Dr. Dalton S. Rosario Profile

Dr. Dalton S. Rosario

Team Lead, Collection Enhancement & Visualization at U.S. Army Research Lab

SPIE Involvement:

Conference Program Committee | Journal Editorial Board Member | Author

Publications (30)

PROCEEDINGS ARTICLE | May 8, 2018

Spectral-elevation data registration using visible-SWIR spatial correspondence

Proc. SPIE. 10644, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIV

KEYWORDS: Image fusion, Short wave infrared radiation, Data modeling, Visualization, LIDAR, 3D modeling, Image registration, Orthophoto maps, 3D image processing, Data fusion

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SPIE Journal Paper | June 19, 2017

Deep greedy learning under thermal variability in full diurnal cycles

Rauss, Patrick , Rosario, Dalton

OE Vol. 56 Issue 08

KEYWORDS: Data modeling, Long wavelength infrared, Infrared radiation, Content addressable memory, Temperature metrology

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PROCEEDINGS ARTICLE | May 5, 2017

Characterizing the temporal and spatial variability of longwave infrared spectral images of targets and backgrounds

Proc. SPIE. 10198, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIII

KEYWORDS: Target detection, Long wavelength infrared, Infrared imaging, Detection and tracking algorithms, Sensors, Single mode fibers, Vegetation, Infrared radiation, Aluminum, Analytical research

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PROCEEDINGS ARTICLE | May 5, 2017

Deep learning over diurnal and other environmental effects

Proc. SPIE. 10198, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIII

KEYWORDS: Long wavelength infrared, Hyperspectral imaging, Infrared imaging, Roads, Data modeling, Sensors, Infrared radiation, Machine learning, Analytical research, Infrared signatures, Environmental sensing, Network architectures, Temperature metrology

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PROCEEDINGS ARTICLE | May 17, 2016

Solid target spectral variability in LWIR

Proc. SPIE. 9840, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXII

KEYWORDS: Target detection, Long wavelength infrared, Data modeling, Sensors, Calibration, Pattern recognition, Remote sensing, Solids, Black bodies, Spectral resolution

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PROCEEDINGS ARTICLE | September 1, 2015

Morphological operators for enhanced polarimetric image target detection

Proc. SPIE. 9613, Polarization Science and Remote Sensing VII

KEYWORDS: Target detection, Long wavelength infrared, Detection and tracking algorithms, Polarization, Sensors, Databases, Image processing, Polarimetry, Image filtering, Image enhancement

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PROCEEDINGS ARTICLE | May 21, 2015

Pattern recognition in hyperspectral persistent imaging

Proc. SPIE. 9472, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXI

KEYWORDS: Long wavelength infrared, Hyperspectral imaging, Sensors, Calibration, Pattern recognition, Clouds, Data acquisition, Black bodies, Spectral resolution, Atmospheric modeling

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PROCEEDINGS ARTICLE | June 13, 2014

First observations using SPICE hyperspectral dataset

Proc. SPIE. 9088, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XX

KEYWORDS: Long wavelength infrared, Sensors, Calibration, Remote sensing, Clouds, Data acquisition, Black bodies, Spectral resolution, Atmospheric sensing, Atmospheric modeling

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PROCEEDINGS ARTICLE | May 21, 2014

A covariance-based anomaly detector for polarimetric remote sensing applications

Proc. SPIE. 9099, Polarization: Measurement, Analysis, and Remote Sensing XI

KEYWORDS: Target detection, Long wavelength infrared, Principal component analysis, Statistical analysis, Detection and tracking algorithms, Polarization, Sensors, Remote sensing, Polarimetry, Palladium

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PROCEEDINGS ARTICLE | May 18, 2013

A multistage framework for dismount spectral verification in the VNIR

Proc. SPIE. 8743, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIX

KEYWORDS: Target detection, Hyperspectral imaging, Detection and tracking algorithms, Sensors, Skin, Reflectivity, Fourier transforms, Quantization, Hyperspectral target detection, RGB color model

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PROCEEDINGS ARTICLE | October 15, 2012

Range-invariant anomaly detection applied to imaging Fourier transform spectrometry data

Proc. SPIE. 8515, Imaging Spectrometry XVII

KEYWORDS: Detection and tracking algorithms, Sensors, Calibration, Image processing, Spectroscopy, Fourier transforms, Data processing, Black bodies, Niobium, Algorithm development

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PROCEEDINGS ARTICLE | May 15, 2012

VNIR data processing of small (human) targets

Proc. SPIE. 8393, Signal and Data Processing of Small Targets 2012

KEYWORDS: Target detection, Hyperspectral imaging, Human subjects, Detection and tracking algorithms, Sensors, Blood, Skin, Reflectivity, Fourier transforms, Algorithm development

