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Ultramicroscopy, 2021-09, Vol.228, p.113343-113343, Article 113343
2021
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Autor(en) / Beteiligte
Titel
Quantitative reconstruction of the complex-valued object based on complementary phase modulations
Ist Teil von
  • Ultramicroscopy, 2021-09, Vol.228, p.113343-113343, Article 113343
Ort / Verlag
Elsevier B.V
Erscheinungsjahr
2021
Quelle
Alma/SFX Local Collection
Beschreibungen/Notizen
  • •Phase modulations are introduced to solve the phase retrieval problem using multi-dimensional spatial constraints;•It is easier to fabricate the phase plates (binary patterns) that implement the CPM in practical application;•A more accurate, robust, and faster reconstruction can be accomplished via the SCPM-based method; In the coherent diffraction imaging (CDI) techniques, a key point is to reconstruct the complex-valued object from the far-field intensity measurements, i.e., solving the phase retrieval problem. However, due to this ill-posed problem, traditional phase retrieval algorithms often encounter some problems associated with the iteration convergence. In this work, complementary phase modulations (CPM) are introduced to generate different far-field intensity measurements. The namely CPM-based method aims to find out the global optimal solution by imposing multi-dimensional constraints, including the diverse intensity images at the Fourier plane and the CPM at the object plane. It is proved by the numerical simulations and the optical experiments that the convergence speed and the recovery accuracy could be greatly improved. Furthermore, the shifting complementary phase modulations (SCPM)-based method is proposed by introducing more CPMs. The reconstruction performance is further improved even when the phase range is larger, and the support constraints are not required. In addition, the SCPM-based method is more robust to the Poisson noise. With the outstanding reconstruction performance, the CPM-based methods may be helpful to phase imaging in the application of visible-light microscopy and X-ray imaging.
Sprache
Englisch
Identifikatoren
ISSN: 0304-3991
eISSN: 1879-2723
DOI: 10.1016/j.ultramic.2021.113343
Titel-ID: cdi_proquest_miscellaneous_2548399706

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