Computational Hyperspectral Imaging with Diffractive Optics and Deep Residual Network

Tutkimustuotos: KonferenssiartikkeliScientificvertaisarvioitu

16 Lataukset (Pure)

Abstrakti

Hyperspectral imaging critically serves for various fields such as remote sensing, biomedical and agriculture. Its potential can be exploited to a greater extent when combined with deep learning methods, which improve the reconstructed hyperspectral image quality and reduce the processing time. In this paper, we propose a novel snapshot hyperspectral imaging system using optimized diffractive optical element and color filter along with the residual dense network. We evaluate our method through simulations considering the effects of each optical element and noise. Simulation results demonstrate high-quality hyperspectral image reconstruction capabilities through the proposed computational hyperspectral camera.
AlkuperäiskieliEnglanti
OtsikkoIEEE European Workshop on Visual Information Processing (EUVIP)
ISBN (elektroninen)978-1-6654-6623-3
DOI - pysyväislinkit
TilaJulkaistu - 2022
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaEuropean Workshop on Visual Information Processing - Lisbon, Portugali
Kesto: 11 syysk. 202214 syysk. 2022

Julkaisusarja

NimiEuropean Workshop on Visual Information Processing
ISSN (elektroninen)2471-8963

Conference

ConferenceEuropean Workshop on Visual Information Processing
Maa/AluePortugali
KaupunkiLisbon
Ajanjakso11/09/2214/09/22

Julkaisufoorumi-taso

  • Jufo-taso 1

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