@inproceedings{d1e9b50c469f4ae7b900afe5909bc984,
title = "Dictionary based Hyperspectral Image Reconstruction Captured with CS-MUSI",
abstract = "The Compressive Sensing Miniature Ultra-Spectral Imaging (CS-MUSI) camera uses a spectral modulator and a grayscale sensor in order to capture an encoded compressed spectral signal. Using the compressive sensing (CS) theory hyperspectral (HS) cubes with hundreds of spectral bands can be reconstructed from an order of magnitude fewer samples. In this work, we show that by using spectral dictionary, as the sparsifying operator, for reconstruction of CS HS images acquired with our CS-MUSI camera, we can both increase the reconstruction quality and reduce the number of measurements CS theory requires as well.",
keywords = "CS-MUSI, Compressive sensing, Dictionary, Hyperspectral, Sparsifying operator",
author = "Yaniv Oiknine and Boaz Arad and Isaac August and Ohad Ben-Shahar and Adrian Stern",
note = "Funding Information: This research was supported by the Ministry of Science, Technology & Space, Israel (grant 3-18410). This research was supported in part by the Israel Science Foundation (ISF FIRST/BIKURA Grant 281/15) and the European Commission (Horizon 2020 grant SWEEPER GA no. 644313). Yaniv Oiknine wishes to thank Ministry of Science, Technology & Space, Israel (grant 3-13351) for supporting this research. Boaz Arad and Ohad Ben-Shahar wishes to thank the Frankel Fund and the Helmsley Charitable Trust through the ABC Robotics Initiative, both at Ben-Gurion University of the Negev. Publisher Copyright: {\textcopyright} 2018 IEEE.; 9th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2018 ; Conference date: 23-09-2018 Through 26-09-2018",
year = "2018",
month = sep,
day = "1",
doi = "10.1109/WHISPERS.2018.8747233",
language = "English",
series = "Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing",
publisher = "Institute of Electrical and Electronics Engineers",
booktitle = "2018 9th Workshop on Hyperspectral Image and Signal Processing",
address = "United States",
}