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Comparison of registration techniques for speckle suppression in 2D LADAR image sequences

Comparison of registration techniques for speckle suppressio...

引用

Conference on Applications of Digital Image Processing XXVII

作者： MacDonald, MA Armstrong, E Cain, S Cain, A USAF Inst Technol Wright Patterson AFB OH 45433 USA

ISBN: (纸本)0819454966

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 eight distinct image registration algorithms was conducted using data collected from a coherent optical imaging system developed by the Air Force Research Laboratories, Sensors Division, ARFL/SNJT. A total of 400 images of three distinct scenes were collected by SRJT and made available to the Air Force Institute of Technology (AFIT) for this study. Scenery was collected at 3 and 10 kilometers of wheeled vehicles supporting resolution and uniform target boards. The algorithms under study were developed by scientists and engineers at AFRL, and had varying levels of performance in terms of image miss-registration and execution time. These eight algorithms were implemented on a general-purpose computer running the MATLAB simulation environment. The algorithms compared included: block-match, cross-correlation, cross-search, directional-search, gradient-based, hierarchical-block, three-step, and vector-block methods. It was found that the cross-correlation, gradient-based and vector-block search techniques typically had the lowest error metric. The vector-block and cross-correlation methods proved to have the fastest execution times, while not suffering significant error degradation when estimating the registration shift of the test images.

关键词： Image registration Algorithm development Image processing detection and tracking algorithms Imaging systems Coherence imaging Speckle Image restoration Computer simulations LIDAR

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Target preference in multitarget sensor management: A unified approach

Target preference in multitarget sensor management: A unifie...

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

作者： Mahler, R Lockheed Martin MS2 Tact Syst Eagan MN USA

ISBN: (纸本)0819453528

Sensor management algorithms must be capable of directing sensing resources preferentially to known or potential Targets of Interest (ToIs) having high tactical importance. In principle one could simply wait until accumulated information strongly suggests that particular targets axe probable ToIs and then bias the allocation of sensor resources to those targets. However, such ad hoc techniques have inherent limitations. To avoid these limitations target preference must be incorporated into the fundamental statistical description of multisensor-multitarget problems. In this paper we show that finite-set statistics (FISST) has built-in mathematical tools for doing this, thereby allowing target preference to be incorporated into sensor management objective functions.

关键词： Sensors Digital filtering Fuzzy logic Image filtering Mathematical modeling Optical correlators Statistical modeling Data fusion detection and tracking algorithms Missiles

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Evaluation of an approximate crosscovariance calculation for track-to-track fusion

Evaluation of an approximate crosscovariance calculation for...

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16th Conference on Signal and Data Processing of Small Targets

作者： Sinav, A Balci, AM Bar-Shalom, Y Turkish Navy Res & Dev Ctr Command Istanbul Turkey

ISBN: (纸本)081945351X

The effect of the crosscovariance in track-to-track fusion has been studied in [2] [3] [4] [5]. Ignoring the crosscovariance of the local track estimation errors leads to optimistic covariance for the fused state estimates. However, evaluation of this crosscovariance is too demanding. Consequently, we approximate the crosscovariances between two sensors' track estimation errors in a manner similar to one of the procedures presented in [2], namely, with constant crosscorrelation coefficients. The results of using this in a practical naval surveillance system are discussed by comparing the exact covariances;of the fused tracks, the covariances obtained with the approximation and the covariances obtained by completely ignoring the crosscorrelations.

关键词： Error analysis Sensors Monte Carlo methods Filtering (signal processing) Matrices Radar Surveillance systems Computer engineering detection and tracking algorithms Sensor fusion

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IR and SAR automatic target detection benchmarks

IR and SAR automatic target detection benchmarks

引用

14th Conference on Automatic Target Recognition

作者： Jaeger, U Maier-Herburger, H Stahl, C Heinze, N Willersinn, D Fraunhofer Inst Informat & Data Proc D-76131 Karlsruhe Germany

