提出了一种新的光谱相似性度量方法，即非线性光谱角制图。
A novel method for spectral similarity measure, which is called nonlinear spectral Angle mapper, is presented.
探讨了光谱特征和光谱相似性度量、空间关系和空间谓词、元数据的应用。
Spectral features and spectral similarity measurement, spatial relationship and spatial predicate, and metadata are discussed in detail.
高光谱图像分割实验结果表明该方法在光谱相似性度量上优于传统的光谱角制图方法。
Experimental results of Hyperspectral image segmentation show that our method is better than traditional spectral Angle mapping method.
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