High-precision lane-level map elements extracting based on high-resolution remote sensing image

doi:10.13474/j.cnki.11-2246.2021.0075

Abstract

Abstract: High-precision map is automatically under the city road scene driving one of the necessary infrastructures. Aiming at the problems of the high acquisition cost, long period, and complicated data processing in the production and update of the static layer of high-precision map, the lane-level element extraction scheme of high-precision map static layer based on high-resolution remote sensing image is proposed. Firstly, multi-temporal images are registered by the SURF algorithm, and pixels are judged by combining the spectral information of the image, thus realizing the detection and removal of dynamic vehicles in the lane.Secondly, based on the object-oriented method, a feature selection method of element objects is proposed, and the threshold analysis of each element is carried out in combination with the statistical theory to realize the detection and extraction of lane-level elements such as the dashed lane line crosswalk.Finally, combined with experimental data, the effectiveness of the proposed lane-level elements extraction scheme based on remote sensing image is verified.

Key words: high-precision map, remote sensing images, target detection and removal, object-oriented, object features selection

CLC Number:

P237

HOU Qiaochu, LI Bijun, CAI Yi. High-precision lane-level map elements extracting based on high-resolution remote sensing image[J]. Bulletin of Surveying and Mapping, 2021, 0(3): 38-43.

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