基于多种空间信息的高光谱遥感图像分类方法

在高光谱遥感图像分类方法中，空间特征和光谱特征的融合可以有效地改善分类效果。针对单一空间特征的信息表达不充分问题，提出了一种联合多种空间特征的高光谱图像空谱分类方法。利用超像素信息对分类结果进行后处理去掉椒盐噪声，并创造性地将超像素信息应用于分类前处理，提出了一种利用超像素信息对像素点的特征向量进行线性加权融合的方法。试验结果表明，所提方法的性能优于目前的通常方法。

A hyperspectral remote sensing image classification method based on multi spatial information

In the field of hyperspectral remote sensing image classification, spatial and spectral feature fusion can improve the effect of classification. A multi feature spectral and spatial classification method for hyperspectral images was proposed. In the post processing procedure, the salt and pepper noises were removed by using superpixel information. It was also used in the pre processing procedure, and the feature vector of pixels was weighted by superpixel information. The experiment results show that the results of proposed method are better than the present methods.