Stuart, M. orcid.org/0000-0002-3187-9164, Davies, M., Hobbs, M. et al. (3 more authors) (2022) High-resolution hyperspectral imaging using low-cost components: application within environmental monitoring scenarios. Sensors, 22 (12). 4652. ISSN 1424-8220
Abstract
High-resolution hyperspectral imaging is becoming indispensable, enabling the precise detection of spectral variations across complex, spatially intricate targets. However, despite these significant benefits, currently available high-resolution set-ups are typically prohibitively expensive, significantly limiting their user base and accessibility. These limitations can have wider implications, limiting data collection opportunities, and therefore our knowledge, across a wide range of environments. In this article we introduce a low-cost alternative to the currently available instrumentation. This instrument provides hyperspectral datasets capable of resolving spectral variations in mm-scale targets, that cannot typically be resolved with many existing low-cost hyperspectral imaging alternatives. Instrument metrology is provided, and its efficacy is demonstrated within a mineralogy-based environmental monitoring application highlighting it as a valuable addition to the field of low-cost hyperspectral imaging.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
Keywords: | hyperspectral; low-cost; high-resolution; environmental monitoring |
Dates: |
|
Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Electronic and Electrical Engineering (Sheffield) |
Funding Information: | Funder Grant number Engineering and Physical Sciences Research Council 2117397 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 21 Jun 2022 13:12 |
Last Modified: | 21 Jun 2022 14:16 |
Published Version: | https://www.mdpi.com/1424-8220/22/12/4652 |
Status: | Published |
Publisher: | MDPI AG |
Refereed: | Yes |
Identification Number: | 10.3390/s22124652 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:188261 |