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中文摘要：
以前的研究往往从像素光谱的角度来解译高光谱影像，忽略了像素问的空间上下文关系。本文提出一种基于像素和对象层形状特征提取与融合的方法，把多层形状特征和光谱信息用支持向量机（SVM）输出函数方法进行融合，用于提取城市高光谱影像的形状特性，利用影像的空间关系。实验用HydICE—DC航空高光谱数据对提出的方法进行了验证，结果表明：像素级形状指数能够提供比对象级形状指数更优的结果，但像素一对象级形状特征的融合，能够给出更高的精度。
英文摘要：
Traditional methods for hyperspectral image interpretation only focused on spectral information, without considering the spatial context. In this paper, we proposed a multilevel shape feature fusion approach combing both pixel- and object-level shape features. The extracted multilevel shape information was integrated with the spectral features using the output of SVM-based discriminant function. Experiments were conducted on the HydlCE DC Mall hyperspectral dataset, and results showed that the pixel-level shape index outperformed the obiect-based index, while the multilevel shape features gave the highest accuracies.
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