GSM法－從空載光達點雲萃取道路交通標線交點

GSM Method for Extraction of Intersection Points of Road Marking Lines from Airborne LiDAR Point Clouds

李宏君(Hong-Chun Li) ； 蔡展榮(Jaan-Rong Tsay)

《航測及遙測學刊》 20卷2期 (2016/04) Pp. 75-92

https://doi.org/10.6574/JPRS.2016.20(2).1

摘要

本文根據瀝青路面及道路交通標線之光達回波強度的差異性，設計高斯曲面匹配(Gaussian SurfaceMatching, GSM)法，以求定直線型交通標線之線特徵參數，進而求得垂直交會的兩條直線標線之交點，並由不同航帶的光達點雲同名交點來估計與改正相鄰航帶點雲坐標基準偏差量，俾使用標線交點群來求解空照影像的外方位元素，使兩者建立在共同的坐標系統之中，以利後續空載光達與航空攝影測量的整合應用。經由實際資料測試，光達航帶點雲坐標基準經改正後，同名交點之整體平面偏差量之均方根值從0.650m降至0.286m，符合光達點之先驗平面精度±0.25m。使用這些基準改正後的點位做為地控點(共30點)，施行空照影像光束法平差，整體空三精度達到±0.67個像元的次像元精度等級。

關鍵字

高斯曲面匹配法 ； 空載光達 ； 空照數位影像 ； 反射強度

並列摘要

Real airborne LiDAR data show that the laser intensity on asphalt surface is significantly lower than the one on road marking lines. A Gaussian Surface Matching (GSM) approach is thus developed and presented to determine the parameters of road marking lines and the coordinates of the intersection of two road marking lines as well. Those intersections in the overlapping scanning areas of two neighboring LiDAR strips can be then applied to evaluate the related systematic bias. After systematic bias estimation and correction, the root mean square registration error is reduced from 0.650m to 0.286m in horizontal direction. These intersections are then used as ground control points in aero triangulation (AT). The AT with the precision of ±0.67 pixel is generated.

並列關鍵字

gaussian surface matching ； airborne LiDAR ； aerial digital image ； reflectance