Dr. Patrick C. Hytla Profile

Dr. Patrick C. Hytla

Group Lead at Univ of Dayton Research Institute

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Publications (5)

SPIE Journal Paper | 17 May 2017

Multiratio fusion change detection with adaptive thresholding

Patrick Hytla, Eric Balster, Juan Vasquez, Robert Neuroth

JARS, Vol. 11, Issue 02, 025010, (May 2017) https://doi.org/10.1117/12.10.1117/1.JRS.11.025010

KEYWORDS: Magnetorheological finishing, Magnetic resonance imaging, Target detection, Image fusion

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Proceedings Article | 20 May 2015 Paper

Predicting exploitation success on compressed imagery through common image quality metrics: an initial look

Christopher McGuinness, Patrick Hytla, Kevin Priddy

Proceedings Volume 9464, 94640T (2015) https://doi.org/10.1117/12.2181940

KEYWORDS: Image compression, Image quality, Image processing, Distortion, JPEG2000, Detection and tracking algorithms, Computer programming, Data modeling, Video compression, Video

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Proceedings Article | 7 March 2014 Paper

Illumination invariant 3D change detection

Yakov Diskin, Vijayan Asari, Patrick Hytla, Juan Vasquez

Proceedings Volume 9024, 90240D (2014) https://doi.org/10.1117/12.2041038

KEYWORDS: 3D modeling, Cameras, Clouds, Reconstruction algorithms, Video, 3D image processing, Binary data, Image registration, Detection and tracking algorithms, Buildings

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SPIE Journal Paper | 1 September 2009

Anomaly detection in hyperspectral imagery: comparison of methods using diurnal and seasonal data

Patrick Hytla, Russell Hardie, Michael Eismann, Joseph Meola

JARS, Vol. 3, Issue 01, 033546, (September 2009) https://doi.org/10.1117/12.10.1117/1.3236689

KEYWORDS: Sensors, Target detection, Detection and tracking algorithms, Hyperspectral imaging, Contamination, Scanning electron microscopy, Expectation maximization algorithms, Statistical modeling, Image processing, Snow cover

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Proceedings Article | 7 May 2007 Paper

Anomaly detection in hyperspectral imagery: a comparison of methods using seasonal data

Patrick Hytla, Russell Hardie, Michael Eismann, Joseph Meola

Proceedings Volume 6565, 656506 (2007) https://doi.org/10.1117/12.718381

KEYWORDS: Sensors, Target detection, Hyperspectral imaging, Detection and tracking algorithms, Signal to noise ratio, Calibration, Statistical analysis, Staring arrays, Cameras, Spectral calibration

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