or color copiers for counterfeiting e. g. money or other valuable documents, many of these machines print Counterfeit Protection System (CPS) codes on the page. These small yellow dots encode information about the specific printer and allow the questioned document examiner in cooperation with the manufacturers to track down the printer that was used to generate the document. However, the access to the methods to decode the tracking dots pattern is restricted. The exact decoding of a tracking pattern is often not necessary, as tracking the pattern down to the printer class may be enough. In this paper we present a method that detects what CPS pattern class was used in a given document. This can be used to specify the printer class that the document was printed on. Evaluation proved an accuracy of up to 91%.

关键词： Printing Virtual point source Manufacturing Image filtering Nonimpact printing Classification systems Distance measurement Visualization detection and tracking algorithms Databases

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Biomimetic Novelty detection

Biomimetic Novelty Detection

引用

Conference on Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering VIII

作者： Ma, Lein W. Szu, Harold Univ Wisconsin Dept Biomed Engn Madison WI 53706 USA US Army RDECOM CERDEC NVESD Modeling & Simulat Div Human Signature Exploitat Branch Ft Belvoir VA USA

ISBN: (纸本)9780819481672

In the crowded rain forest, how do animals locate camouflaged prey that resemble the environment, such as walking sticks? Birds will observe the suspected stick over a period of time to determine if its behavior matches that of a tree. If the stick's behavior exceeds normal tree behavior, such as moving faster than the other branches, the bird will determine that it is actually a walking stick and not a tree branch. Once this determination is made, they will prey on the insect. Studying this natural process of novelty detection, present in a variety of animals from birds to turkey vultures, can be beneficial for numerous human applications. The spatiotemporal novelty detector will be developed using self-referencing matched filters to go beyond auto-regression. This algorithm is more than the usual change detector for it will detect a novelty behavior that exceeds its predicted value based on past data, e. g. the bird who identifies a walking stick in the forest. A scalar model is presented;however, the application can be expanded to multiple modalities for more detailed applications. Some of these applications include gas pipeline leak detection, persistent surveillance, and the creation of a smart sensor web.

关键词： Sensors Climate change Environmental sensing Independent component analysis detection and tracking algorithms Methane Surveillance Biomimetics Machine learning Autoregressive models

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Hyperspectral Sub-Pixel Target Identification using Least-Angle Regression

Hyperspectral Sub-Pixel Target Identification using Least-An...

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

作者： Villeneuve, Pierre V. Boisvert, Alex R. Stocker, Alan D. Space Comp Corp Los Angeles CA 90025 USA

ISBN: (纸本)9780819481597

A novel approach to VNIR hyperspectral target identification is presented based on the Least-Angle Regression (LARS) variable selection and model building algorithm. The problem to be solved is that of accurately identifying a target's primary signature component given a sub-pixel observation. Traditional matched detectors (MF, ACE, etc.) perform well at discriminating a target from a random cluttered background, but do not perform so well at unambiguously matching an observation with its counterpart in a large spectral library containing thousands of signatures. The LARS model-building algorithm efficiently selects a parsimonious subset of a large ensemble of model terms to optimally describe a particular target observation. The LARS solution technique is a recent addition to the family of model selection algorithms that includes Stepwise Regression, Forward Selection, and Backward Elimination. LARS is particularly well-suited to this problem as it is easily modified to enforce material abundance constraints: positive coefficients that sum to unity. Other approaches generally enforce such constraints in an ad-hoc fashion or use computationally demanding nonlinear programming solution techniques. LARS enforces these constraints as an inherent property of the model while remaining as computationally efficient as traditional sequential linear least-squares solvers. We demonstrate and quantify sub-pixel material identification performance using simulated target observations tested against large signature libraries.

关键词： Target detection detection and tracking algorithms RGB color model Target recognition Reflectivity Sensors Hyperspectral target detection Data modeling Digital filtering Feature selection

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Fast Correspondence of Unrectified Stereo Images using Genetic Algorithm and Spline Representation

Fast Correspondence of Unrectified Stereo Images using Genet...

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27th Conference on Intelligent Robots and Computer Vision: algorithms and Techniques

作者： Tippetts, Beau Lee, Dah Jye Archibald, James Brigham Young Univ Provo UT 84602 USA

ISBN: (纸本)9780819479327

Spline representations have been successfully used with a genetic algorithm to determine a disparity map for stereo image pairs. This paper describes work to modify the genetic spline algorithm to use a version of the genetic algorithm with small populations and few generations, previously referred to as "Tiny GAs", to allow algorithm implementations to achieve real-time performance. The algorithm was also targeted at unrectified stereo image pairs to reduce preprocessing making it more suitable for real-time performance. To ensure disparity map quality is preserved, the two dimensional nature of images is maintained to leverage persistent information instead of representing the images as 1-D signals as suggested in the orignal genetic spline algorithm. Experimental results are given of this modified algorithm using unrectified images.

关键词： Genetic algorithms detection and tracking algorithms Visual process modeling Genetics Computing systems Stereo vision systems Cameras Visualization Computer vision technology Machine vision

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