@inproceedings{d79bd25ffb2e4076a7c1874715104e51,
title = "Spatial versus spectral compression ratio in compressive sensing of hyperspectral imaging",
abstract = "Compressive hyperspectral imaging is based on the fact that hyperspectral data is highly redundant. However, there is no symmetry between the compressibility of the spatial and spectral domains, and that should be taken into account for optimal compressive hyperspectral imaging system design. Here we present a study of the influence of the ratio between the compression in the spatial and spectral domains on the performance of a 3D separable compressive hyperspectral imaging method we recently developed.",
keywords = "CHISSS, Compressive sensing, Hyperspectral imaging, Separable sensing",
author = "Yitzhak August and Chaim Vachman and Adrian Stern",
year = "2013",
month = aug,
day = "8",
doi = "10.1117/12.2017949",
language = "English",
isbn = "9780819495082",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
booktitle = "Compressive Sensing II",
note = "Compressive Sensing II ; Conference date: 02-05-2013 Through 03-05-2013",
}