Practical spectral photography II: snapshot spectral imaging using linear retarders and microgrid polarization cameras

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 co-registration, 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 anisotropic polymer film retarders to create multivariate optical filters. We then describe the calibration procedure, which leverages neural networks to convert measured data into calibrated spectra (intensity versus wavelength). Experimental results are presented for a multivariate and channeled optical filter. Finally, imaging results taken using a red, green, and blue microgrid polarization camera and the channeled optical filter are presented. Imaging experiments indicated that the calculated spectra's root mean square error is highest in the region where the camera's red, green, and blue filter responses overlap. The average error of the spectral reflectance, measured of our spectralon tiles, was 6.5% for wavelengths spanning 425-675 nm. This technique demonstrates that 12 spectral channels can be obtained with a relatively simple and robust optical setup, and at minimal cost beyond the purchase of the camera. (C) 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement

Automated summary

This paper presents a generalized procedure for multispectral sensing using a pixelated polarization camera and anisotropic polymer film retarders to create multivariate optical filters. The calibration procedure is described, and experimental results demonstrate the feasibility of obtaining multiple spectral channels with a relatively simple and robust optical setup.