Simulation techniques for image utility analysis

Abstract

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.