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Authors: Sebastian Merzbach 1 ; Michael Weinmann 1 ; Martin Rump 2 and Reinhard Klein 1

Affiliations: 1 University of Bonn, Germany ; 2 X-Rite and Inc., United States

Keyword(s): Spectral, Reflectance, Noise, Spectral Reconstruction.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Image-Based Rendering ; Lighting and Appearance ; Rendering

Abstract: In recent years there has been an increasing interest in multispectral imaging hardware. Among many other applications is the color-correct reproduction of materials. In this paper, we aim at circumventing the limitations of most devices, namely extensive acquisition times for acceptable signal-to-noise-ratios. For this purpose we propose a novel approach to spectral imaging that combines high-quality RGB data and spatial filtering of extremely noisy and sparsely measured spectral information. The capability of handling noisy spectral data allows a dramatic reduction of overall exposure times. The speed-up we achieve allows for spectral imaging at practical acquisition times. We use the RGB images for constraining the reconstruction of dense spectral information from the filtered noisy spectral data. A further important contribution is the extension of a commonly used radiometric calibration method for determining the camera response in the lowest, noise-dominated range of pixel valu es. We apply our approach both to capturing single high-quality spectral images, as well as to the acquisition of image-based multispectral surface reflectance. Our results demonstrate that we are able to lower the acquisition times for such multispectral reflectance from several days to the few hours necessary for an RGB-based measurement. (More)

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Paper citation in several formats:
Merzbach, S.; Weinmann, M.; Rump, M. and Klein, R. (2017). Fast Capture of Spectral Image Series. In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - GRAPP; ISBN 978-989-758-224-0; ISSN 2184-4321, SciTePress, pages 148-159. DOI: 10.5220/0006175901480159

@conference{grapp17,
author={Sebastian Merzbach. and Michael Weinmann. and Martin Rump. and Reinhard Klein.},
title={Fast Capture of Spectral Image Series},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - GRAPP},
year={2017},
pages={148-159},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006175901480159},
isbn={978-989-758-224-0},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - GRAPP
TI - Fast Capture of Spectral Image Series
SN - 978-989-758-224-0
IS - 2184-4321
AU - Merzbach, S.
AU - Weinmann, M.
AU - Rump, M.
AU - Klein, R.
PY - 2017
SP - 148
EP - 159
DO - 10.5220/0006175901480159
PB - SciTePress