基于信息熵的遥感分类最优空间尺度选择方法

A New Approach for Choice of Optimal Spatial Scale in Image Classification Based on Entropy

以影像分类为例,从类别可分性的角度提出了基于信息熵的最优空间尺度选择方法。实验结果表明,基于信息熵的最优尺度选择方法的结果有很好的合理性,符合实际的分类结果,能够在一定程度上指导实际遥感分类中的空间尺度选择。

The existing methods for choice of optimal spatial scale are evaluated. It is pointed out that these are some methods based on statistics. However, these methods have not taken into account the spatial distribution. A new approach based on information entropy is introduced to select an optimal spatial scale in image classification. An experimental evaluation is also conducted. Results show that the new approach is more meaningful than traditional one. The proposed method will be useful for a variety of scale-related land cover classification tasks.