Background Denoising for Ptychography via Wigner Distribution Deconvolution

TL;DR

This paper introduces a novel Wigner Distribution Deconvolution method for background noise removal in ptychography, enabling accurate phase retrieval even with additive background noise affecting measurements.

Contribution

It proposes a new algorithm based on lifting the problem into a higher-dimensional space to effectively handle background noise in ptychographic phase retrieval.

Findings

The method successfully reconstructs objects despite background noise.

Uniqueness of reconstruction is established for phase objects.

The approach discards affected equations and uses redundancy for recovery.

Abstract

Ptychography is a computational imaging technique that aims to reconstruct the object of interest from a set of diffraction patterns. Each of these is obtained by a localized illumination of the object, which is shifted after each illumination to cover its whole domain. As in the resulting measurements the phase information is lost, ptychography gives rise to solving a phase retrieval problem. In this work, we consider ptychographic measurements corrupted with background noise, a type of additive noise that is independent of the shift, i.e., it is the same for all diffraction patterns. Two algorithms are provided, for arbitrary objects and for so-called phase objects that do not absorb the light but only scatter it. For the second type, a uniqueness of reconstruction is established for almost every object. Our approach is based on the Wigner Distribution Deconvolution, which lifts the object to a higher-dimensional matrix space where the recovery can be reformulated as a linear problem. Background noise only affects a few equations of the linear system that are therefore discarded. The lost information is then restored using redundancy in the higher-dimensional space. Keywords: phase retrieval, ptychography, background noise, Wigner Distribution Deconvolution, uniqueness of reconstruction.