Projection methods for high numerical aperture phase retrieval

Nguyen Hieu Thao*, Oleg Soloviev, Russell Luke, Michel Verhaegen

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

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We develop for the first time a mathematical framework in which the class of projection algorithms can be applied to high numerical aperture (NA) phase retrieval. Within this framework, we first analyze the basic steps of solving the high-NA phase retrieval problem by projection algorithms and establish the closed forms of all the relevant projection operators. We then study the geometry of the high-NA phase retrieval problem and the obtained results are subsequently used to establish convergence criteria of projection algorithms in the presence of noise. Making use of the vectorial point-spread-function (PSF) is, on the one hand, the key difference between this paper and the literature of phase retrieval mathematics which deals with the scalar PSF. The results of this paper, on the other hand, can be viewed as extensions of those concerning projection methods for low-NA phase retrieval. Importantly, the improved performance of projection methods over the other classes of phase retrieval algorithms in the low-NA setting now also becomes applicable to the high-NA case. This is demonstrated by the accompanying numerical results which show that available solution approaches for high-NA phase retrieval are outperformed by projection methods.

Original languageEnglish
Article number125005
Number of pages27
JournalInverse Problems
Issue number12
Publication statusPublished - 2021


  • High numerical aperture
  • Inconsistent feasibility
  • Nonconvex optimization
  • Phase retrieval
  • Projection algorithm


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