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Straight line detection from remote sensing images by rule-based feature fusion

机译:基于规则的特征融合从遥感影像中进行直线检测

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Straight line detection is a fundamental problem in target recognition from remote sensing images since many man-made objects have straight boundaries. In this study, an integrated straight line detection method for remote sensing images is proposed. In this method, the edge-based straight lines are extracted using a chain code tracing method and the phase-based straight lines are extracted using a phase grouping method. The two types of lines are combined using a rule-based feature fusion method by removing redundant line extraction. Since this method integrates the specialties of edge- and phase-based straight line detection methods, it can detect straight lines from remote sensing images with high correctness and robustness.
机译:直线检测是遥感图像目标识别中的一个基本问题,因为许多人造物体都具有直线边界。在这项研究中,提出了一种综合的遥感图像直线检测方法。在这种方法中,使用链码跟踪方法提取基于边缘的直线,并使用相位分组方法提取基于相位的直线。通过删除多余的行提取,使用基于规则的特征融合方法将这两种类型的行组合在一起。由于该方法融合了基于边缘和相位的直线检测方法的特长,因此可以从遥感图像中检测直线,具有较高的正确性和鲁棒性。

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