Dr. Jerrell R. Ballard Profile

Dr. Jerrell R. Ballard

Computer Scientist

SPIE Involvement:

Author

Publications (22)

Proceedings Article | 12 April 2021 Presentation + Paper

Modeling the radiative response of a high facet count rainforest for synthetic sensor imagery

Robert Hunter, Barry White, Reena Patel, Jerrell Ballard

Proceedings Volume 11727, 117270K (2021) https://doi.org/10.1117/12.2585983

KEYWORDS: Solar radiation models, Sensors, Image sensors, Ray tracing, Monte Carlo methods, Data modeling, Visualization, Solar radiation, Radiative transfer, Prototyping

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Proceedings Article | 24 April 2020 Presentation + Paper

Massively parallel synthetic sensor-based infrared image generation for object detection

Aaron Valoroso, Barry White, Jerrell Ballard, R. Harrison Hunter, Reena Patel

Proceedings Volume 11418, 114180A (2020) https://doi.org/10.1117/12.2558107

KEYWORDS: Sensors, Image sensors, Infrared sensors, Data modeling, Systems modeling, Telecommunications, Image processing, Process modeling, Infrared radiation, Image quality

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Proceedings Article | 22 April 2020 Presentation + Paper

A terabyte-scale geometry query engine for the generation of synthetic radiative transfer sensor imagery

Barry White, R. Harrison Hunter, Aaron Valoroso, Reena Patel, Jerrell Ballard

Proceedings Volume 11419, 1141902 (2020) https://doi.org/10.1117/12.2558210

KEYWORDS: Vegetation, Radiative transfer, Sensors, Data modeling, Ray tracing, Data storage, Image sensors, Parallel computing

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Proceedings Article | 17 October 2019 Paper

Exploitable synthetic sensor imagery from high-fidelity, physics-based target and background modeling

Stacy Howington, Jerrell Ballard, Nagaraju Kala, Andrew Trautz, Matthew Bray, Matthew Farthing, Amanda Hines

Proceedings Volume 11158, 1115809 (2019) https://doi.org/10.1117/12.2532923

KEYWORDS: Soil science, Sensors, Image processing, Image sensors, Vegetation, Data modeling, Process modeling, Computer simulations

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It is well established that object recognition by human perception and by detection/identification algorithms is confounded by false alarms (e.g., [1]). These false alarms often are caused by static or transient features of the background. Machine learning can help discriminate between real targets and false alarms, but requires large and diverse image sets for training. The potential number of scenarios, environmental processes, material properties and states to be assessed is overwhelming and cannot practically be explored by field/lab collections alone. High-fidelity, physics-based simulation can now augment training sets with accurate synthetic sensor imagery, but at a high computational cost. To make synthetic image generation practical, it should include the fewest processes and coarsest spatiotemporal resolution needed to capture the system physics/state and accomplish the training.

Among the features known or expected to generate false alarms are: (1.) soil/material variability (spatial heterogeneity in density, mineral composition, reflectance), (2.) non-threat objects (rocks, trash), (3.) soil disturbance (physical and spectral effects), (4.) soil processes (moisture migration, evaporation), (5.) surface hydrology (rainfall runoff and surface ponding), (6.) vegetation processes (transpiration, rainfall interception and evaporation, non-saturating rain events, multi-layer canopy, (including thatch), discrete versus parameterized vegetation), and (7.) energy reflected or emitted by other scene components. This paper presents a suite of computational tools that will allow the community to begin to explore the relative importance of these features and determine when and how individual processes must be included explicitly or through simplifying assumptions/parameterizations. The justification for this decision to simplify is driven ultimately by the performance of a detection algorithm with the generated synthetic imagery. Knowing the required level of modeling detail is critical for designing test matrices for building image sets capable of training improved algorithms.

A related consideration in the creation of synthetic sensor imagery is validation of these complex, coupled modeling tools. Very few analytical solutions or laboratory experiments include enough complexity to thoroughly test model formulations. Conversely, field data collection cannot normally be characterized and measured with sufficient spatial and temporal detail to support true validation. Intermediate-scale physical exploration of near surface soil and atmospheric processes (e.g., Trautz et al., [2]) offers an alternative that is intermediary to the laboratory column and field scales. This allows many field-scale-dependent processes and effects to be reproduced, manipulated, isolated, and measured within a well characterized and controlled test environment at requisite spatiotemporal resolutions in both the air and soil.

