利用边缘密度特征提取高分辨率遥感影像中的居民区

居民区相对于其他区域具有更明显更丰富的边缘特征. 根据这一特点，提出一种利用边缘密度特征差异
进行高分辨率遥感影像居民区自动提取的方法. 该方法首先利用Mean Shift 算法平滑原始影像，然后检测平滑影
像上的边缘并拟合成直线段，最后利用影像中的边缘密度分布构建空间投票矩阵，并结合Ostu 阈值分割方法提取
居民区. 实验表明：该方法可用于提取场景比较复杂的影像中的居民区，且具有较高的准确率和鲁棒性.

Extraction of Built-Up Areas Extraction from High-Resolution Remote-Sensing Images Using Edge Density Features

Built-up area contains obvious edge features. We propose a method to extract edge-based built-up
area from high resolution remote sensing images. The algorithm includes three steps: smoothing the original
image with a mean shift algorithm, extracting edges with the Canny operator and fitting them as several
straight lines, and forming a spatial voting matrix based on the edge distribution and extracting the built-up
area using the Ostu’s method. Experimental results show that the proposed approach can detect built-up areas
in images with complicated background. It is highly robust and accurate.