Regularization of dielectric tensor tomography using total variation

TL;DR

This paper introduces a total variation regularization method for dielectric tensor tomography, improving 3D reconstructions by reducing artifacts and addressing the missing cone problem inherent in transmission measurements.

Contribution

The study generalizes total variation regularization to 3D tensor fields, specifically enhancing dielectric tensor tomography reconstructions.

Findings

Reduced halo artifacts in tensor reconstructions

Improved axial resolution in dielectric tomography

Mitigated missing cone problem effects

Abstract

Dielectric tensor tomography reconstructs the three-dimensional dielectric tensors of microscopic objects and provides information about the crystalline structure orientations and principal refractive indices. Because dielectric tensor tomography is based on transmission measurement, it suffers from the missing cone problem, which causes poor axial resolution, underestimation of the refractive index, and halo artifacts. In this study, we present the generalization of total variation regularization to three-dimensional tensor distributions. In particular, demonstrate the reduction of artifacts when applied to dielectric tensor tomography.