Revealing Structural Organization with Liquid Crystal-based Spectral Imaging Polarimetry

Abstract

Structural organization refers to the particular ordering of scatterers. Probing structural organization by imaging polarized spectral scatter provides insight into the composition of a medium, and can aid in remote sensing, the identification of tissue pathologies, and material characterization and differentiation. The vector nature of polarized light enables it to interact with optical anisotropies within a medium, while the spectral aspect of polarization is sensitive to small-scale structure. However, many polarization studies have limitations, as they provide qualitative image analysis, incomplete anisotropy information, or both. The ability to image the effects of anisotropy and small-scale structure at multiple wavelengths is key for parameterizing structural organization. The Stokes/Mueller formalism is a framework that quantifies a medium's complete spectral polarization response, and allows for the parameterization of structural organization. Additionally, advances in liquid crystal (LC) technology have resulted in new polarimetric devices. These computer-controlled devices impart spectral polarization effects on the millisecond timescale with no mechanically moving hardware, providing the ability for making rapid polarimetric measurements. This dissertation describes a methodology for revealing structural organization by exploiting the Stokes/Mueller formalism and by utilizing measurements from a spectral imaging polarimeter constructed from variable retardance LC devices, such as liquid crystal variable retarders (LCVRs) and a liquid crystal tunable filter (LCTF).The methodology includes developing the system, the Stokes/Mueller model, and all i of the procedures, calibrations, and data interpretation. Developing the system also consists of component and system calibration, a system sensitivity and performance analysis, and finally test measurements for system validation. The final validation measurement is made on a mineral sample for inferring structural organization.ii DedicationIn memory of my father, Jim Gladish.iii Acknowledgments