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PROCEEDINGS ARTICLE | May 27, 2011

Smart compression using high-dimensional imagery

Proc. SPIE. 8063, Mobile Multimedia/Image Processing, Security, and Applications 2011

KEYWORDS: Target detection, Defense and security, Data compression, Image compression, Detection and tracking algorithms, Data modeling, Sensors, Image processing, Expectation maximization algorithms, Mahalanobis distance

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PROCEEDINGS ARTICLE | May 13, 2010

Hyperspectral object tracking using small sample size

Proc. SPIE. 7695, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVI

KEYWORDS: Target detection, Hyperspectral imaging, Statistical analysis, Detection and tracking algorithms, Sensors, Image processing, Video, Remote sensing, Kinematics, Feature extraction

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PROCEEDINGS ARTICLE | May 13, 2010

Spectral imagery collection experiment

Proc. SPIE. 7695, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVI

KEYWORDS: Hyperspectral imaging, Infrared imaging, Mid-IR, Sensors, Calibration, Databases, Polarimetry, Black bodies, Infrared radiation, Algorithm development

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PROCEEDINGS ARTICLE | May 4, 2010

Hyper-Cam automated calibration method for continuous hyperspectral imaging measurements

Proc. SPIE. 7687, Active and Passive Signatures

KEYWORDS: Staring arrays, Hyperspectral imaging, Infrared imaging, Mid-IR, Sensors, Calibration, Black bodies, Software development, Medium wave, Temperature metrology

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The midwave and longwave infrared regions of the electromagnetic spectrum contain rich information which can be captured by hyperspectral sensors thus enabling enhanced detection of targets of interest. A continuous hyperspectral imaging measurement capability operated 24/7 over varying seasons and weather conditions permits the evaluation of hyperspectral imaging for detection of different types of targets in real world environments. Such a measurement site was built at Picatinny Arsenal under the Spectral and Polarimetric Imagery Collection Experiment (SPICE), where two Hyper-Cam hyperspectral imagers are installed at the Precision Armament Laboratory (PAL) and are operated autonomously since Fall of 2009. The Hyper-Cam are currently collecting a complete hyperspectral database that contains the MWIR and LWIR hyperspectral measurements of several targets under day, night, sunny, cloudy, foggy, rainy and snowy conditions. The Telops Hyper-Cam sensor is an imaging spectrometer that enables the spatial and spectral analysis capabilities using a single sensor. It is based on the Fourier-transform technology yielding high spectral resolution and enabling high accuracy radiometric calibration. It provides datacubes of up to 320x256 pixels at spectral resolutions of up to 0.25 cm-1. The MWIR version covers the 3 to 5 μm spectral range and the LWIR version covers the 8 to 12 μm spectral range. This paper describes the automated operation of the two Hyper-Cam sensors being used in the SPICE data collection. The Reveal Automation Control Software (RACS) developed collaboratively between Telops, ARDEC, and ARL enables flexible operating parameters and autonomous calibration. Under the RACS software, the Hyper-Cam sensors can autonomously calibrate itself using their internal blackbody targets, and the calibration events are initiated by user defined time intervals and on internal beamsplitter temperature monitoring. The RACS software is the first software developed for COTS hyperspectal sensors that allows for full autonomous data collection capability for the user. The accuracy of the automatic calibration was characterized and is presented in this paper.

PROCEEDINGS ARTICLE | April 27, 2009

Hyperspectral anomaly detection using Sony PlayStation 3

Proc. SPIE. 7334, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XV

KEYWORDS: Target detection, Long wavelength infrared, Detection and tracking algorithms, Sensors, Image processing, Composites, Infrared radiation, Analytical research, Algorithm development, Parallel computing

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PROCEEDINGS ARTICLE | April 27, 2009

VNIR hyperspectral background characterization methods in adverse weather conditions

Proc. SPIE. 7334, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XV

KEYWORDS: Target detection, Hyperspectral imaging, Detection and tracking algorithms, Fiber optic gyroscopes, Sensors, Image processing, Palladium, Parallel computing, Hyperspectral target detection, Mahalanobis distance

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PROCEEDINGS ARTICLE | May 5, 2008

Statistical methods for analysis of hyperspectral anomaly detectors

Proc. SPIE. 6966, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIV

KEYWORDS: Statistical analysis, Detection and tracking algorithms, Data modeling, Sensors, Error analysis, Computer simulations, Image analysis, Sensor performance, Statistical methods, Statistical modeling

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PROCEEDINGS ARTICLE | April 14, 2008

Analysis of an autonomous clutter background characterization method for hyperspectral imagery