Proceedings Article | 2 May 2017 Paper

Simulated transient thermal infrared emissions of forest canopies during rainfall events

Jerrell Ballard, William Hawkins, Stacy Howington, Raju Kala

Proceedings Volume 10206, 102060U (2017) https://doi.org/10.1117/12.2261874

KEYWORDS: Thermography, Infrared radiation, Solar radiation models, Monte Carlo methods, Wind energy, Solar energy, Shortwaves, Thermal modeling, Atmospheric modeling, 3D modeling

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Proceedings Article | 11 May 2012 Paper

Overview of computational testbed for evaluating electro-optical/infrared sensor systems

Raju Kala, Josh Fairley, Stephanie Price, Jerry Ballard, Alex Carrillo, Stacy Howington, Owen Eslinger, Amanda Hines, Ricky Goodson

Proceedings Volume 8357, 83570J (2012) https://doi.org/10.1117/12.922910

KEYWORDS: Sensors, Electro optical modeling, Atmospheric modeling, RGB color model, Data modeling, 3D modeling, Vegetation, Mid-IR, General packet radio service, Systems modeling

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Proceedings Article | 23 May 2011 Paper

High-resolution soil moisture mapping in Afghanistan

Jan M. Hendrickx, J. Bruce Harrison, Brian Borchers, Julie Kelley, Stacy Howington, Jerry Ballard

Proceedings Volume 8017, 801710 (2011) https://doi.org/10.1117/12.887255

KEYWORDS: Soil science, Landsat, Earth observing sensors, Satellite imaging, Satellites, Visualization, Spatial resolution, Land mines, Improvised explosive devices, Heat flux

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Proceedings Article | 4 May 2010 Paper

High-resolution soil moisture mapping using operational optical satellite imagery

Jan M. Hendrickx, Bruce Harrison, Brian Borchers, Graciela Rodríguez-Marín, Stacy Howington, Jerrell Ballard

Proceedings Volume 7664, 76641O (2010) https://doi.org/10.1117/12.856462

KEYWORDS: Soil science, Landsat, Earth observing sensors, Spatial resolution, Roads, Satellite imaging, Satellites, Vegetation, Improvised explosive devices, Thermal modeling

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Proceedings Article | 10 June 2005 Paper

High-resolution spatial measurements of minefield vegetation density and modeled surface heat flux

Jerrell Ballard

Proceedings Volume 5794, (2005) https://doi.org/10.1117/12.604276

KEYWORDS: Vegetation, Heat flux, Reflectivity, Soil science, LIDAR, Solar radiation, Solar radiation models, Thermal modeling, Infrared signatures, Data modeling

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Proceedings Article | 5 August 2004 Paper

High temporal and spatial thermal infrared characterization of dense grass during high-humidity conditions

Jerrell Ballard, Thomas Berry, David Leese, Stacy Anderson, Laura Bunch

Proceedings Volume 5431, (2004) https://doi.org/10.1117/12.541388

KEYWORDS: Thermography, Cameras, Solar radiation, Wind measurement, Humidity, Infrared signatures, Infrared radiation, Temperature metrology, Vegetation, Infrared cameras

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Proceedings Article | 5 August 2004 Paper

Toward a high-temporal-frequency grass canopy thermal IR model for background signatures

Jerrell Ballard, James Smith, George Koenig

Proceedings Volume 5431, (2004) https://doi.org/10.1117/12.541048

KEYWORDS: Thermography, Atmospheric modeling, Heat flux, Thermal modeling, Humidity, Data modeling, Infrared signatures, Infrared radiation, Temperature metrology, Wind measurement

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Proceedings Article | 12 September 2003 Paper

Basic development and testing of a short-range laser profiling model

Bruce Sabol, Jerrell Ballard

Proceedings Volume 5092, (2003) https://doi.org/10.1117/12.487355

KEYWORDS: Sensors, Target detection, Reflectivity, Profilometers, Optical simulations, Device simulation, Pulsed laser operation, Receivers, Data modeling, Computer simulations

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Proceedings Article | 5 September 2003 Paper

Methodology of real-time simulation to support field testing of dual-mode smart munitions sensors

Jerrell Ballard, Hollis Bennett, Bruce Sabol

Proceedings Volume 5075, (2003) https://doi.org/10.1117/12.487364

KEYWORDS: Sensors, Reflectivity, Infrared sensors, Computer simulations, Profilometers, Data modeling, Systems modeling, Roads, Thermography, Detection and tracking algorithms

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Proceedings Article | 2 August 2002 Paper

