高分辨率遥感影像的支持张量机分类方法

Classification of High Spatial Resolution Imagery Using Support Tensor Machine

针对高分辨率遥感数据分类多特征、小样本的特点,将训练样本像素邻域的数据立方以三阶张量表征,并提出了利用支持张量机对训练样本进行监督分类的模型和解法。实验结果表明,此方法能够利用少量的训练样本实现更优的分类精度。

We propose a support tensor machine for remote sensing image classification.The training samples are represented as 3-order tensors with local neighbor information.Then the mathematical model and solution of support tensor machine are discussed in detail.A range of experiments demonstrate that the effectiveness of the proposed method can deliver a high classification rate with a small number of training samples.