Unfolding-Aided Bootstrapped Phase Retrieval in Optical Imaging

Samuel Pinilla, Kumar Vijay Mishra, Igor Shevkunov, Mojtaba Soltanalian, Vladimir Katkovnik, Karen Egiazarian

Research output: Working paperPreprintResearch

Abstract

Phase retrieval in optical imaging refers to the recovery of a complex signal from phaseless data acquired in the form of its diffraction patterns. These patterns are acquired through a system with a coherent light source that employs a diffractive optical element (DOE) to modulate the scene resulting in coded diffraction patterns at the sensor. Recently, the hybrid approach of model-driven network or deep unfolding has emerged as an effective alternative to conventional model-based and learning-based phase retrieval techniques because it allows for bounding the complexity of algorithms while also retaining their efficacy. Additionally, such hybrid approaches have shown promise in improving the design of DOEs that follow theoretical uniqueness conditions. There are opportunities to exploit novel experimental setups and resolve even more complex DOE phase retrieval applications. This paper presents an overview of algorithms and applications of deep unfolding for bootstrapped - regardless of near, middle, and far zones - phase retrieval.
Original languageEnglish
DOIs
Publication statusPublished - 3 Mar 2022
Publication typeNot Eligible

Keywords

  • physics.optics
  • cs.LG
  • eess.SP

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