loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Authors: Eric Wisotzky 1 ; 2 ; Jost Triller 1 ; Anna Hilsmann 1 and Peter Eisert 1 ; 2

Affiliations: 1 Computer Vision & Graphics, Fraunhofer HHI, Einsteinufer 37, 10587 Berlin, Germany ; 2 Department of Informatics, Humboldt University, Berlin, Germany

Keyword(s): Multispectral, Hyperspectral, Stereo-Reconstruction, Optical Flow, Disparity, Spectral Data Fusion, Demosaicing, Multispectral Snapshot Cameras.

Abstract: Spectral imaging enables the analysis of optical material properties that are invisible to the human eye. Different spectral capturing setups, e.g., based on filter-wheel, push-broom, line-scanning, or mosaic cameras, have been introduced in the last years to support a wide range of applications in agriculture, medicine, and industrial surveillance. However, these systems often suffer from different disadvantages, such as lack of real-time capability, limited spectral coverage or low spatial resolution. To address these drawbacks, we present a novel approach combining two calibrated multispectral real-time capable snapshot cameras, covering different spectral ranges, into a stereo-system. Therefore, a hyperspectral data-cube can be continuously captured. The combined use of different multispectral snapshot cameras enables both 3D reconstruction and spectral analysis. Both captured images are demosaicked avoiding spatial resolution loss. We fuse the spectral data from one camera into the other to receive a spatially and spectrally high resolution video stream. Experiments demonstrate the feasibility of this approach and the system is investigated with regard to its applicability for surgical assistance monitoring. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.23.101.75

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Wisotzky, E. ; Triller, J. ; Hilsmann, A. and Eisert, P. (2024). Multispectral Stereo-Image Fusion for 3D Hyperspectral Scene Reconstruction. In Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP; ISBN 978-989-758-679-8; ISSN 2184-4321, SciTePress, pages 88-99. DOI: 10.5220/0012354400003660

@conference{visapp24,
author={Eric Wisotzky and Jost Triller and Anna Hilsmann and Peter Eisert},
title={Multispectral Stereo-Image Fusion for 3D Hyperspectral Scene Reconstruction},
booktitle={Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP},
year={2024},
pages={88-99},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012354400003660},
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 3: VISAPP
TI - Multispectral Stereo-Image Fusion for 3D Hyperspectral Scene Reconstruction
SN - 978-989-758-679-8
IS - 2184-4321
AU - Wisotzky, E.
AU - Triller, J.
AU - Hilsmann, A.
AU - Eisert, P.
PY - 2024
SP - 88
EP - 99
DO - 10.5220/0012354400003660
PB - SciTePress