ISBN: (纸本)0819453498

This contribution describes the results of a collaboration the objective of which was to technically validate an assessment approach for automatic target recognition (ATR) components'. The approach is intended to become a standard for component specification and acceptance test during development and procurement and includes the provision of appropriate tools and data. The collaboration was coordinated by the German Federal Office for Defense Technology and Procurement (BWB). Partners besides the BWB and the group Assessment of Fraunhofer IITB were ATR development groups of EADS Military Aircraft, EADS Dornier and Fraunhofer IITB. The ATR development group of IITB contributed ATR results and developer's expertise to the collaboration while the industrial partners contributed ATR results and their expertise both from the developer's and the system integrator's point of view. The assessment group's responsibility was to provide task-relevant data and assessment tools, to carry out performance analyses and to document major milestones. The result of the collaboration is twofold: the validation of the assessment approach by all partners, and two approved benchmarks for specific military target detection tasks in IR and SAR images. The tasks are defined by parameters including sensor, viewing geometries, targets, background etc. The benchmarks contain IR and SAR sensor data, respectively. Truth data and assessment tools are available for performance measurement and analysis. The datasets are split into training data for ATR optimization and test data exclusively used for performance analyses during acceptance tests. Training data and assessment tools are available for ATR developers upon request. The work reported in this contribution was supported by the German Federal Office for Defense Technology and Procurement (BWB), EADS Dornier, and EADS Military Aircraft.

关键词： Automatic target recognition Algorithm development Synthetic aperture radar detection and tracking algorithms Fourier transforms Target detection Infrared imaging Standards development Infrared sensors Defense technologies

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Feature-aided tracking of ground targets using a class-independent approach

Feature-aided tracking of ground targets using a class-indep...

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

作者： Sullivan, K Agate, C Beckman, D Toyon Res Corp Goleta CA 93117 USA

ISBN: (纸本)0819453528

We have developed and implemented an approach to performing feature-aided tracking (FAT) of ground vehicles using ground moving target indicator (GMTI) radar measurements. The feature information comes in the form of high-range resolution (HRR) profiles when the GMTI radar is operating in the HRR mode. We use a Bayesian approach where we compute a feature association likelihood that is combined with a kinematic association likelihood. The kinematic association likelihood is found using an IMM filter that has onroad, offroad, and stopped motion models. The feature association likelihood is computed by comparing new measurements to a database of measurements that are collected and stored on each object in track. The database consists of features that have been collected prior to the initiation of the track as well as new measurements that were used to update the track. We have implemented and tested our algorithm using the SLAMEM(TM) simulation.

关键词： Motion models Roads Kinematics Databases detection and tracking algorithms Radar Data modeling Monte Carlo methods Target detection Time metrology

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Operational calibration of solar reflectance channels of the Advanced Very High Resolution Radiometer (AVHRR)

Operational calibration of solar reflectance channels of the...

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Conference on Earth Observing Systems IX

作者： Wu, XQ NOAA NESDIS Off Res & Applicat Camp Springs MD 20746 USA

ISBN: (纸本)081945480X

The AVHRR solar reflectance channels need on-orbit calibration that can only be done vicariously. For over a decade, NOAA/NESDIS has paid particular attention to the vicarious calibration based on the Libyan Desert. A previous algorithm was remarkably precise ( < 2%) in predicting the long term instrument degradation, but because it omitted the seasonal variation caused by the bidirectional reflectance distribution function of the target, the post-launch calibration was much less precise ( similar to 5%). Careful selection of more uniform target and better detection of contaminated measurements (by clouds, dust storm, and wet surface after rain) further reduced noises in the data used to monitor instrument degradation. Together, these improvements reduced latency of post-launch calibration from 3-4 years to 18 months, with enhanced statistical confidence.

关键词： Calibration Reflectivity Bidirectional reflectance transmission function Clouds Radiometry Satellites Target detection detection and tracking algorithms Climatology Environmental sensing

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Authentication-invariant cancellable biometric filters for illumination-tolerant face verification

Authentication-invariant cancellable biometric filters for i...

