作　　者： ; ; ; ; ;

机构地区： 北京林业大学林学院草坪研究所

出　　处： 《光谱学与光谱分析》 2012年第6期1620-1623,共4页

摘　　要： 利用高光谱成像技术(550～1 000nm),采集了6个草地早熟禾品种新鲜叶片的高光谱图像,提取了叶片的光谱信息,运用Wilks’Lambda逐步判别分析法,从94个波段中选择了9个特征波段,根据特征波段的光谱信息,采用Fisher线性判别法,构建草地早熟禾品种的判别分析模型。结果表明,选择3个、6个和9个波段组合,对120个训练样本的识别正确率分别为98.3%,100%和100%,对60个测试样本的识别正确率分别为83.3%,96.7%和100%,说明以9个特征波段的光谱信息构建的草地早熟禾品种判别模型是合适的,利用高光谱成像技术结合判别分析法,为快速识别草地早熟禾品种提供了一种新的方法。 Hyperspectral images of six varieties of Kentucky bluegrass were acquired using hyperspectral imager（550-1 000 nm） and the leaf spectral properties were extracted.Wilks＇ lambda stepwise method was used and 9 optimal wavelengths were selected from the original 94 wavelengths and the discriminant models for varieties identification of Kentucky bluegrass were built based on Fisher＇s linear discriminant function.The results showed that the Fisher＇s linear discriminant model with 9 wavelengths achieved classification accuracies of 100% for both training and testing samples.While for the models with three wavelengths and six wavelengths,classification accuracies reached 83.3% and 96.7% for the testing samples,respectively.It indicates that hyperspectral images combined with discriminant analysis might be a good method to identify the varieties of Kentucky bluegrass.

关 键 词： 高光谱成像 判别分析 草地早熟禾 品种识别

领　　域： [农业科学]