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首页> 外文会议>International symposium on multispectral image processing and pattern recognition >Automated Railroad Reconstruction from Remote Sensing Image based on Texture Filter
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Automated Railroad Reconstruction from Remote Sensing Image based on Texture Filter

机译：基于纹理过滤器的遥感影像自动铁路重建

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摘要

Techniques of remote sensing have been improved incredibly in recent years and very accurate results and high resolution images can be acquired. There exist possible ways to use such data to reconstruct railroads. In this paper, an automated railroad reconstruction method from remote sensing images based on Gabor filter was proposed. The method is divided in three steps. Firstly, the edge-oriented railroad characteristics (such as line features) in a remote sensing image are detected using Gabor filter. Secondly, two response images with the filtering orientations perpendicular to each other are fused to suppress the noise and acquire a long stripe smooth region of railroads. Thirdly, a set of smooth regions can be extracted by firstly computing global threshold for the previous result image using Otsu's method and then converting it to a binary image based on the previous threshold. This workflow is tested on a set of remote sensing images and was found to deliver very accurate results in a quickly and highly automated manner.
机译：近年来，遥感技术得到了令人难以置信的改进，并且可以获得非常准确的结果和高分辨率图像。存在使用此类数据重建铁路的可能方法。提出了一种基于Gabor滤波器的遥感影像自动铁路重建方法。该方法分为三个步骤。首先，使用Gabor滤波器检测遥感图像中的边缘铁路特征（例如线特征）。其次，将两个相互垂直的滤波方向的响应图像融合在一起，以抑制噪声并获得铁路的长条平滑区域。第三，可以通过首先使用Otsu方法计算先前结果图像的全局阈值，然后基于先前阈值将其转换为二进制图像，来提取一组平滑区域。该工作流在一组遥感图像上进行了测试，并被发现以快速，高度自动化的方式提供非常准确的结果。

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