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Remote canopy hemispherical image collection system

机译:远程冠层半球形图像收集系统

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Canopies are major part of plant photosynthesis and have distinct architectural elements such as tree crowns, whorls, branches, shoots, etc. By measuring canopy structural parameters, the solar radiation interception, photosynthesis effects and the spatio-temporal distribution of solar radiation under the canopy can be evaluated. Among canopy structure parameters, Leaf Area Index (LAI) is the key one. Leaf area index is a crucial variable in agronomic and environmental studies, because of its importance for estimating the amount of radiation intercepted by the canopy and the crop water requirements. The LAI can be achieved by hemispheric images which are obtained below the canopy with high accuracy and effectiveness. But existing hemispheric images canopy-LAI measurement technique is based on digital SLR camera with a fisheye lens. Users need to collect hemispheric image manually. The SLR camera with fisheye lens is not suit for long-term canopy-LAI outdoor measurement too. And the high cost of SLR limits its capacity. In recent years, with the development of embedded system and image processing technology, low cost remote canopy hemispheric image acquisition technology is becoming possible. In this paper, we present a remote hemispheric canopy image acquisition system with in-field/host configuration. In-field node based on imbed platform, low cost image sensor and fisheye lens is designed to achieve hemispherical image of plant canopy at distance with low cost. Solar radiation and temperature/humidity data, which are important for evaluating image data validation, are obtained for invalid hemispherical image elimination and node maintenance too. Host computer interacts with in-field node by 3G network. The hemispherical image calibration and super resolution are used to improve image quality in host computer. Results show that the remote canopy image collection system can make low cost remote canopy image acquisition for LAI effectively. It will be a potential technology candidate for low-cost remote canopy hemispherical image collection to measure canopy LAI.
机译:Canopies是植物光合作用的主要部分,并具有不同的建筑元素,如树冠,螺纹,分支机构,芽等,通过测量冠层结构参数,太阳辐射拦截,光合作用以及天坡下的太阳辐射的时空分布可以评估。在树冠结构参数中,叶面积指数(LAI)是关键。叶面积指数是农艺和环境研究中的一个至关重要的变量,因为它的重要性是估计由树冠截取的辐射量和作物水要求。赖莱可以通过高精度和有效性在顶层获得的半球图像实现。但现有的半球图像Canopy-Lai测量技术基于带有Fisheye镜头的数字单反相机。用户需要手动收集半球图像。 SLR摄像头,带有Fisheye镜头的SLR相机不适合长期的Canopy-Lai户外测量。 SLR的高成本限制了其容量。近年来,随着嵌入式系统和图像处理技术的发展,低成本远程冠层半球图像采集技术正在成为可能。在本文中,我们介绍了一个具有现场/主机配置的远程半球形夹层图像采集系统。基于IMBAB平台的现场节点,低成本图像传感器和Fisheye镜头旨在以低成本实现植物冠层的半球形图像。对于无效的半球图像消除和节点维护,可以获得太阳辐射和温度/湿度数据,这对于评估图像数据验证很重要。主机与3G网络与现场节点交互。半球形图像校准和超级分辨率用于提高主机中的图像质量。结果表明,远程冠层图像收集系统有效地为LAI生产低成本的远程冠层图像采集。将是低成本远程冠层半球形图像集合的潜在技术候选人,以测量冠层赖。

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