Dr. John Antoniades Profile

Dr. John Antoniades

Director/Remote Sensing Technology at BAE Systems

SPIE Involvement:

Author

Publications (22)

Proceedings Article | 27 April 2009 Paper

Fusion and normalization to enhance anomaly detection

R. Mayer, G. Atkinson, J. Antoniades, M. Baumback, D. Chester, J. Edwards, A. Goldstein, D. Haas, S. Henderson, L. Liu

Proceedings Volume 7334, 73340N (2009) https://doi.org/10.1117/12.819921

KEYWORDS: Transform theory, Image fusion, Target detection, Simulation of CCA and DLA aggregates, Sensors, Near infrared, Hyperspectral imaging, Vegetation, Cesium, Hyperspectral target detection

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Proceedings Article | 3 April 2008 Paper

Autonomous real-time ground ubiquitous surveillance-imaging system (ARGUS-IS)

Brian Leininger, Jonathan Edwards, John Antoniades, David Chester, Dan Haas, Eric Liu, Mark Stevens, Charlie Gershfield, Mike Braun, James Targove, Steve Wein, Paul Brewer, Donald Madden, Khurram Hassan Shafique

Proceedings Volume 6981, 69810H (2008) https://doi.org/10.1117/12.784724

KEYWORDS: Video, Sensors, Image processing, Field programmable gate arrays, Video surveillance, Imaging systems, Surveillance, Cameras, Staring arrays, Video processing

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Proceedings Article | 26 September 2007 Paper

Shadowed object detection for hyperspectral imagery

R. Mayer, J. Antoniades, M. Baumback, D. Chester, J. Edwards, A. Goldstein, D. Haas, S. Henderson

Proceedings Volume 6678, 66780L (2007) https://doi.org/10.1117/12.738408

KEYWORDS: Target detection, Buildings, Detection and tracking algorithms, Matrices, Hyperspectral imaging, Infrared signatures, Hyperspectral target detection, Curium, Infrared imaging, Image analysis

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Objects shielded from direct illumination, or lying in shadows, can be difficult to detect using airborne hyperspectral sensors. Diminished illumination of objects reduces the signal contrast with respect to the background and shade shifts the spectral signature distribution. Supervised detection of shadowed objects is therefore confounded from implementing the simplest approach, namely inserting signatures trained on fully illuminated objects into target searches. Previously developed statistical temporal transformation ("whitening/dewhitening") of target signatures and target covariance matrices has been adapted to convert fully illuminated signatures to the more appropriate shadowed signatures for target detection. The choice of areas to transform the signatures must include dimilar background composition under full illumination and shadow conditions. A new search algorithm, Regularized Maximum Likelihood Clustering (RMLC), uses pixels for the CV computation associated with the object. "Regularizing" the object's covariance matrix avoids non-singularities from the CV computation and mitigates statistical degradation for the covariance matrix calculation due to undersampling of the small number of pixels. To accurately compute the required covariance matrices from imagery of small open and shadowed areas, "regularization" is also applied to the covariance matrices associated with those areas. The searches are applied to visible/near IR data collected from forested areas. Inserting the transformed signatures into RMLC and the adaptive cosine estimator (ACE) achieved higher target detection for fixed alarm rate, relative to the matched filter. The temporal transform of the signatures was compared to a scaling approach using mean signatures from the open and shadowed areas. This study successfully extracted targets from shadows by using a sensitive target search and through transforming signatures collected from fully illuminated conditions into shadowed spectra.

SPIE Journal Paper | 1 August 2007

Extending classification approaches to hyperspectral object detection

Rulon Mayer, John Antoniades, Mark Baumback, David Chester, Jonathan Edwards, Alon Goldstein, Daniel Haas, Samuel Henderson

JARS, Vol. 1, Issue 01, 013526, (August 2007) https://doi.org/10.1117/12.10.1117/1.2776954

KEYWORDS: Target detection, Detection and tracking algorithms, Hyperspectral imaging, Short wave infrared radiation, Image classification, Mahalanobis distance, Infrared signatures, Hyperspectral target detection, Matrices, Optical filters

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Proceedings Article | 1 September 2006 Paper

Robustness tests for object identification algorithms in hyperspectral imagery

R. Mayer, J. Antoniades, M. Baumback, D. Chester, J. Edwards, A. Goldstein, D. Haas, S. Henderson

Proceedings Volume 6302, 63020Y (2006) https://doi.org/10.1117/12.683219

KEYWORDS: Target detection, Detection and tracking algorithms, Matrices, Transform theory, Hyperspectral imaging, Roads, Algorithm development, Sensors, Curium, Image classification

