Transport of Intensity Equation based Phase Retrieval Using Deep Transfer Learning

Xiaofeng Wu; Sibi Chakravarthy Shanmuagvel; Yunhui Zhu

doi:10.1364/COSI.2022.CM2A.3

Imaging and Applied Optics Congress 2022 (3D, AOA, COSI, ISA, pcAOP)
Technical Digest Series (Optica Publishing Group, 2022),
paper CM2A.3
•https://doi.org/10.1364/COSI.2022.CM2A.3

Transport of Intensity Equation based Phase Retrieval Using Deep Transfer Learning

Xiaofeng Wu, Sibi Chakravarthy Shanmuagvel, and Yunhui Zhu

Computational Optical Sensing and Imaging 2022

Vancouver, British Columbia Canada
11–15 July 2022
ISBN: 978-1-957171-09-8

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Phase Imaging and Phase Retrieval (CM2A)

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X. Wu, S. C. Shanmuagvel, and Y. Zhu, "Transport of Intensity Equation based Phase Retrieval Using Deep Transfer Learning," in Imaging and Applied Optics Congress 2022 (3D, AOA, COSI, ISA, pcAOP), Technical Digest Series (Optica Publishing Group, 2022), paper CM2A.3.

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Abstract

High-fidelity Quantitative phase imaging (QPI) has been achieved via deep learning, but building large data set is expensive and time-consuming. We propose a novel framework for transport of intensity equation based phase retrieval using transfer learning. We show efficacy of the proposed method with accelerated training and increased accuracy.

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