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Article Dans Une Revue Optics Letters Année : 2023

H-Seg: a horizontal reconstruction volume segmentation method for accurate depth estimation in a computer-generated hologram

Résumé

In this work, we introduce a novel approach for depth estimation in a computer-generated hologram by employing horizontal segmentation of the reconstruction volume instead of conventional vertical segmentation. The reconstruction volume is divided into horizontal slices and each slice is processed using a residual U-net architecture to identify in-focus lines, enabling determination of the slice’s intersection with the 3D scene. The individual slice results are then combined to generate a dense depth map of the scene. Our experiments demonstrate the effectiveness of our method, with improved accuracy, faster processing times, lower graphics processing unit (GPU) utilization, and smoother predicted depth maps than existing state-of-the-art models.
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Dates et versions

hal-04122546 , version 1 (08-06-2023)

Identifiants

Citer

Nabil Madali, Antonin Gilles, Patrick Gioia, Luce Morin. H-Seg: a horizontal reconstruction volume segmentation method for accurate depth estimation in a computer-generated hologram. Optics Letters, 2023, 48 (12), pp.3195. ⟨10.1364/OL.487338⟩. ⟨hal-04122546⟩
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