Dr. Robin R. Burton Profile

Dr. Robin R. Burton

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Publications (4)

Proceedings Article | 8 June 2011 Paper

Quantitative data quality metrics for 3D laser radar systems

Jeffrey Stevens, Norman Lopez, Robin Burton

Proceedings Volume 8037, 80370J (2011) https://doi.org/10.1117/12.888832

KEYWORDS: Contrast transfer function, LIDAR, Imaging systems, Laser systems engineering, 3D acquisition, Data processing, Stereoscopy, Detection and tracking algorithms, Clouds, 3D image processing

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Proceedings Article | 4 May 2010 Paper

Product chain analysis of three-dimensional imaging laser radar systems employing Geiger-mode avalanche photodiodes

Norman Lopez, Robin Burton, Gary Kamerman, Brian Miles, Wayne Crouch

Proceedings Volume 7684, 76840A (2010) https://doi.org/10.1117/12.854702

KEYWORDS: LIDAR, Clouds, Sensors, Laser systems engineering, Imaging systems, Photons, Pulsed laser operation, Stereoscopy, Visualization, 3D image processing

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Proceedings Article | 4 May 2010 Paper

Foliage penetration obscuration probability density function analysis from overhead canopy photos for gimbaled linear-mode and Geiger-mode airborne lidar

Robin Burton

Proceedings Volume 7684, 76840E (2010) https://doi.org/10.1117/12.854704

KEYWORDS: LIDAR, Sensors, Photography, Cameras, Vegetation, Signal to noise ratio, Staring arrays, Binary data, Imaging systems, Target detection

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Three-dimensional (3D) Light Detection And Ranging (LIDAR) systems designed for foliage penetration can produce good bare-earth products in medium to medium-heavy obscuration environments, but product creation becomes increasingly more difficult as the obscuration level increases. A prior knowledge of the obscuration environment over large areas is hard to obtain. The competing factors of area coverage rate and product quality are difficult to balance. Ground-based estimates of obscuration levels are labor intensive and only capture a small portion of the area of interest. Estimates of obscuration levels derived from airborne data require that the area of interest has been collected previously. Recently, there has been a focus on lacunarity (scale dependent measure of translational invariance) to quantify the gap structure of canopies. While this approach is useful, it needs to be evaluated relative to the size of the instantaneous field-of-view (IFOV) of the system under consideration. In this paper, the author reports on initial results to generate not just average obscuration values from overhead canopy photographs, but to generate obscuration probability density functions (PDFs) for both gimbaled linear-mode and geiger-mode airborne LIDAR. In general, gimbaled linear-mode (LM) LIDAR collects data with higher signal-to-noise (SNR), but is limited to smaller areas and cannot collect at higher altitudes. Conversely, geiger-mode (GM) LIDAR has a much lower SNR, but is capable of higher area rates and collecting data at higher altitudes. To date, geiger-mode LIDAR obscurant penetration theory has relied on a single obscuration value, but recent work has extended it to use PDFs1. Whether or not the inclusion of PDFs significantly changes predicted results and more closely matches actual results awaits the generation of PDFs over specific ground truth targets and comparison to actual collections of those ground truth targets. Ideally, examination of individual PDFs for specific collections will provide insight into how collection operations can be optimized in general and whether or not a generation of representative PDFs of various forest types will be useful for collection planning.

Proceedings Article | 8 November 2002 Paper

Elastic ladar modeling for synthetic imaging applications

Robin Burton, John Schott, Scott Brown

Proceedings Volume 4816, (2002) https://doi.org/10.1117/12.451630

KEYWORDS: Atmospheric modeling, Systems modeling, LIDAR, Speckle, Beam propagation method, Atmospheric propagation, Receivers, Sensors, Laser scattering, Scattering

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The Digital Imaging and Remote Sensing Image Generation (DIRSIG) model is a synthetic imagery generation model developed at the Center for Imaging Science (CIS) at the Rochester Institute of Technology (RIT). It is a quantitative first principle based model that calculates the sensor reaching radiance from the visible through to the long wave infrared on a spectral basis. DIRSIG generates a very accurate representation of what a sensor would see by modeling all the processes involved in the imaging chain. Currently, DIRSIG only models passive sources such as the sun and blackbody radiation due to the temperature of an object. Active systems have the benefit of the user being able to control the illumination source and tailor it for specific applications. Remote sensing Laser Detection and Ranging (LADAR) systems that utilize a laser as the active source have been in existence for over 30 years. Recent advances in tunable lasers and infrared detectors have allowed much more sophisticated and accurate work to be done, but a comprehensive spectral LADAR model has yet to be developed. In order to provide a tool to assist in LADAR development, this research incorporates a first principle based elastic LADAR model into DIRSIG. It calculates the irradiance onto the focal plane on a spectral basis for both the atmospheric and topographic return, based on the system characteristics and the assumed atmosphere. The geometrical form factor, a measure of the overlap between the sensor and receiver field-of-view, is carefully accounted for in both the monostatic and bistatic cases. The model includes the effect of multiple bounces from topographical targets. Currently, only direct detection systems will be modeled. Several sources of noise are extensively modeled, such as speckle from rough surfaces. Additionally, atmospheric turbulence effects including scintillation, beam effects, and image effects are accounted for. To allow for future growth, the model and coding are modular and anticipate the inclusion of advanced sensor modules and inelastic scattering.

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