基于局部方向编码的遥感影像平行边缘识别

针对高分辨率遥感图像中道路、建筑物和水域等的特征识别难题,提出了一种基于边缘局部方向信息的平行边缘自动识别算法。该算法首先定义平行边缘由一系列相互平行的短直线组成;然后提出了交叉点共线约束的8-邻域边界追踪和9-像素滑动窗口内直线检测算法,实现了边缘连续线条局部方向信息编码;最后通过分析连续线条结构及方向编码规律,提出了主元分析及方向一致性判别准则进行平行特征识别。实验结果表明,该算法能够有效提取高分辨率遥感图像中具有最近邻关系的平行直线和曲线特征,平均识别准确率在95%以上,但算法执行速度有待提高。

Parallel Edges Detection from Remote Sensing Image Using Local Orientation Coding

In order to solve the difficulty for extraction of roads, buildings and rivers from high-resolution remote sensing images, a new parallel feature detection algorithm based on edge directional information is proposed in this paper. Firstly, parallel edges model is defined as boundaries made up of parallel short lines. Then, the methods of 8-neighborhood boundary-tracking based on collinear restriction in junction points and line detection algorithm in 9-pixels sliding window are proposed to obtain the local directional codes of edge chains. Finally, two efficient criterions are presented to extract the parallel features based on the principal component analysis and the consistency of edge coding. Experimental results show that the proposed algorithm is effective for extracting the nearest parallel lines and curves from high-resolution remote sensing images, and the average accuraty is more than 95%, but the running speed needs further improvement.