高光谱成像
多光谱图像
叶斑病
遥感
天蓬
RGB颜色模型
无人机
计算机科学
极化(电化学)
环境科学
计算机视觉
生物
地理
农学
植物
化学
物理化学
作者
Joshua Larsen,Robert Austin,Jeffrey C. Dunne,Michael W. Kudenov
摘要
Polarization imaging has been used extensively in applications related to atmospheric monitoring, remote sensing, and quality control. However, it has been used less extensively in agricultural applications, where color sensing - either red, green, and blue (RGB) imaging, multispectral, and/or hyperspectral cameras are more common. In this paper, we discuss our preliminary results related to the use of polarization imaging to quantify defoliation in peanut plants in response to leaf spot disease. A key metric for breeding resistant peanut varieties involves identifying the point at which defoliation occurs. Since defoliation is a geometrical property of the plant canopy, we investigated whether polarization imaging can provide a better-automated score when compared to conventional visual scoring. Initial results are presented, as well as a discussion of our drone-based platform and our experimental trials conducted during the 2021 North Carolina growing season.
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