License: 
Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/DagRep.7.10.14
URN: urn:nbn:de:0030-drops-86614
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2018/8661/
Arce, Gonzalo R. ;
Bamler, Richard ;
Hardeberg, Jon Yngve ;
Kolb, Andreas ;
Beigpour, Shida
Weitere Beteiligte (Hrsg. etc.): Gonzalo R. Arce and Richard Bamler and Jon Yngve Hardeberg and Andreas Kolb and Shida Beigpour
HMM Imaging: Acquisition, Algorithms, and Applications (Dagstuhl Seminar 17411)
Abstract
In the last couple of decades, hyperspectral, multispectral, and multimodal (HMM) imaging has emerged as an essential tool in various fields of science, medicine, and technology. Compared to integrated broad-band information as, e.g., present in RGB images, HMM imaging strives to acquire a multitude of specific narrow bands of the electromagnetic spectrum in order to solve specific detection or analysis tasks. HMM research is interested in studying light-matter interaction in a wide range of wavelengths from the high energy radiation down to Terahertz radiation (sub-millimeter waves). Furthermore, combining spectral data captured using different imaging modalities can unveil additional information of the scene that is not revealed solely by each of the individual imaging modalities.
The workshop intended to connect researchers from different disciplines that involve HMM imaging and analysis. Even though there are very different approaches towards HMM imaging research and application, the main hypothesis of the workshop was that there is a large amount of common goals, approaches and challenges. Thus, these disciplines will benefit from intensifying communication and knowledge transfer and an out-of-the-box thinking and a broader vision of the fundamental concepts regarding common fields of interest, e.g., in the configuration of HMM acquisition systems, data analysis, and improved development techniques by common software bases and validation tools.
The seminar succeeded in bringing together researchers from different scientific communities and fostering open-minded discussions across very different fields of research and application.
BibTeX - Entry
@Article{arce_et_al:DR:2018:8661,
author = {Gonzalo R. Arce and Richard Bamler and Jon Yngve Hardeberg and Andreas Kolb and Shida Beigpour},
title = {{HMM Imaging: Acquisition, Algorithms, and Applications (Dagstuhl Seminar 17411)}},
pages = {14--41},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2018},
volume = {7},
number = {10},
editor = {Gonzalo R. Arce and Richard Bamler and Jon Yngve Hardeberg and Andreas Kolb and Shida Beigpour},
publisher = {Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
address = {Dagstuhl, Germany},
URL = {http://drops.dagstuhl.de/opus/volltexte/2018/8661},
URN = {urn:nbn:de:0030-drops-86614},
doi = {10.4230/DagRep.7.10.14},
annote = {Keywords: compressive sensing, computer vision, hyperspectral and multispectral imaging and analysis, multi-modal sensor fusion, remote sensing and geoscience}
}
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Keywords: |
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compressive sensing, computer vision, hyperspectral and multispectral imaging and analysis, multi-modal sensor fusion, remote sensing and geoscience |
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Collection: |
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Dagstuhl Reports, Volume 7, Issue 10 |
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Issue Date: |
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2018 |
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Date of publication: |
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27.03.2018 |
