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In this paper, a novel technique to generate a high resolution and high precision Orthorectified Road Imagery (ORI) by using spatial\udinformation acquired from a Mobile Mapping System (MMS) is introduced. The MMS was equipped with multiple sensors such as\udGPS, IMU, odometer, 2-6 digital cameras and 2-4 laser scanners. In this study, a Triangulated Irregular Network (TIN) based\udapproach, similar to general aerial photogrammetry, was adopted to build a terrain model in order to generate ORI with high\udresolution and high geometric precision. Compared to aerial photogrammetry, there are several issues that are needed to be addressed.\udORI is generated by merging multiple time sequence images of a short section. Hence, the influence of occlusion due to stationary\udobjects, such as telephone poles, trees, footbridges, or moving objects, such as vehicles, pedestrians are very significant. Moreover,\udinfluences of light falloff at the edges of cameras, tone adjustment among images captured from different cameras or a round trip\uddata acquisition of the same path, and time lag between image exposure and laser point acquisition also need to be addressed\udproperly. The proposed method was applied to generate ORI with 1 cm resolution, from the actual MMS data sets. The ORI\udgenerated by the proposed technique was more clear, occlusion free and with higher resolution compared to the conventional\udorthorectified coloured point cloud imagery. Moreover, the visual interpretation of road features from the ORI was much easier. In\udaddition, the experimental results also validated the effectiveness of proposed radiometric corrections. In occluded regions, the ORI\udwas compensated by using other images captured from different angles. The validity of the image masking process, in the occluded\udregions, was also ascertained

the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences

GENERATION OF HIGH RESOLUTION AND HIGH PRECISION ORTHORECTIFIED ROAD IMAGERY FROM MOBILE MAPPING SYSTEM