Publication detail

Addressing Data Management for Custom Built Hyperspectral Microscopy Station

VACULÍK, O. ŠERÝ, M. ŠILHAN, L. ŠILHANOVÁ, D. ZEMÁNEK, P.

English title

Addressing Data Management for Custom Built Hyperspectral Microscopy Station

Type

conference paper

Language

en

Original abstract

Hyperspectral (HS) imaging, originally developed for satellite applications as a remote sensing spatiospectral analysis technique, has been adopted by numerous scientific fields. By combining HS imaging and microscopy, we can capture not only spectral and spatial information but also non-destructively uncover compositional and chemical information, which is especially beneficial for applications in agriculture, food safety and inspection, medical research, microbiology and algae research. To assist in this endeavor, we have developed a modular pushbroom HS microscope platform that allows automated HS measurement to be conducted. This naturally poses a problem in the form of proper data management, as the volume and data storage requirements for such a type of system are essential to plan for in advance. In this paper, we address this problem and present our HS data management workflow with complete data and metadata collection, suitable format selection, and data compression, all with the FAIR data principles in mind.

English abstract

Hyperspectral (HS) imaging, originally developed for satellite applications as a remote sensing spatiospectral analysis technique, has been adopted by numerous scientific fields. By combining HS imaging and microscopy, we can capture not only spectral and spatial information but also non-destructively uncover compositional and chemical information, which is especially beneficial for applications in agriculture, food safety and inspection, medical research, microbiology and algae research. To assist in this endeavor, we have developed a modular pushbroom HS microscope platform that allows automated HS measurement to be conducted. This naturally poses a problem in the form of proper data management, as the volume and data storage requirements for such a type of system are essential to plan for in advance. In this paper, we address this problem and present our HS data management workflow with complete data and metadata collection, suitable format selection, and data compression, all with the FAIR data principles in mind.

Keywords in English

data management; dimensionality reduction; image compression; machine learning; pushbroom hyperspectral imaging

Released

19.02.2025

Publisher

IEEE Computer Society

Location

Helsinki, Finland

ISBN

979-8-3315-1313-9

Book

2024 14th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)

Pages count

5

BIBTEX


@inproceedings{BUT197471,
  author="Ondřej {Vaculík} and Mojmír {Šerý} and Lukáš {Šilhan} and Denisa {Šilhanová} and Pavel {Zemánek},
  title="Addressing Data Management for Custom Built Hyperspectral Microscopy Station",
  booktitle="2024 14th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)",
  year="2025",
  month="February",
  publisher="IEEE Computer Society",
  address="Helsinki, Finland",
  isbn="979-8-3315-1313-9"
}