摘要:
从遥感图像中提取道路边缘可以大量简化道路网的测绘与规划工作。传统边缘检测算子由于方向和模板尺寸的局限性,易造成检测结果中边缘点散乱、不连续或过多边缘点误判。基于道路边缘完整且连续的特点,针对传统检测效果并不理想的问题,提出了一种改进的Sobel算子,即5×5的8方向模板。从Sobel 算子的基本原理出发,根据Pascal三角形理论推导出各方向的最优模板。研究表明,该算子不仅能较好地检测出更多方向上的边缘,而且能有效减少误判点,检测出的边缘线条更加平滑、完整,轮廓清晰且连续性好,尤其在弯曲道路检测中表现得更为突出,优于其他算子的检测效果。
Abstract:
Extracting road edge from remote sensing image can extremely simplify the land survey workload for planning traffic networks .Because of the direction and size limitations of the template , the edge detection result derived by traditional algorithms shows high rate of false positive points and discontinuity , which is the reason why traditional edge detection algorithms can seldom achieve an ideal result in detecting continuous and integral road edge.To deal with this problem , this study proposes an improved Sobel operator which is based on an 8 directional 5 ×5 template .The optimal settings of each direction in the template are derived by the Pascal ’ s triangle theory . The improved operator not only achieves a better performance of edge detection in different directions but reduces the false positive point effectively as well .In comparison with other operators , the improved Sobel operator proposed by this study has better integrity and continuity in road edge extraction results , especially in road curve detection .
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