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Fast reconstruction of hyperspectral images from coded acquisitions using a separability assumption

Elizabeth Hemsley 1 Ibrahim Ardi 2, 1 Tony Rouvier 2 Simon Lacroix 3 Hervé Carfantan 2 Antoine Monmayrant 1 
1 LAAS-PHOTO - Équipe Photonique
LAAS - Laboratoire d'analyse et d'architecture des systèmes
3 LAAS-RIS - Équipe Robotique et InteractionS
LAAS - Laboratoire d'analyse et d'architecture des systèmes
Abstract : We present a fast reconstruction algorithm for hyperspectral images, utilizing a small amount of data without the need for any training. The method is implemented with a dual disperser hyperspectral imager, and makes use of spatial-spectral correlations by a so-called separability assumption which assumes that the image is made of regions of homogenous spectra. The reconstruction algorithm is simple and ready-to-use, and does not require any prior knowledge of the scene. A simple proof-of-principle experiment is performed, demonstrating that only a small number of acquisitions are required, and the resulting compressed data-cube is reconstructed near instantaneously.
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https://hal.archives-ouvertes.fr/hal-03610209
Contributor : Antoine Monmayrant Connect in order to contact the contributor
Submitted on : Thursday, July 28, 2022 - 11:08:44 AM
Last modification on : Tuesday, August 2, 2022 - 4:36:59 AM

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Elizabeth Hemsley, Ibrahim Ardi, Tony Rouvier, Simon Lacroix, Hervé Carfantan, et al.. Fast reconstruction of hyperspectral images from coded acquisitions using a separability assumption. Optics Express, Optical Society of America - OSA Publishing, 2022, 30 (5), pp.8174-8185. ⟨10.1364/OE.448893⟩. ⟨hal-03610209v2⟩

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