Dr. Patrick D. O'Shea Profile

Dr. Patrick D. O'Shea

Electrical Engineer at US Army Redstone Technical Test Ctr

SPIE Involvement:

Author

Publications (12)

SPIE Journal Paper | 28 October 2020

Measuring the infrared intensity of a close-up resolved target with close-up blackbody references

Jeff Meier, Kenny N. M. Emmanuel, Zach Whitfield, Matthew Hester, Patrick O'Shea, Ronald Driggers, Carl Halford, Orges Furxhi

OE, Vol. 59, Issue 10, 103108, (October 2020) https://doi.org/10.1117/12.10.1117/1.OE.59.10.103108

KEYWORDS: Black bodies, Sensors, Calibration, Radiometry, Infrared radiation, Target detection, Nonuniformity corrections, Infrared sensors, Infrared search and track, Signal to noise ratio

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The intensity of objects in the infrared is an important quantity for a number of applications. Intensity in watts per steradian is the parameter that is used to describe either small targets or targets that are far away. Intensity is used because these cases are usually presented to a detection sensor where the object is smaller than the sensor detector angular subtense, a situation known as an “unresolved target.” In the military, unresolved targets can be rocket-propelled grenades, man-portable air defense threats, enemy aircraft at long range, or even ground vehicles that are being engaged by ground-to-ground or air-to-ground missiles. Typical “resolved target” metrics such as root-sum-squared differential temperature do not work well for unresolved targets. In addition, a given target intensity coupled with range, atmospheric transmission, and sensor noise equivalent irradiance can provide a quick signal-to-noise estimate of a particular sensor against a particular target. Target intensity can even be a measure of how visible ones platform is to other sensor and can be used to reduce platform signatures. Measurement of intensity is always a difficult procedure, where there is typically a sensor that does not encompass all aspects of measurement parameters. For example, there are very few radiometers that include high-resolution spatial measurements with high-resolution spectral measurements with high-resolution temporal measurements, not to mention polarization. For the few systems that exist that can provide a simultaneous measurement with most of these parameters, the cost is prohibitive. Usually, a spectral radiometer will provide high spectral resolution with no spatial information and a slow temporal rate. These measurements are common. In the case we describe here, the intensity measurement is taken broadband in the midwave or longwave infrared regions with good spatial resolution. This measurement provides a band integrated intensity measurement. We describe an approach for sensor calibration and object intensity measurement that can be used for broadband sensors applications.

Proceedings Article | 11 April 2008 Paper

The impact of spatio-temporal focal plane array nonuniformity noise on target search and identification performance

Richard Espinola, Patrick O'Shea, Jason Zeibel, Joseph Reynolds

Proceedings Volume 6941, 69410L (2008) https://doi.org/10.1117/12.785559

KEYWORDS: Staring arrays, Target detection, Sensors, Infrared imaging, Image processing, Infrared radiation, Target acquisition, Infrared sensors, Imaging systems, Long wavelength infrared

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SPIE Journal Paper | 1 January 2008

Effects of image compression on sensor performance

Patrick O'Shea, Eddie Jacobs, Richard Espinola

OE, Vol. 47, Issue 01, 013202, (January 2008) https://doi.org/10.1117/12.10.1117/1.2829770

KEYWORDS: Image compression, Modulation transfer functions, Sensors, JPEG2000, Performance modeling, Sensor performance, Image processing, Image sensors, Optical engineering, Wavelets

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Proceedings Article | 30 April 2007 Paper

IR system field performance with superresolution

Jonathan Fanning, Justin Miller, Jennifer Park, Gene Tener, Joseph Reynolds, Patrick O'Shea, Carl Halford, Ron Driggers

Proceedings Volume 6543, 65430Z (2007) https://doi.org/10.1117/12.720912

KEYWORDS: Sensors, Super resolution, Modulation transfer functions, Cameras, Image processing, NVThermIP, Staring arrays, Imaging systems, Performance modeling, Motion models

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Proceedings Article | 16 May 2006 Paper

Standard target sets for field sensor performance measurements

John O'Connor, Patrick O'Shea, John Palmer, Dawne Deaver

Proceedings Volume 6207, 62070U (2006) https://doi.org/10.1117/12.667002

KEYWORDS: Sensors, Performance modeling, Sensor performance, Electro optical modeling, Standards development, Calibration, Electro optical sensors, Gold, Data modeling, Visual process modeling

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Proceedings Article | 16 May 2006 Paper

Separation of presampling and postsampling modulation transfer functions in infrared sensor systems

