Mr. Shawn D. Higbee Profile

Shawn D. Higbee

at Rochester Institute of Technology

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Author

Publications (4)

Proceedings Article | 8 May 2018 Presentation + Paper

Simulation techniques for image utility analysis

Sanghui Han, John Kerekes , Shawn Higbee, Lawrence Siegel

Proceedings Volume 10644, 106440P (2018) https://doi.org/10.1117/12.2305163

KEYWORDS: Imaging systems, Sensors, Image analysis, Image processing, Image quality, Point spread functions, Digital imaging

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Modeling a space borne imaging system is key in predicting mission utility and exploring the sensor design trade space. It is important to capture critical real world phenomena in the modeling as accurately as possible to optimize design parameters. As a step toward optimal design of spectral imaging systems, this work presents simulation techniques that were used to model a panchromatic imaging system and predict well-known image quality metrics for a range of values of a key optical design variable - the effective focal length (EFL).We designed a at desert scene that included 7% and 15% reflectance panels and generated simulated images for a range of EFLs. The panels were used to calculate a sensor signal-to-noise ratio (SNR). The simulation incorporated a summer atmosphere with a collection time and geometry set to produce zenith solar and nadir collection angles. Platform motion and height with a given integration time for known detector parameters were also incorporated to produce images with changing EFL. A point spread function (PSF) of a typical optical system was incorporated that was scaled according to the EFL for a constant aperture diameter in order to capture the optical resolution changes. The PSF along with smear from the platform motion and integration time introduced realistic image blur to enable the relative edge response (RER) for the system to be estimated from the simulated images. The simulation used the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model that incorporates ray-tracing techniques and physics based radiation propagation modules. The SNR, RER, and GSD calculated from the synthetic images were used to estimate the National Imagery Interpretability Rating Scale (NIIRS) rating for a range of EFLs. An optimum EFL was found by this process which included the compensating effects of resolution, sampling, and noise as the EFL changed. This technique is currently being expanded to assess trades for sensor design in order to optimize optical payload designs for multispectral and hyperspectral imaging systems.

Proceedings Article | 27 April 2009 Paper

A Bayesian approach to identification of gaseous effluents in passive LWIR imagery

Shawn Higbee, David Messinger, Yolande Tra, Joseph Voelkel, Lawrence Chilton

Proceedings Volume 7334, 73341T (2009) https://doi.org/10.1117/12.818704

KEYWORDS: Gases, Long wavelength infrared, Sensors, Data modeling, Absorption, Hyperspectral imaging, Atmospheric sensing, Lutetium, Chlorine, Atmospheric modeling

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Proceedings Article | 29 September 2006 Paper

Robust detection and spectrum estimation of multiple sources from rotating-prism spectrometer images

Ross Deming, Shawn Higbee, Derek Dwyer, Michael Welser, Leonid Perlovsky, Paul Pellegrini

Proceedings Volume 6365, 636502 (2006) https://doi.org/10.1117/12.689105

KEYWORDS: Data modeling, Prisms, Signal to noise ratio, Sensors, Spectroscopy, Staring arrays, Electro optical modeling, Imaging systems, Optimization (mathematics), Computed tomography

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Proceedings Article | 17 May 2006 Paper

Adaptive spectral imager for space-based sensing

Pajo Vujkovic-Cvijin, Neil Goldstein, Marsha Fox, Shawn Higbee, Latika Becker, Teng Ooi

Proceedings Volume 6206, 62060X (2006) https://doi.org/10.1117/12.669825

KEYWORDS: Imaging systems, Staring arrays, Spectroscopy, Spatial light modulators, Multispectral imaging, Data acquisition, Long wavelength infrared, Spectrographs, Sensors, Mirrors

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