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Proceedings Article | 4 May 2006 Paper

A classification approach and comparison to other object identification algorithms for hyperspectral imagery

R. Mayer, J. Antoniades, M. Baumback, D. Chester, J. Edwards, A. Goldstein, D. Haas, S. Henderson

Proceedings Volume 6233, 623306 (2006) https://doi.org/10.1117/12.663945

KEYWORDS: Target detection, Curium, Matrices, Image classification, Detection and tracking algorithms, Hyperspectral imaging, Mahalanobis distance, Sensors, Algorithm development, Roads

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Proceedings Article | 27 October 1999 Paper

New results from the ORASIS/NEMO compression algorithm

Jeffrey Bowles, Dean Clamons, David Gillis, Peter Palmadesso, John Antoniades, Mark Baumback, Mark Daniel, John Grossmann, Daniel Haas, Jeffrey Skibo

Proceedings Volume 3753, (1999) https://doi.org/10.1117/12.366284

KEYWORDS: Sensors, Interference (communication), Spectroscopy, Satellites, Data compression, Reconstruction algorithms, Image processing, Image compression, Short wave infrared radiation

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Proceedings Article | 27 October 1999 Paper

Calibration, characterization, and first results with the Ocean PHILLS hyperspectral imager

Curtiss Davis, Mary Kappus, Jeffrey Bowles, John Fisher, John Antoniades, Megan Carney

Proceedings Volume 3753, (1999) https://doi.org/10.1117/12.366279

KEYWORDS: Calibration, Spectrographs, Cameras, Imaging systems, Hyperspectral imaging, Distortion, Sensors, Water, Spectral calibration, Remote sensing

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Proceedings Article | 18 November 1998 Paper

On-board hyperspectral compression and analysis system for the NEMO satellite

Jeffrey Bowles, John Antoniades, Jeffrey Skibo, Mark Daniel, Daniel Haas, John Grossmann, Mark Baumback

Proceedings Volume 3437, (1998) https://doi.org/10.1117/12.331330

KEYWORDS: Data processing, Satellites, Data compression, Spectrographs, Short wave infrared radiation, Sensors, Hyperspectral imaging, Space operations, Signal to noise ratio, Signal processing

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Proceedings Article | 16 October 1998 Paper

Comparison of low-cost hyperspectral sensors

John Fisher, Mark Baumback, Jeffrey Bowles, John Grossmann, John Antoniades

Proceedings Volume 3438, (1998) https://doi.org/10.1117/12.328112

KEYWORDS: Spectrographs, Sensors, Distortion, Holography, Diffraction gratings, Image quality, Mirrors, Monochromatic aberrations, Cameras, Reflectivity

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Proceedings Article | 16 October 1998 Paper

Comparison of output from ORASIS and pixel purity calculations

Jeffrey Bowles, Mark Daniel, John Grossmann, John Antoniades, Mark Baumback, Peter Palmadesso

Proceedings Volume 3438, (1998) https://doi.org/10.1117/12.328097

KEYWORDS: Visualization, Acquisition tracking and pointing, Mathematical modeling, Hyperspectral imaging, Sensors, Diamond, Analytical research, Quantization, Algorithm development, Transform theory

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Proceedings Article | 21 September 1998 Paper

Hyperspectral imaging sensor for the coastal environment

John Fisher, John Antoniades, Chris Rollins, LianQin Xiang

Proceedings Volume 3482, (1998) https://doi.org/10.1117/12.322003

KEYWORDS: Spectrographs, Telescopes, Space telescopes, Mirrors, Short wave infrared radiation, Distortion, Sensors, Holography, Diffraction gratings, Monochromatic aberrations

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Proceedings Article | 2 July 1998 Paper

Evaluation of endmember selection techniques and performance results from ORASIS hyperspectral analysis

Kwok Tsang, John Grossmann, Peter Palmadesso, John Antoniades, Mark Baumback, Jeffrey Bowles, Mark Daniel, John Fisher, Daniel Haas

Proceedings Volume 3372, (1998) https://doi.org/10.1117/12.312607

KEYWORDS: Target detection, Algorithm development, Detection and tracking algorithms, Transparency, Photons, Analytical research, Physics, Adaptive optics, System identification, Optical testing

