文章采用了基于核的Fisher linear discriminant(FLD)分类和形状特征相结合的方法进行道路提取。首先，对标记的样本进行色彩信息的抽取；其次，利用基于核的FLD根据抽取的信息对遥感影像进行特征训练分类，将影像分为道路和非道路两类；接着利用道路的形状特征去除误提的信息；最后利用形态学对道路网进行优化处理。实验证明，本方法可以实现具有颜色信息的遥感影像道路的提取。
In this paper, a road extracton method is proposed by combining kernel-based Fisher linear discriminant (FLD) classification and shape feature. This method has four main steps: First, the color information of labeled samples is extracted. Then kernel-based Fisher linear discriminant is used to implement feature classification to segment the images into two categories: road and non-road, according to the information extracted before. After that, the road shape optimization features are used to remove erroneous extraction. Finally, morphological processing are used to optimize the extraction results.Experiment results show that the proposed method in this paper can realize the extraction of road from remote sensing image with color information.
引用本文格式： 谢明鸿,宋纳. 一种高分辨率遥感影像道路提取方法[J]. 四川大学学报: 自然科学版, 2017, 54: 81.复制