实验结果表明了基于动力演化算法的投影寻踪在高光谱影像异常目标检测中的有效性。
The experimental results show that the Projection Pursuit based on dynamical evolutionary approach is an effective means to detect anomaly target in hyperspectral images.
实验也表明，选择合适的对称化方法规范扩散算子对于最终的高光谱影像表示有重要的影响。
Experiments also show that selecting suitable symmetrization normalization techniques while forming the diffusion operator is important to hyperspectral imagery representation.
将关联向量机应用于高光谱影像分类， 实现高维空间中训练样本不足时分类器的精确建模。
The relevance vector machine (RVM) is used to process the hyperspectral image in this paper to estimate the classifiers precisely in the high dimensional space with limited training samples.
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