Snapshot spectral imaging using Solc-based multivariate optical filters and pixelated polarization cameras

Abstract

Despite recent advances, customized multispectral cameras can be challenging or costly to deploy in some use cases. Complexities span electronic synchronization, multi-camera calibration, parallax and spatial coregistration, and data acquisition from multiple cameras, all of which can hamper their ease of use. This paper discusses a generalized procedure for multispectral sensing using a pixelated polarization camera and Solc stages to create multivariate optical filters. We then describe some preliminary experimental results of a fabricated filtered camera system. Finally, classification of the imagery is achieved using either shallow or deep neural networks. We also discuss the potential of using a color red, green, and blue microgrid polarization camera to detect upwards of 12 spectral channels using readily available standard off-the-shelf components.