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Article Dans Une Revue Optics Express Année : 2023

Automatic depth map retrieval from digital holograms using a deep learning approach

Résumé

Information extraction from computer-generated holograms using learning-based methods is a topic that has not received much research attention. In this article, we propose and study two learning-based methods to extract the depth information from a hologram and compare their performance with that of classical depth from focus (DFF) methods. We discuss the main characteristics of a hologram and how these characteristics can affect model training. The obtained results show that it is possible to extract depth information from a hologram if the problem formulation is well-posed. The proposed methods are faster and more accurate than state-of-the-art DFF methods.
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Dates et versions

hal-03997493 , version 1 (20-02-2023)

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Nabil Madali, Antonin Gilles, Patrick Gioia, Luce Morin. Automatic depth map retrieval from digital holograms using a deep learning approach. Optics Express, 2023, 31 (3), pp.4199-4215. ⟨10.1364/oe.480561⟩. ⟨hal-03997493⟩
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