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Dive into the research topics where Christopher M. Stellman is active.

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Featured researches published by Christopher M. Stellman.


Optical Engineering | 2000

Real-time hyperspectral detection and cuing

Christopher M. Stellman; Geoffrey G. Hazel; Frank Bucholtz; Joseph V. Michalowicz; Alan D. Stocker; William Schaaf

The Dark HORSE 1 (Hyperspectral Overhead Reconnais- sance and Surveillance Experiment 1) flight test has demonstrated au- tonomous, real-time visible hyperspectral detection of military ground tar- gets with real-time cuing of a high-resolution framing camera. An overview of the Dark HORSE 1 hyperspectral sensor system is pre- sented. The system hardware components are described in detail, with an emphasis on the visible hyperspectral sensor and the real-time pro- cessor. Descriptions of system software and processing methods are also provided. The recent field experiment in which the Dark HORSE 1 system was employed is described in detail along with an analysis of the collected data. The results evince per-pixel false-alarm rates on the or- der of 10 25 /km 2 , and demonstrate the improved performance obtained


Proceedings of SPIE | 2001

WAR HORSE (wide-area reconnaissance: hyperspectral overhead real-time surveillance experiment)

Christopher M. Stellman; Frederick M. Olchowski; Joseph V. Michalowicz

In recent years the Optical Sciences Division, Naval Research Laboratory (NRL) has been involved in the development of real-time hyperspectral detection, cueing, target location, and target designation capabilities. Under the Dark HORSE program it was demonstrated that a hyperspectral sensor could be used for the autonomous, real- time detection of airborne and military ground targets. This work has culminated in WAR HORSE, an autonomous real-time visible hyperspectral target detection system that has been configured for us on a Predator Unmanned Air Vehicle (UAV). The sensor system provides Predator with the ability to detect manmade objects in areas of natural background. The system consists of a visible hyperspectral imaging sensor, a real-time signal processor, a high-resolution visible line scan camera, an interface and control software application, and a data storage medium. The system is coupled to an on- board GPS/INS to provide target geo-location information and relevant data is transmitted to a ground station using line- of-sight down-link capabilities. The presented paper will provide an overview of the WAR HORSE sensor system hardware components and their integration aboard a Predator UAV. In addition, the results of a recently completed demonstration aboard the Predator UAV will be provided. This demonstration represents the first autonomous real-time hyperspectral target detection system to flown aboard a Predator UAV.


Sensors and Actuators B-chemical | 1998

Fiber-optic pipette (FOP) for rapid long pathlength capillary spectroscopy

Christopher M. Stellman; Frank Bucholtz; Kenneth J. Ewing

The fiber-optic pipette (FOP) couples a glass capillary, common syringe and a single optical fiber together to provide for a facile means of achieving long-pathlength capillary spectroscopy. The FOP acquires rapid spectroscopic measurements of small-volume liquid samples, while simultaneously achieving signal enhancements of the collected spectroscopic signal.


Sensors and Actuators B-chemical | 1998

Determination of BTEX contaminants in water via a long-pathlength fiber-optic Raman ‘dip-stick’

Christopher M. Stellman; Kenneth J. Ewing; Frank Bucholtz; Ishwar D. Aggarwal

Abstract A novel device is described for measuring benzene, toluene, ethylbenzene and xylenes (BTEX) in water. The instrument employs a long-pathlength fiber-optic Raman ‘dip-stick’ for rapid in-situ interrogation of liquid samples. The instrumental set-up, experimental conditions and fiber probe design are described in detail. Signal enhancements by factors of 100–150 over conventional Raman measurements have been achieved and limits of detection at the 95% confidence interval of 8–48 ppm for the BTEX analytes in water have been calculated. Signal response has been demonstrated to be linear over four orders of magnitude. Factors limiting detection limits have been identified and possible solutions are presented.


Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery IX | 2003

WAR HORSE and IRON HORSE at Camp Shelby: data collection and associated processing results

Christopher M. Stellman; Frederick M. Olchowski; Geoffrey G. Hazel; Eric Allman; M. L. Surratt

The following paper describes a recent data collection exercise in which the WAR HORSE visible-near-infrared hyperspectral imaging sensor and IRON HORSE short-wave-infrared hyperspectral imaging sensor were employed in the collection of wide-area hyperspectral data sets. A preliminary analysis of the data has been performed and results are discussed.


Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery IX | 2003

PHIRST light: a liquid crystal tunable filter hyperspectral sensor

Brian Stevenson; William B. Kendall; Christopher M. Stellman; Frederick M. Olchowski

PHIRST Light is a visible and near-infrared (VNIR) hyperspectral imaging sensor that has been assembled at the Naval Research Laboratory (NRL) using off-the-shelf components. It consists of a Dalsa 1M60 camera mated to a CRI VariSpec liquid crystal tunable filter (LCTF) and a conventional 75mm Pentax lens. This system can be thought of as the modern equivalent of a filter-wheel sensor. Historically, the problem with such sensors has been that images for different wavelengths are collected at different times. This causes spectral correlation problems when the camera is not perfectly still during the collection time for all bands (such as when it is deployed on an airborne platform). However, the PHIRST Light sensor is hard mounted in a Twin Otter aircraft, and is mated to a TrueTime event capture board, which records the precise GPS time of each image frame. Combining this information with the output of a CMIGITS INS/GPS unit permits precise coregistration of images from multiple wavelengths, and allows the formation of a conventional hyperspectral image cube. In this paper we present an overview of the sensor and its deployment, describe the processing steps required to produce coregistered hyperspectral cubes, and show detection results for targets viewed during the Aberdeen Collection Experiment (ACE).


Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery VIII | 2002

Sensor and algorithm performance of the WAR HORSE hyperspectral sensor during the 2001 Camp Navajo wide-area collect

Frederick M. Olchowski; Geoffrey G. Hazel; Christopher M. Stellman

The following paper describes a recent data collection exercise in which the WAR HORSE visible-near-infrared hyperspectral sensor was employed in the collection of wide- area hyperspectral data sets. Two anomaly detection algorithms, Subspace RX (SSRX) ans Gaussian Spectral Clustering (GSC), were used on the data and their performance is discussed.


Chemometrics and Intelligent Laboratory Systems | 1999

Optical regression: a method for improving quantitative precision of multivariate prediction with single channel spectrometers

Anna M.C. Prakash; Christopher M. Stellman; Karl S. Booksh


Archive | 1999

Dark HORSE 2 Quick-Look Report: Real-time Detection of Military Ground Targets Using an Infrared Hyperspectral Imaging Sensor

Christopher M. Stellman; Frank Bucholtz; Joseph V. Michalowicz


Archive | 1999

Spectral Calibration, Spatial Mapping and Flat Fielding Studies of the Dark HORSE 1 (DH1) March Data Collection

Christopher M. Stellman; Geoffrey G. Hazel; Jonathon M. Schuler; Frank Bucholtz; Joseph V. Michalowicz

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Frank Bucholtz

United States Naval Research Laboratory

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Frederick M. Olchowski

United States Naval Research Laboratory

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Joseph V. Michalowicz

United States Naval Research Laboratory

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Geoffrey G. Hazel

United States Naval Research Laboratory

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Kenneth J. Ewing

United States Naval Research Laboratory

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Eric Allman

United States Naval Research Laboratory

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Ishwar D. Aggarwal

United States Naval Research Laboratory

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Karl S. Booksh

Arizona State University

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M. L. Surratt

United States Naval Research Laboratory

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