Hyperspectral canopy reflectance modeling and EO-1 Hyperion

Jerrell Ballard, James Smith

Proceedings Volume 4725, (2002) https://doi.org/10.1117/12.478786

KEYWORDS: 3D modeling, Reflectivity, Solar radiation models, Alternate lighting of surfaces, Atmospheric modeling, Data modeling, Spectroscopy, Photography, Atmospheric corrections, Sensors

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Proceedings Article | 28 January 2002 Paper

Directional satellite thermal IR measurements and modeling of a forest in winter and their relationship to air temperature

Lee Balick, Jerrell Ballard, James Smith, Stewart Goltz

Proceedings Volume 4542, (2002) https://doi.org/10.1117/12.454212

KEYWORDS: Temperature metrology, Satellites, Thermography, Data modeling, Thermal modeling, Sun, Sensors, 3D modeling, Infrared imaging, Remote sensing

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Proceedings Article | 19 September 2001 Paper

Integration of a V&V smart munition model into OneSAF testbed baseline for simulation and training

Jerrell Ballard

Proceedings Volume 4367, (2001) https://doi.org/10.1117/12.440052

KEYWORDS: Systems modeling, Computer simulations, Sensors, Target detection, Performance modeling, Target acquisition, Computing systems, Sensor performance, Environmental sensing, Infrared sensors

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SPIE Journal Paper | 1 August 2001

Thermal infrared hot spot and dependence on canopy geometry

James Smith, Jerrell Ballard

OE, Vol. 40, Issue 08, (August 2001) https://doi.org/10.1117/12.10.1117/1.1387990

KEYWORDS: Thermography, Infrared radiation, Reflectivity, Monte Carlo methods, Computer simulations, Atmospheric optics, Satellites, Remote sensing, Infrared sensors, Optical engineering

SPIE Journal Paper | 1 August 1999

Effect of spatial resolution on thermal and near-infrared sensing of canopies

James Smith, Jerrell Ballard

OE, Vol. 38, Issue 08, (August 1999) https://doi.org/10.1117/12.10.1117/1.602193

KEYWORDS: Spatial resolution, Reflectivity, Thermography, Sensors, Temperature metrology, 3D modeling, Thermal sensing, Near infrared, Vegetation, Anisotropy

Proceedings Article | 11 December 1998 Paper

Effect of spatial resolution on thermal IR sensing of plant canopies

James Smith, Jerrell Ballard, Lee Balick, James Getter

Proceedings Volume 3499, (1998) https://doi.org/10.1117/12.332747

KEYWORDS: Spatial resolution, 3D modeling, Reflectivity, Sensors, Agriculture, Thermal modeling, Thermography, Remote sensing, Vegetation, Soil science

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Proceedings Article | 7 July 1998 Paper

Sensor-based validation of synthetic thermal scenes: how close is good enough?

Jerrell Ballard, Bruce Sabol, R. Melton

Proceedings Volume 3375, (1998) https://doi.org/10.1117/12.327163

KEYWORDS: Sensors, Detection and tracking algorithms, Infrared sensors, Monte Carlo methods, Temperature metrology, Vegetation, Sensor performance, 3D modeling, Thermography, Data modeling

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Proceedings Article | 30 December 1997 Paper

Three-dimensional modeling of agricultural canopies for thermal IR exitance studies

James Smith, Jeffrey Pedelty, Jerrell Ballard, Thomas Schmugge

Proceedings Volume 3222, (1997) https://doi.org/10.1117/12.298184

KEYWORDS: 3D modeling, Thermography, Vegetation, Thermal modeling, Agriculture, Infrared radiation, Atmospheric modeling, Sensors, Resistance, Sun

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SPIE Journal Paper | 1 November 1997

Effect of three-dimensional canopy architecture on thermal infrared exitance

James Smith, Jerrell Ballard, Jeffrey Pedelty

OE, Vol. 36, Issue 11, (November 1997) https://doi.org/10.1117/12.10.1117/1.601527

KEYWORDS: 3D modeling, Vegetation, Thermography, Infrared radiation, Thermal modeling, Resistance, Sun, Sensors, Atmospheric modeling, Chemical elements

Showing 5 of 22 publications

Conference Committee Involvement (4)

Detection and Remediation Technologies for Mines and Minelike Targets XI

17 April 2006 | Orlando (Kissimmee), Florida, United States

Targets and Backgrounds XII: Characterization and Representation

17 April 2006 | Orlando (Kissimmee), Florida, United States

Targets and Backgrounds XI: Characterization and Representation

28 March 2005 | Orlando, Florida, United States

Targets and Backgrounds X: Characterization and Representation

12 April 2004 | Orlando, Florida, United States

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