Abstract

In this work, we propose a method based on nonlinear optimization to process holograms corrupted with nonuniform intensity fluctuations in digital holographic microscopy. Our method focuses on formulating an objective function from the recorded signal and subsequently minimizing it using a second-order optimization algorithm. We demonstrate the effectiveness of our method for phase extraction in the presence of severe noise and rapid intensity variations through extensive numerical simulations. Further, we validate the practical applicability of our method for nanoscale surface topography of standard test samples in digital holographic microscopy.

© 2023 Optica Publishing Group

Demodulation of noisy interferograms with rapid phase variations and amplitude fluctuations using a surrogate principle-based optimization method

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Step phase reconstruction using an anisotropic total variation regularization method in a diffraction phase microscopy

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Phase derivative estimation in digital holographic interferometry using a deep learning approach

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Multiple phase extraction using graphics processing unit assisted unitary transformation method in digital holographic interferometry

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Appl. Opt. 61(28) 8180-8189 (2022)