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Fast super-resolution of hyperspectral 2d raman data

D. Winterauer 1 Saïd Moussaoui 2 Tim Batten 3 Bernard Humbert 1 Daniel Funes-Hernando 1 
1 IMN - Institut des Matériaux Jean Rouxel
2 LS2N - Laboratoire des Sciences du Numérique de Nantes
3 Renishaw plc
Abstract : Raman images are restored using interior point least squares (IPLS). Bounding hyperplane-based hyperspectral unmixing reduces the dimensionality of the data cube, substantially decreasing computation time. IPLS is then independently applied to all resulting map images. The proposed method is first validated on simulated data and then being applied to real Raman spectroscopic data. The results allow for better physical characterisation of the sample and the spatial resolution is enhanced from 400nm to better than 50nm.
Keywords : image enhancement inverse problems nonlinear optimization hyperspectral image restoration image deblurring
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Conference papers
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https://hal.archives-ouvertes.fr/hal-02585959
Contributor : Saïd Moussaoui Connect in order to contact the contributor
Submitted on : Friday, May 15, 2020 - 7:48:29 AM
Last modification on : Friday, August 5, 2022 - 2:54:51 PM

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  • HAL Id : hal-02585959, version 1

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UNIV-NANTES | INSTITUT-TELECOM | CNRS | EC-NANTES | IMN | UNAM | PMN | INC-CNRS | LS2N | LS2N-SIMS | NANTES-UNIVERSITE

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D. Winterauer, Saïd Moussaoui, Tim Batten, Bernard Humbert, Daniel Funes-Hernando. Fast super-resolution of hyperspectral 2d raman data. SIAM conference on Imaging Science, Jun 2018, Bologne, Italy. ⟨hal-02585959⟩

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