Compressive sensing for channeled polarimetry: Applications in spectropolarimetry and imaging polarimetry

摘要

This paper will present an overview of compressive sensing for channeled polarimetry. We frame the recon-struction of the Stokes parameters as an underdetermined problem, where we solve for 3N unknowns fromN measurements. We discuss two types of polarimeters: channeled spectropolarimeters and channeled linearimaging polarimeters. The polarimeters may differ in a few aspects: the output may be signals or images, theoptical elements may vary, and the dimensions may be spatial or spectral. Our algorithms work with existingpolarimeters and require no change in optical elements or measurement procedure. The purpose of this work is topresent this framework and describe how it applies across different types of polarimeters. Both simulations andexperiments show that our algorithms produce more accurate reconstructions with less artifacts than frequencydomain filtering.