Richard Espinola, Jeffrey Olson, Patrick O'Shea, Van Hodgkin, Eddie Jacobs

Proceedings Volume 6207, 62070P (2006) https://doi.org/10.1117/12.663903

KEYWORDS: Modulation transfer functions, Sensors, Infrared sensors, Performance modeling, Electro optical modeling, Visual process modeling, NVThermIP, Minimum resolvable temperature difference, Point spread functions, Imaging systems

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Proceedings Article | 15 May 2006 Paper

Effects of image compression on sensor performance

Patrick O'Shea, Eddie Jacobs

Proceedings Volume 6207, 62070B (2006) https://doi.org/10.1117/12.666620

KEYWORDS: Image compression, Sensors, Modulation transfer functions, JPEG2000, Performance modeling, Sensor performance, Image sensors, Image processing, Wavelets, Image quality

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Proceedings Article | 12 May 2005 Paper

Practical issues with 3D noise measurements and application to modern infrared sensors

Patrick O'Shea, Stephen Sousk

Proceedings Volume 5784, (2005) https://doi.org/10.1117/12.604588

KEYWORDS: Sensors, 3D metrology, Analog electronics, Calibration, Infrared sensors, Staring arrays, 3D modeling, Modulation transfer functions, Forward looking infrared, Infrared imaging

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Proceedings Article | 12 May 2005 Paper

Measurement of uncooled thermal imager noise

Stephen Sousk, Patrick O'Shea, Van Hodgkin

Proceedings Volume 5784, (2005) https://doi.org/10.1117/12.604595

KEYWORDS: Sensors, 3D metrology, Thermography, Nonuniformity corrections, Analog electronics, Cameras, Image sensors, 3D modeling, 3D acquisition, Infrared sensors

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Proceedings Article | 5 August 2004 Paper

Uncertainties in the minimum resolvable temperature difference measurement

Stephen Sousk, Patrick O'Shea, Van Hodgkin

Proceedings Volume 5407, (2004) https://doi.org/10.1117/12.541352

KEYWORDS: Sensors, Spatial frequencies, Minimum resolvable temperature difference, Imaging systems, Thermography, Visualization, Signal to noise ratio, Infrared imaging, Systems modeling, Mathematical modeling

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Proceedings Article | 22 August 2003 Paper

Minimum resolvable temperature difference measurements on undersampled imagers

Ronald Driggers, Van Hodgkin, Richard Vollmerhausen, Patrick O'Shea

Proceedings Volume 5076, (2003) https://doi.org/10.1117/12.487065

KEYWORDS: Imaging systems, Modulation transfer functions, Sensors, Minimum resolvable temperature difference, Performance modeling, Thermography, Staring arrays, Target acquisition, Phase shift keying, Image processing

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Proceedings Article | 22 August 2003 Paper

Comparison of emissive and reflective minimum resolvable temperature difference for measurements of sensor performance

Van Hodgkin, Ronald Driggers, Patrick O'Shea

Proceedings Volume 5076, (2003) https://doi.org/10.1117/12.487165

KEYWORDS: Sensors, Modulation transfer functions, Reflectivity, Infrared sensors, Sensor performance, Modulation, Spatial frequencies, Black bodies, Infrared imaging, Performance modeling

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The Minimum Resolvable Temperature Difference (MRT or MRTD) of an IR imaging sensor provides a measure of system performance in terms of sensitivity as a function of resolution. It's expressed as the temperature difference (ΔT) between a target and a background at which target features are just discernable as a function of spatial frequency. Traditionally, MRT has been measured in the laboratory by imaging a flat plate “blackbody” at slightly elevated and depressed temperatures through a sequence of 4-bar slot patterns (“targets”) in high Emissivity disks (“backgrounds”) at ambient temperature. In this traditional, purely emissive MRT approach, the luminance modulation in the images of the smaller targets ride upon luminance pedestals against the ambient background that make the image modulation hard to discern. Consequently, in the laboratory, sensor gain and offset adjustments sometimes must be performed in order to see the modulation on the smaller, i.e., higher spatial frequency, MRT targets. Quite frequently this part of the procedure does not correspond to how the sensor is operated in the field. An alternative approach, called reflective MRT, uses a disk in which the target region consists of slots and highly reflective, low Emissivity spaces and is surrounded by a high Emissivity background. Two flat plate “blackbodies” are used, one in transmission through the slots and one in reflection from the spaces between the slots. Both are at slightly different temperatures controlled and regulated above and below ambient. This results in target luminance modulation that does not ride upon ambient luminance pedestals, thus allowing MRT to be measured at the same sensor gain and offset for all target spatial frequencies. The intent of this approach is to improve the accuracy of laboratory MRT measurements as predictors of field performance. This paper describes this problem with emissive MRT, reflective MRT as a possible solution, and the experimental research planned for calendar year 2003 to compare emissive and reflective MRT measurements of well sampled imaging sensors.

Showing 5 of 12 publications

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