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Authors: Wen Cao ; Ehsan Miandji and Jonas Unger

Affiliation: Media and Information Technology, Department of Science and Technology, Linköping University, SE-601 74 Norrköping, Sweden

Keyword(s): Spectral Light Field, Compressive Sensing.

Abstract: This paper considers a compressive multi-spectral light field camera model that utilizes a one-hot spectral-coded mask and a microlens array to capture spatial, angular, and spectral information using a single monochrome sensor. We propose a model that employs compressed sensing techniques to reconstruct the complete multi-spectral light field from undersampled measurements. Unlike previous work where a light field is vectorized to a 1D signal, our method employs a 5D basis and a novel 5D measurement model, hence, matching the intrinsic dimensionality of multispectral light fields. We mathematically and empirically show the equivalence of 5D and 1D sensing models, and most importantly that the 5D framework achieves orders of magnitude faster reconstruction while requiring a small fraction of the memory. Moreover, our new multidimensional sensing model opens new research directions for designing efficient visual data acquisition algorithms and hardware.

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Paper citation in several formats:
Cao, W.; Miandji, E. and Unger, J. (2024). Multidimensional Compressed Sensing for Spectral Light Field Imaging. In Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP; ISBN 978-989-758-679-8; ISSN 2184-4321, SciTePress, pages 349-356. DOI: 10.5220/0012431300003660

@conference{visapp24,
author={Wen Cao. and Ehsan Miandji. and Jonas Unger.},
title={Multidimensional Compressed Sensing for Spectral Light Field Imaging},
booktitle={Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP},
year={2024},
pages={349-356},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012431300003660},
isbn={978-989-758-679-8},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP
TI - Multidimensional Compressed Sensing for Spectral Light Field Imaging
SN - 978-989-758-679-8
IS - 2184-4321
AU - Cao, W.
AU - Miandji, E.
AU - Unger, J.
PY - 2024
SP - 349
EP - 356
DO - 10.5220/0012431300003660
PB - SciTePress

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