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Journal Articles Optics Express Year : 2024

PS-NET: an end-to-end phase space depth estimation approach for computer-generated holograms

Abstract

In the present work, an end-to-end approach is proposed for recovering an RGB-D scene representation directly from a hologram using its phase space representation. The proposed method involves four steps. First, a set of silhouette images is extracted from the hologram phase space representation. Second, a minimal 3D volume that describes these silhouettes is extracted. Third, the extracted 3D volume is decomposed into horizontal slices, and each slice is processed using a neural network to generate a coarse estimation of the scene geometry. Finally, a third neural network is employed to refine the estimation for higher precision applications. Experimental results demonstrate that the proposed approach yields faster and more accurate results compared to numerical reconstruction-based methods. Moreover, the obtained RGB-D representation can be directly utilized for alternative applications such as motion estimation.
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Dates and versions

hal-04392285 , version 1 (15-01-2024)

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Nabil Madali, Antonin Gilles, Patrick Gioia, Luce Morin. PS-NET: an end-to-end phase space depth estimation approach for computer-generated holograms. Optics Express, 2024, 32 (2), pp.2473. ⟨10.1364/oe.501085⟩. ⟨hal-04392285⟩
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