A comparison of edge-preserving approaches for differential interference contrast microscopy

In this paper we address the problem of estimating the phase from color images acquired with differential-interference-contrast microscopy. In particular, we consider the nonlinear and nonconvex optimization problem obtained by regularizing a least-squares-like discrepancy term with an edge-preserving functional, given by either the hypersurface potential or the total variation one. We investigate the analytical properties of the resulting objective functions, proving the existence of minimum points, and we propose effective optimization tools able to obtain in both the smooth and the nonsmooth case accurate reconstructions with a reduced computational demand

TV-regularized phase reconstruction in differential-interference-contrast (DIC) microscopy

In this paper we address the problem of reconstructing the phase from color images acquired with differential-interference-contrast (DIC) microscopy. In particular, we reformulate the problem as the minimization of a least-squares fidelity function regularized with of a total variation term, and we address the solution by exploiting a recently proposed inexact forward-backward approach. The effectiveness of this method is assessed on a realistic synthetic test