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Proceedings Article | 2 July 1998 Paper

Hyperspectral analysis and target detection system for the Adaptive Spectral Reconnaissance Program (ASRP)

John Grossmann, Jeffrey Bowles, Daniel Haas, John Antoniades, Mitchell Grunes, Peter Palmadesso, David Gillis, Kwok Tsang, Mark Baumback, Mark Daniel, John Fisher, Ioana Triandaf

Proceedings Volume 3372, (1998) https://doi.org/10.1117/12.312591

KEYWORDS: Target detection, Detection and tracking algorithms, Automatic target recognition, Analytical research, Hyperspectral imaging, Scanners, Hyperspectral target detection, Spatial filters, Reconnaissance systems, Reconnaissance

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Proceedings Article | 31 October 1997 Paper

Real-time analysis of hyperspectral data sets using NRL's ORASIS algorithm

Jeffrey Bowles, John Antoniades, Mark Baumback, John Grossmann, Daniel Haas, Peter Palmadesso, John Stracka

Proceedings Volume 3118, (1997) https://doi.org/10.1117/12.283841

KEYWORDS: Digital signal processing, Imaging systems, Cameras, Hyperspectral imaging, Spectroscopy, Unmanned aerial vehicles, Sensors, Target detection, Signal processing, Infrared cameras

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Proceedings Article | 29 October 1997 Paper

Generalized linear feature detection of weak targets in spectrally mixed clutter

Xiaoli Yu, Lawrence Hoff, Scott Beaven, Edwin Winter, John Antoniades, Irving Reed

Proceedings Volume 3163, (1997) https://doi.org/10.1117/12.283957

KEYWORDS: Target detection, Sensors, Algorithm development, Detection and tracking algorithms, Buildings, Signal to noise ratio, Data fusion, Infrared imaging, Infrared radiation, Silicon

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Proceedings Article | 6 November 1996 Paper

Effect of spectral resolution and number of wavelength bands in analysis of a hyperspectral data set using NRL's ORASIS algorithm

Jeffrey Bowles, Peter Palmadesso, John Antoniades, Mark Baumback, John Grossmann, David Haas

Proceedings Volume 2821, (1996) https://doi.org/10.1117/12.257166

KEYWORDS: Sensors, Spectral resolution, Minerals, RGB color model, Composites, Cobalt, Hyperspectral imaging, Imaging systems, Cameras, Spatial resolution

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Proceedings Article | 29 September 1995 Paper

Hyperspectral imaging results from the NRL PHILLS instrument

Mark Baumback, John Antoniades, Jeffrey Bowles, Peter Palmadesso, Lee Rickard

Proceedings Volume 2553, (1995) https://doi.org/10.1117/12.221351

KEYWORDS: Optical filters, Hyperspectral imaging, Spectrometers, Spectral data processing, Imaging systems, Spatial resolution, Low light imagers, Imaging spectroscopy, Spectroscopes, Image processing

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Proceedings Article | 29 September 1995 Paper

Use of filter vectors in hyperspectral data analysis

Jeffrey Bowles, Peter Palmadesso, John Antoniades, Mark Baumback, Lee Rickard

Proceedings Volume 2553, (1995) https://doi.org/10.1117/12.221352

KEYWORDS: Algorithm development, Hyperspectral imaging, Image filtering, Data analysis, Detection and tracking algorithms, Optical filters, Composites, Linear filtering, Electronic filtering, Remote sensing

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Proceedings Article | 29 September 1995 Paper

PHILLS: NRL's modular hyperspectral imaging system

John Antoniades, David Haas, Mark Baumback, Peter Palmadesso, John Stracka, Jeffrey Bowles, Lee Rickard

Proceedings Volume 2553, (1995) https://doi.org/10.1117/12.221350

KEYWORDS: Imaging systems, Hyperspectral imaging, Sensors, Optical filters, Analog electronics, Computing systems, Control systems, Cameras, Data analysis, Video

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Proceedings Article | 12 June 1995 Paper

Hyperspectral imaging using rotational spectrotomography

Paul Bernhardt, John Antoniades

Proceedings Volume 2480, (1995) https://doi.org/10.1117/12.210910

KEYWORDS: Imaging systems, Sensors, Photons, Fourier transforms, 3D image processing, Image filtering, Optical filters, Cameras, Dispersion, Spatial frequencies

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