@inproceedings{a213df265eb84998bbc3859b19546d9b,
title = "Learning Extended Depth of field Hyperspectral Imaging",
abstract = "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.",
keywords = "deep learning, diffractive optics, extended depth of field, Hyperspectral imaging",
author = "Erdem Sahin and Ugur Akpinar and Ayoung Kim and Atanas Gotchev",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; IEEE International Conference on Image Processing (ICIP) ; Conference date: 08-10-2023 Through 11-10-2023",
year = "2023",
doi = "10.1109/ICIP49359.2023.10222477",
language = "English",
series = "Proceedings - International Conference on Image Processing, ICIP",
publisher = "IEEE",
pages = "1850--1854",
booktitle = "2023 IEEE International Conference on Image Processing, ICIP 2023 - Proceedings",
address = "United States",
}