一种改进的遥感影像道路中心线搜索方法

Duan Juan, Liu Runsheng, Jin Fei
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引用次数: 0

摘要

针对基于方向纹理的道路中心线提取算法对图像干扰的敏感性,提出了一种基于方向纹理和卡尔曼滤波的高分辨率遥感图像道路中心线提取改进方法。通过纹理定向匹配获得初始道路中心点后,结合先验信息和道路中心点观测信息,应用卡尔曼滤波迭代跟踪准确的道路中心点。设计了多个实验验证该算法的可靠性和鲁棒性,结果表明,该算法可以降低车辆、树木和阴影对高分辨率图像道路提取的覆盖影响,具有较强的鲁棒性和灵活性。平均位置偏差为1.9像素,平均位置偏差误差为1.7像素。
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A Modified Road Centerlines Search Method from Remote Sensing Images
Aiming at the sensitivity of the road centerline extraction algorithm using directional texture to the disturbance in the images, a modified method for road centerlines on highresolution remote sensing images is proposed based on the directional texture and Kalman Filter. After the initial center points of the road are obtained by directional texture matching, Kalman Filter combined with priori information and observation information of the road center points is applied to track the accurate road center points iteratively. Multiple experiments are designed to verify the reliability and robustness of the algorithm, showing that it can reduce the covering impact of vehicles, trees and shadow on road extraction in high-resolution images with relatively strong robustness and flexibility. The average position deviation is 1.9 pixels, and the average position deviation error is 1.7 pixels.
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