多光谱图像技术在土壤酸碱度检测中的应用

提出了一种利用多光谱图像的颜色特征对土壤酸碱度(pH值)进行快速无损检测的方法。首先,利用2CCD多光谱成像仪获取每个土壤样本的R、G、B、NIR图像各一幅,并对多光谱图像进行颜色空间转换,即从RGB色彩空间分别转换到HSV颜色空间和Lab颜色空间;然后提取不同颜色空间中多光谱图像的颜色特征;最后,分别将提取的颜色特征作为模型的输入变量,建立PLS和LS-SVM算法的土壤酸碱度预测模型。实验结果表明,利用多光谱图像技术对土壤酸碱度进行检测是可行的。预测模型的最佳结果如下:决定系数(R~2)为0.91,预测均方根误差(RMSEP)为0.34.

Application of Multispectral Image Technology in Detection of Soil pH Value

A method for fast and non-destructively detecting soil pH by using the color features in multispectral images is proposed. First, a 2 CCD multispectral imager is used to obtain the R, G, B and NIR images of each soil sample respectively. The multispectral images are converted in color space, i.e. the RGB color spaces are converted to the HSV color space and the Lab color space. Then, the color features of the multispectral images are extracted in different color spaces. Finally, the extracted color features are used as input variables, so as to establish a prediction model of soil pH by using PLS and LS-SVM algorithms. The experimental result shows that it is feasible to detect soil pH by using the multispectral image technology. The best result is given by the prediction model established. Its determination coefficient (R2) and root mean square error (RMSEP) value are 0.91 and 0.34 respectively.