Automated algorithms to identify and locate grains of specific composition for NIR hyperspectral microscopes: Application to the MicrOmega instrument onboard ExoMars
- Creators
- Pilorget, C.
- Bibring, J.-P.
Abstract
MicrOmega is an NIR hyperspectral microscope that has been selected as part of the ExoMars rover payload. We demonstrate here that this instrument has the capability through automated algorithms to identify and locate grains of interest (composition-wise) within a collected sample that could be further targeted by other instruments within the ExoMars payload. Results will also be used to perform an optimized compression of the data, with regard to the relevance of the different grains, in order to limit the volume of downloaded data. The algorithms that we have developed, using combined spectral criteria and different tests to avoid false positive, have proven to be both highly robust and efficient. They will be used onboard ExoMars rover, and could also be adapted for future robotic missions involving hyperspectral microscopes.
Additional Information
© 2014 Elsevier Ltd. Received 13 August 2013, revised 10 April 2014, accepted 26 May 2014, available online 3 June 2014. We would like to thank our colleagues from the MicrOmega team for helping us to perform the measurements on the breadboard and for fruitful discussions. We also thank the two anonymous reviewers for their comments which helped improving the manuscript.Additional details
- Eprint ID
- 49055
- DOI
- 10.1016/j.pss.2014.05.017
- Resolver ID
- CaltechAUTHORS:20140829-092013521
- Created
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2014-08-29Created from EPrint's datestamp field
- Updated
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2021-11-10Created from EPrint's last_modified field