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Melnyk, O.

Convergence properties of ePIE and stochastic gradient methods for blind ptychography.

Anal. Appl., DOI: 10.1142/S0219530525500216 (2025)
Postprint DOI
Open Access Green
We consider blind ptychography, an imaging technique which aims to reconstruct an object of interest from a set of its diffraction patterns each obtained by a local illumination. As the distribution of the light within the illuminated region, called the window, is not known, it has to be estimated as well. For the recovery, a minimization of amplitude-base squared loss via gradient and stochastic gradient descent methods is considered. In particular, this includes extended Ptychographic Iterative Engine as a special case of stochastic gradient descent. We show that with a proper choice of step sizes, all methods converge to a critical point at a sublinear rate and discuss possibilities for larger step sizes.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Blind Ptychography ; Extended Ptychographic Iterative Engine ; Gradient Descent ; Stochastic Gradient Descent; Phase Retrieval Uniqueness; Diffraction; Microscopy; Algorithm; Recovery; Image
Sprache englisch
Veröffentlichungsjahr 2025
HGF-Berichtsjahr 2025
ISSN (print) / ISBN 0219-5305
e-ISSN 1793-6861
Zeitschrift Analysis and Applications
Verlag World Scientific Publishing
Verlagsort 5 Toh Tuck Link, Singapore 596224, Singapore
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Biological and Medical Imaging (IBMI)
POF Topic(s) 30205 - Bioengineering and Digital Health
Forschungsfeld(er) Enabling and Novel Technologies
PSP-Element(e) G-505595-001
Förderungen Helmholtz Association
DOI 10.1142/S0219530525500216
WOS ID 001472712700001
Scopus ID 105003477245
Erfassungsdatum 2025-05-09
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