Towards practical holographic coherent diffraction imaging via maximum likelihood estimation

David A. Barmherzig, Ju Sun

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


A new algorithmic framework is developed for holographic coherent diffraction imaging (HCDI) based on maximum likelihood estimation (MLE). This method provides superior image reconstruction results for various practical HCDI settings, such as when data is highly corrupted by Poisson shot noise and when low-frequency data is missing due to occlusion from a beamstop apparatus. This method is also highly robust in that it can be implemented using a variety of standard numerical optimization algorithms, and requires fewer constraints on the physical HCDI setup compared to current algorithms. The mathematical framework developed using MLE is also applicable beyond HCDI to any holographic imaging setup where data is corrupted by Poisson shot noise.

Original languageEnglish (US)
Pages (from-to)6886-6906
Number of pages21
JournalOptics Express
Issue number5
StatePublished - Feb 28 2022

Bibliographical note

Publisher Copyright:
© 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement

PubMed: MeSH publication types

  • Journal Article


Dive into the research topics of 'Towards practical holographic coherent diffraction imaging via maximum likelihood estimation'. Together they form a unique fingerprint.

Cite this