Proc. SPIE. 6966, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIV

KEYWORDS: Target detection, Long wavelength infrared, Hyperspectral imaging, Detection and tracking algorithms, Sensors, Image processing, Palladium, Parallel computing, Hyperspectral target detection, Algorithms

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PROCEEDINGS ARTICLE | May 7, 2007

Random sampling statistical analysis for adaptive target-scale-invariant hyperspectral anomaly detection

Proc. SPIE. 6565, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIII

KEYWORDS: Target detection, Hyperspectral imaging, Image fusion, Statistical analysis, Sensors, Image processing, Sensor performance, Parallel computing, Hyperspectral target detection, Process modeling

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PROCEEDINGS ARTICLE | April 26, 2007

Wide-area hyperspectral chemical plume detection using parallel random sampling

Proc. SPIE. 6554, Chemical and Biological Sensing VIII

KEYWORDS: Target detection, Long wavelength infrared, Image fusion, Statistical analysis, Detection and tracking algorithms, Sensors, Algorithm development, Parallel computing, Statistical modeling, Process modeling

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PROCEEDINGS ARTICLE | May 4, 2006

Principle of indirect comparison (PIC): simulation and analysis of PIC-based anomaly detection in multispectral data

Proc. SPIE. 6233, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XII

KEYWORDS: Target detection, Statistical analysis, Data modeling, Sensors, Image analysis, Photonic integrated circuits, Analytical research, Ferroelectric LCDs, Statistical modeling, Hyperspectral simulation

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PROCEEDINGS ARTICLE | June 1, 2005

The AsemiP anomaly detector: comparative performance in hyperspectral imagery

Proc. SPIE. 5806, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XI

KEYWORDS: Hyperspectral imaging, Lithium, Detection and tracking algorithms, Sensors, Surveillance, Sensor performance, Image sensors, Algorithm development

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PROCEEDINGS ARTICLE | September 21, 2004

A semiparametric approach using the discriminant metric SAM (spectral angle mapper)

Proc. SPIE. 5426, Automatic Target Recognition XIV

KEYWORDS: Target detection, Mathematical modeling, Hyperspectral imaging, Detection and tracking algorithms, Sensors, Data storage, Composites, Distortion, Image sensors, Probability theory

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PROCEEDINGS ARTICLE | September 16, 2003

Higher-order zero crossings for HSI ATD

Proc. SPIE. 5094, Automatic Target Recognition XIII

KEYWORDS: Target detection, Optical filters, Detection and tracking algorithms, Data modeling, Sensors, Frequency modulation, Fermium, Electronic filtering, Expectation maximization algorithms, Amplitude modulation

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PROCEEDINGS ARTICLE | July 25, 2002

Multivariate regression as a method for FLIR target detection

Proc. SPIE. 4726, Automatic Target Recognition XII

KEYWORDS: Target detection, Infrared detectors, Thermography, Infrared imaging, Detection and tracking algorithms, Sensors, Infrared radiation, Convolution, Automatic target recognition, Forward looking infrared

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PROCEEDINGS ARTICLE | August 27, 2001

Stochastic process modeling and Monte Carlo simulation: assisting higher-level decision making for aided target recognition networks

Proc. SPIE. 4382, Algorithms for Synthetic Aperture Radar Imagery VIII

KEYWORDS: Mathematical modeling, Digital signal processing, Statistical analysis, Surveillance, Monte Carlo methods, Target recognition, Automatic target recognition, Stochastic processes, Performance modeling, Systems modeling

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PROCEEDINGS ARTICLE | August 24, 2000

End-to end performance of the TESAR ATR system

Proc. SPIE. 4053, Algorithms for Synthetic Aperture Radar Imagery VII

KEYWORDS: Target detection, Radar, Unmanned aerial vehicles, Detection and tracking algorithms, Sensors, Synthetic aperture radar, Image processing, Automatic target recognition, Missiles, Binary data

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PROCEEDINGS ARTICLE | August 13, 1999

New automated terrain and feature extraction approach for the Predator UAV TESAR ATR system

Proc. SPIE. 3721, Algorithms for Synthetic Aperture Radar Imagery VI

KEYWORDS: Target detection, Radar, Unmanned aerial vehicles, Statistical analysis, Detection and tracking algorithms, Sensors, Synthetic aperture radar, Fourier transforms, Buildings, Automatic target recognition

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Showing 5 of 30 publications

Conference Committee Involvement (5)

Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imagery XXV

14 April 2019 | Baltimore, Maryland, United States

Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIV

16 April 2018 | Orlando, Florida, United States

Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIII

11 April 2017 | Anaheim, California, United States

Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXII

18 April 2016 | Baltimore, Maryland, United States

Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXI

21 April 2015 | Baltimore, Maryland, United States

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