Using automatic differentiation as a general framework for ptychographic reconstruction - Aix-Marseille Université Access content directly
Journal Articles Optics Express Year : 2019

Using automatic differentiation as a general framework for ptychographic reconstruction

Abstract

Coherent diffraction imaging methods enable imaging beyond lens-imposed resolution limits. In these methods, the object can be recovered by minimizing an error metric that quantifies the difference between diffraction patterns as observed, and those calculated from a present guess of the object. Efficient minimization methods require analytical calculation of the derivatives of the error metric, which is not always straightforward. This limits our ability to explore variations of basic imaging approaches. In this paper, we propose to substitute analytical derivative expressions with the automatic differentiation method, whereby we can achieve object reconstruction by specifying only the physics-based experimental forward model. We demonstrate the generality of the proposed method through straightforward object reconstruction for a variety of complex ptychographic experimental models.
Fichier principal
Vignette du fichier
oe-27-13-18653.pdf (4.09 Mo) Télécharger le fichier
Origin : Publisher files allowed on an open archive
Loading...

Dates and versions

hal-02163380 , version 1 (24-06-2019)

Licence

Attribution

Identifiers

Cite

Saugat Kandel, S. Maddali, Marc Allain, Stephan Hruszkewycz, Chris Jacobsen, et al.. Using automatic differentiation as a general framework for ptychographic reconstruction. Optics Express, 2019, 27 (13), pp.18653. ⟨10.1364/OE.27.018653⟩. ⟨hal-02163380⟩
69 View
140 Download

Altmetric

Share

Gmail Facebook X LinkedIn More