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Towards Low-Cost Hyperspectral Single-Pixel Imaging for Plant Phenotyping

Hyperspectral imaging techniques have been expanding considerably in recent years. The cost of current solutions is decreasing, but these high-end technologies are not yet available for moderate to low-cost outdoor and indoor applications. We have used some of the latest compressive sensing methods...

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Detalles Bibliográficos
Autores principales: Ribes, Mathieu, Russias, Gaspard, Tregoat, Denis, Fournier, Antoine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7070961/
https://www.ncbi.nlm.nih.gov/pubmed/32093006
http://dx.doi.org/10.3390/s20041132
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author Ribes, Mathieu
Russias, Gaspard
Tregoat, Denis
Fournier, Antoine
author_facet Ribes, Mathieu
Russias, Gaspard
Tregoat, Denis
Fournier, Antoine
author_sort Ribes, Mathieu
collection PubMed
description Hyperspectral imaging techniques have been expanding considerably in recent years. The cost of current solutions is decreasing, but these high-end technologies are not yet available for moderate to low-cost outdoor and indoor applications. We have used some of the latest compressive sensing methods with a single-pixel imaging setup. Projected patterns were generated on Fourier basis, which is well-known for its properties and reduction of acquisition and calculation times. A low-cost, moderate-flow prototype was developed and studied in the laboratory, which has made it possible to obtain metrologically validated reflectance measurements using a minimal computational workload. From these measurements, it was possible to discriminate plant species from the rest of a scene and to identify biologically contrasted areas within a leaf. This prototype gives access to easy-to-use phenotyping and teaching tools at very low-cost.
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spelling pubmed-70709612020-03-19 Towards Low-Cost Hyperspectral Single-Pixel Imaging for Plant Phenotyping Ribes, Mathieu Russias, Gaspard Tregoat, Denis Fournier, Antoine Sensors (Basel) Article Hyperspectral imaging techniques have been expanding considerably in recent years. The cost of current solutions is decreasing, but these high-end technologies are not yet available for moderate to low-cost outdoor and indoor applications. We have used some of the latest compressive sensing methods with a single-pixel imaging setup. Projected patterns were generated on Fourier basis, which is well-known for its properties and reduction of acquisition and calculation times. A low-cost, moderate-flow prototype was developed and studied in the laboratory, which has made it possible to obtain metrologically validated reflectance measurements using a minimal computational workload. From these measurements, it was possible to discriminate plant species from the rest of a scene and to identify biologically contrasted areas within a leaf. This prototype gives access to easy-to-use phenotyping and teaching tools at very low-cost. MDPI 2020-02-19 /pmc/articles/PMC7070961/ /pubmed/32093006 http://dx.doi.org/10.3390/s20041132 Text en © 2020 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Ribes, Mathieu
Russias, Gaspard
Tregoat, Denis
Fournier, Antoine
Towards Low-Cost Hyperspectral Single-Pixel Imaging for Plant Phenotyping
title Towards Low-Cost Hyperspectral Single-Pixel Imaging for Plant Phenotyping
title_full Towards Low-Cost Hyperspectral Single-Pixel Imaging for Plant Phenotyping
title_fullStr Towards Low-Cost Hyperspectral Single-Pixel Imaging for Plant Phenotyping
title_full_unstemmed Towards Low-Cost Hyperspectral Single-Pixel Imaging for Plant Phenotyping
title_short Towards Low-Cost Hyperspectral Single-Pixel Imaging for Plant Phenotyping
title_sort towards low-cost hyperspectral single-pixel imaging for plant phenotyping
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7070961/
https://www.ncbi.nlm.nih.gov/pubmed/32093006
http://dx.doi.org/10.3390/s20041132
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