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Conference on Biometric Technology for Human Identification

作者： Savvides, M Vijayakumar, BVK Khosla, PK Carnegie Mellon Univ Dept Elect & Comp Engn CyberSecur Lab Pittsburgh PA 15213 USA

ISBN: (纸本)0819453277

In this paper we address the issue of producing cancelable biometric templates;a necessary feature in the deployment of any biometric authentication system. We propose a novel scheme that encrypts the training images used to synthesize the single (minimum average correlation energy) filter for biometric authentication. We show theoretically that convolving the training images with any random convolution kernel prior to building the filter does not change the resulting correlation output peak-to-sidelobe ratios, thus preserving the authentication performance. However, different templates can be obtained from the same biometric by varying the convolution kernels thus enabling the cancelability of the templates. We evaluate the proposed method using the illumination subset of the CMU pose, illumination, expressions (PIE) face dataset and show that we are still able to achieve 100% face verification using the proposed encryption scheme. Our proposed method is interesting from a pattern recognition theory point of view, as we are able to 'encrypt' the data and perform recognition in the encrypted domain that performs as well as the unencrypted case, for a variety of encryption kernels;we show analytically that the recognition performance remains invariant to the proposed encryption scheme, while retaining the desired shift-invariance property of correlation filters.

关键词： Image filtering detection and tracking algorithms Biometrics Convolution Point spread functions Light sources and illumination Fourier transforms Image encryption Facial recognition systems Optical filters

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Simulation of point-like optical flashes in the sky

Simulation of point-like optical flashes in the sky

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12th IEEE-SPIE Symposium on Photonics and Web Engineering

作者： Piotrowski, LW Sokolowski, M Inst Phys Expt Warsaw Poland

ISBN: (纸本)081945415X

We present optimized performance of algorithms developed for detection of point like, visible light bursts in the sky. The algorithms based on analysis of series of consequtive images and detecting local differences between them were tested on simulated data obtained by inserting images of stars of different magnitudes at random positions. We discuss the choice of parameters which results in the maximal detection efficiency and simultaneously keeps the number of false detections as low as possible.

关键词： Stars detection and tracking algorithms Algorithm development Computer simulations Object recognition Optical simulations Atmospheric optics Electronics Satellites Shape analysis

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The relationship between shape under similarity transformations and shape under affine transformations

The relationship between shape under similarity transformati...

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7th Conference on Mathematics of Data/Image Coding, Compression, and Encryption

作者： Stiller, PF Texas A&M Univ College Stn TX 77843 USA

ISBN: (纸本)0819454990

Recent progress in shape theory, including the development of object/image equations for shape matching and shape space metrics (especially object/image metrics), is now being exploited to develop new algorithms for target recognition. This theory makes use of advanced mathematical techniques from algebraic and differential geometry to construct generalized shape spaces for various projection and sensor models, and then uses that construction to find natural metrics that express the distance (difference) between two configurations of object features, two configurations of image features, or an object and an image pair. Such metrics produce the most robust tests for target identification;at least as far as target geometry is concerned. Moreover, they also provide the basis for efficient hashing schemes to do target identification quickly and provide a rigorous foundation for error analysis in ATR.

关键词： Target recognition Algorithm development Image sensors algorithms detection and tracking algorithms Matrices Sensors Error analysis Mathematical modeling Mathematics

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Performance evaluation of road detection and following systems

Performance evaluation of road detection and following syste...

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Conference on Mobile Robots XVII

作者： Hong, T Takeuchi, A Foedisch, M Shneier, M Natl Inst Stand & Technol Gaithersburg MD 20899 USA

ISBN: (纸本)0819455628

We describe a methodology for evaluating algorithms to provide quantitative information about how well road detection and road following algorithms perform. The approach relies on generating a set of standard data sets annotated with ground truth. We evaluate the algorithms used to detect roads by comparing the output of the algorithms with ground truth, which we obtain by having humans annotate the data sets used to test the algorithms. Ground truth annotations are acquired from more than one person to reduce systematic errors. Results are quantified by looking at false positive and false negative regions of the image sequences when compared with the ground truth. We describe the evaluation of a number of variants of a road detection system based on neural networks.

关键词： Roads detection and tracking algorithms Algorithm development Image segmentation Video Neural networks Visualization Databases Evolutionary algorithms Pattern recognition

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