Suppr超能文献

面向植物表型低成本高光谱单像素成像。

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

机构信息

Department of Crop Phenotyping, Arvalis-Institut du Végétal, 45 voie Romaine, Ouzouer le Marché, 41240 Beauce-la-Romaine, France.

Department of Biophotonics, Photonics Bretagne, 4 rue Louis de Broglie, 22300 Lannion, France.

出版信息

Sensors (Basel). 2020 Feb 19;20(4):1132. doi: 10.3390/s20041132.

Abstract

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.

摘要

近年来,高光谱成像技术得到了极大的发展。目前解决方案的成本正在降低,但这些高端技术还无法应用于中低价位的户外和室内应用。我们使用了一些最新的压缩感知方法和单像素成像设置。投影模式是在傅里叶基上生成的,傅里叶基以其特性和减少采集和计算时间而闻名。我们开发并在实验室中研究了一种低成本、中等流量的原型,它可以使用最小的计算工作量获得经过计量验证的反射率测量值。通过这些测量,可以从场景的其余部分中区分植物物种,并识别叶片内具有生物对比度的区域。这个原型提供了非常低成本的易于使用的表型和教学工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a67/7070961/0118e560a1db/sensors-20-01132-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验