融合多时相高分影像的建筑物轮廓优化方法

Building contour optimization method based on multitemporal high-resolution images

针对高分影像建筑物提取存在错分和漏分等问题,常见的单幅影像矩形轮廓优化由于投影差、树木和阴影遮挡等问题边缘准确度不够,本文提出了一种融合多时相建筑物轮廓优化方法。首先,将两期高分影像进行匹配等预处理,利用基于偏移阴影分类验证提取建筑物初始结果。然后,分别获得两期影像中各建筑物轮廓的最小面积外接矩形,并对同名建筑物的最小面积外接矩形的各对应角点进行匹配。最后,通过对比两期影像的对应最小面积外接矩形的对应边上建筑物像素点的数量,选择像素点数量多的边作为适宜边进行平移以获得最优边,四条边都是最优边后进行直线正交得到最终符合建筑物原始形态的轮廓。试验结果表明,本文方法相比传统方法和其他轮廓优化方法在精确度和完整度上均有提高。

In view of the problems of misclassification and omission in building extraction from high-resolution images,the common rectangular contour optimization of single image is not accurate enough due to poor projection,trees and shadow shading,Therefore,an optimization method of multi-temporal building contour is proposed.Firstly,the two high-resolution images are preprocessed by matching,and the initial results of buildings are extracted by shadow classification verification.Then,the minimum area circumscribed rectangles of each building contour in the two images are obtained,and the corresponding corners of the minimum area circumscribed rectangles of the same building are matched.Finally,by comparing the number of building pixels on the corresponding edge of the corresponding minimum area circumscribed rectangle of the two phases of image,the edge with more pixels is selected as the appropriate edge for translation to obtain the optimal edge.After the four edges are the optimal edges,the final contour that conforms to the original shape of the building is obtained by orthogonal lines.Experimental results show that the proposed method improves the accuracy and completeness compared with the traditional results and other contour optimization methods.