融合高程信息的低空遥感影像SLIC分割和区域合并方法

Study on SLIC segmentation and region merging method of low-altitude remote sensing images with fused elevation information

针对SLIC分割算法在进行遥感影像分割时未考虑高程信息,导致某些地物分割效果欠佳的问题,本文提出了融合高程信息的遥感影像SLIC超像素分割与基于高程分级的双阈值区域合并方法。首先,在初始聚类分割阈值中引入高程信息,以获得对光谱梯度和高程梯度都具有一定依赖性的初始分割结果;然后,在预分割的基础上采用邻域数组的数据结构,将不同区域的光谱信息加权结合高程信息建立相似性度量;最后,设置分级的高程阈值,根据不同的区域间高差设置不同的合并阈值权重进行区域合并。利用融合高程信息的低空遥感影像数据及国际摄影测量与遥感协会提供的数据集进行所提方法验证,结果表明,在基于光谱信息的超像素分割与区域合并方法中引入高程信息,取得了良好的分割结果。

Aiming at the problem that SLIC segmentation algorithm does not consider elevation information in remote sensing image segmentation,which leads to poor segmentation effect of some features,this paper proposes the SLIC super-pixel segmentation of remote sensing image fused with elevation information and the double-threshold region merging method based on elevation grading.Firstly,the elevation information is introduced into the initial clustering segmentation threshold to obtain the initial segmentation result with dependence on both spectral gradient and elevation gradient.Then,the data structure of neighborhood array is adopted on the basis of pre-segmentation to establish the similarity metric by weighting the spectral information of different regions combined with elevation information.Finally,the graded elevation threshold is set,and different merging threshold weights are set according to the elevation difference between different regions perform region merging.The proposed method is validated by using the low-altitude remote sensing image data with fused elevation information and the dataset provided by the international society for photogrammetry and remote sensing,and the results show that good segmentation results are achieved by introducing elevation information in the super-pixel segmentation and region merging method based on spectral information.