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Comparisons have been made showing that modeled multi and hyperspectral imagery can approach the complexity of real data and the use of modeled data to perform algorithm testing and sensor modeling is well established. With growing interest in the acquisition and exploitation of polarimetric imagery, there is a need to perform similar comparisons for this imaging modality. This paper will describe the efforts to reproduce polarimetric imagery acquired of a real world scene in a synthetic image generation environment. Real data was collected with the Wildfire Airborne Sensor ProgramLite (WASP-Lite) imaging system using three separate cameras to acquire simultaneously three polarization orientations. Modeled data were created using the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model. This model utilizes existing tools such as polarized bi-directional reflectance distribution functions (pBRDF), polarized atmospheric models, and polarization-sensitive sensor models to recreate polarized imagery. Results will show comparisons between the real and synthetic imagery, highlighting successes in the model as well as areas where improved fidelity is required.

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