Learning Extended Depth of field Hyperspectral Imaging
Sahin, Erdem; Akpinar, Ugur; Kim, Ayoung; Gotchev, Atanas (2023)
Sahin, Erdem
Akpinar, Ugur
Kim, Ayoung
Gotchev, Atanas
2023
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-202407257729
https://urn.fi/URN:NBN:fi:tuni-202407257729
Kuvaus
Peer reviewed
Tiivistelmä
We propose a learning-based method for snapshot hyper-spectral (HS) imaging of deep 3D scenes. The method combines computational HS imaging and extended depth of field (EDoF) imaging capabilities in a single framework, resulting in novel EDoF-HS camera designs. The camera system incorporates a diffractive optical element at the aperture position, a CFA in front of the sensor and a residual dense network at the post-processing stage. These optical and neural components are jointly optimized through end-to-end learning procedure. We demonstrate high quality HS image reconstructions for scenes as deep as 4 diopters.
Kokoelmat
- TUNICRIS-julkaisut [19385]