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Full-Text Articles in Physics
Fast And Effective Techniques For Lwir Radiative Transfer Modeling: A Dimension-Reduction Approach, Nicholas M. Westing [*], Brett J. Borghetti, Kevin C. Gross
Fast And Effective Techniques For Lwir Radiative Transfer Modeling: A Dimension-Reduction Approach, Nicholas M. Westing [*], Brett J. Borghetti, Kevin C. Gross
Faculty Publications
The increasing spatial and spectral resolution of hyperspectral imagers yields detailed spectroscopy measurements from both space-based and airborne platforms. These detailed measurements allow for material classification, with many recent advancements from the fields of machine learning and deep learning. In many scenarios, the hyperspectral image must first be corrected or compensated for atmospheric effects. Radiative Transfer (RT) computations can provide look up tables (LUTs) to support these corrections. This research investigates a dimension-reduction approach using machine learning methods to create an effective sensor-specific long-wave infrared (LWIR) RT model.
M2 Factor Of A Vector Schell-Model Beam, Milo W. Hyde Iv, Mark F. Spencer
M2 Factor Of A Vector Schell-Model Beam, Milo W. Hyde Iv, Mark F. Spencer
Faculty Publications
Extending existing scalar Schell-model source work, we derive the M2 factor for a general electromagnetic or vector Schell-model source to assess beam quality. In particular, we compute the M2 factors for two vector Schell-model sources found in the literature. We then describe how to synthesize vector Schell-model beams in terms of specified, desired M2 and present Monte Carlo simulation results to validate our analysis.