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Multimodal remote sensing for enhancing detection of spatial variability in agricultural fields

机译:多模式遥感技术,用于增强对农业空间变异性的检测

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Detection of variability in agricultural fields depends on the spatial scale of the observed variable. Plant water status can be evaluated using thermal IR images that can provide valuable information on the water status, whereas visible RGB images can provide detailed information on the plants' color, which is not a good indicator of the water status. The informative mode (thermal IR images) has coarse resolution, as opposed to the excessive resolution of the less informative mode (visible RGB). In the present study, we present a method to enhance the information obtained from the thermal IR mode, by combining information from the visible RGB mode. We propose to un-mix the temperature of objects in the thermal images based on the information extracted from the high resolution RGB image.
机译:在农业领域中检测变异性取决于所观察变量的空间尺度。可以使用热红外图像评估植物水的状态,该图像可以提供有关水状态的有价值的信息,而可见的RGB图像可以提供有关植物颜色的详细信息,这并不是水状态的良好指示。信息模式(热红外图像)的分辨率较差,而信息较少模式(可见RGB)的分辨率过高。在本研究中,我们提出了一种通过组合来自可见RGB模式的信息来增强从热IR模式获得的信息的方法。我们建议根据从高分辨率RGB图像中提取的信息,取消混合热图像中物体的温度。

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