Fast Phase Retrieval: Unique and Stable Complex Object Recovery in O(NLogN) Time

Cole Brabec; Sivan Trajtenberg Mills; Mohamed ElKabbash; Ian Christen; Dirk Englund

doi:10.1364/CLEO_AT.2023.AW4I.5

CLEO 2023
Technical Digest Series (Optica Publishing Group, 2023),
paper AW4I.5
•https://doi.org/10.1364/CLEO_AT.2023.AW4I.5

Fast Phase Retrieval: Unique and Stable Complex Object Recovery in O(NLogN) Time

Cole Brabec, Sivan Trajtenberg Mills, Mohamed ElKabbash, Ian Christen, and Dirk Englund

CLEO: Applications and Technology 2023

San Jose, CA United States
7–12 May 2023
ISBN: 978-1-957171-25-8

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Advancing Environmental Sensing with Artificial Intelligence and Machine Learning Methods (AW4I)

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C. Brabec, S. T. Mills, M. ElKabbash, I. Christen, and D. Englund, "Fast Phase Retrieval: Unique and Stable Complex Object Recovery in O(NLogN) Time," in CLEO 2023, Technical Digest Series (Optica Publishing Group, 2023), paper AW4I.5.

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Abstract

We present a novel Phase Retrieval algorithm that is able to uniquely recover a complex object from its noise-corrupted Fourier magnitudes in an arbitrary number of dimensions while running in O(N Log N) time.

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