Channeled spectropolarimetry is a novel method of measuring the spectral and polarization content of light. It employs amplitude modulation to encode all four Stokes component spectra into a single optical power spectrum. We describe a practical approach to system calibration and object reconstruction, which is able to account for important non-ideal effects. These include dispersion in retarder materials and limited spectral resolution in the incorporated spectrometer. The spectropolarimeter is modeled as a linear operator, represented in practice by a matrix. The matrix is estimated in the calibration, and pseudoinverted subject to a constraint on object space for reconstructions. Experimental results are shown and compared with reference measurements. An example is given of the technique's application to the characterization of time-varying, stress-induced birefringence.
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Channeled spectropolarimetry enables real-time measurement of the polarimetric spectral information of the target. A crucial aspect of this technology is the accurate reconstruction of Stokes parameters spectra from the modulated spectra obtained through snapshot measurements. In this paper, a learnable sparse dictionary compressed sensing method is proposed for channeled spectropolarimeter (CSP) spectral reconstruction.
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