Results 161 to 170 of about 7,057 (212)
Road Centerline Extraction in Complex Urban Scenes From LiDAR Data Based on Multiple Features
IEEE Transactions on Geoscience and Remote Sensing, 2014 Automatic extraction of roads from images of complex urban areas is a very difficult task due to the occlusions and shadows of contextual objects, and complicated road structures. As light detection and ranging (LiDAR) data explicitly contain direct 3-D information of the urban scene and are less affected by occlusions and shadows, they are a good data
null Xiangyun Hu +4 more
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Road network extraction by a higher-order CRF model built on centerline cliques
2015 23rd European Signal Processing Conference (EUSIPCO), 2015 The goal of this work is to recover road networks from aerial images. This problem is extremely challenging because roads not only exhibit a highly varying appearance but also are usually occluded by nearby objects. Most importantly, roads are complex structures as they form connected networks of segments with slowly changing width and curvature. As an
O. Besbes, A. Benazza-Benyahia
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ISPRS Journal of Photogrammetry and Remote Sensing, 2016 Abstract Road information acquisition is an important part of city informatization construction. Airborne LiDAR provides a new means of acquiring road information. However, the existing road extraction methods using LiDAR point clouds always decide the road intensity threshold based on experience, which cannot obtain the optimal threshold to extract ...
Zhenyang Hui +3 more
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IEEE Geoscience and Remote Sensing Letters, 2013 Road centerline extraction from remotely sensed imagery can be used to update a Geographic Information System (GIS) database. The common road extraction from high-resolution imagery is based on spectral information only; it is difficult to separate road features from background completely, and a thinning algorithm always results in short spurs which ...
Zelang Miao +3 more
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18th International Conference on Pattern Recognition (ICPR'06), 2006 Using a local Radon transform helps improve the performance of the Radon transform-based linear feature detection. In this paper, three different approaches to localize the Radon transform are implemented and compared in the context of road centerline extraction from classified satellite imagery.
null Qiaoping Zhang, I. Couloigner
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Road Centerline Extraction via Semisupervised Segmentation and Multidirection Nonmaximum Suppression
IEEE Geoscience and Remote Sensing Letters, 2016Accurate road centerline extraction from remotely sensed images plays a significant role in road map generation and updating. In the road extraction problem, the acquisition of labeled data is time consuming and costly; thus, there are only a small amount of labeled samples in reality.
Guangliang Cheng +3 more
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Road Centerline Extraction From VHR Images Using SVM and Multi-Scale Maximum Response Filter
Journal of the Indian Society of Remote Sensing, 2021In this work, an integrated framework comprising of pixel-based classification, road network filtering, and multi-scale Gabor filter is proposed to address the various prevailing issues in road centerline extraction from VHR images. The proposed framework is composed of three steps; generation of the initial road map, road network filtering and road ...
Pramod Kumar Soni +2 more
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A Semi-Supervised High-Level Feature Selection Framework for Road Centerline Extraction
IEEE Geoscience and Remote Sensing Letters, 2020Accurate road centerline extraction is very important for many vital applications. In the road extraction, the acquisition of labeled data is time-consuming; thus, there is only a small amount of labeled samples in reality. To solve the problem of limited labeled samples, a semi-supervised road centerline extraction is proposed, which incorporates high-
Ruyi Liu +4 more
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A Semi-Automatic Method for Road Centerline Extraction From VHR Images
IEEE Geoscience and Remote Sensing Letters, 2014This letter presents a semi-automatic approach to delineating road networks from very high resolution satellite images. The proposed method consists of three main steps. First, the geodesic method is used to extract the initial road segments that link the road seed points prescribed in advance by users. Next, a road probability map is produced based on
Zelang Miao +3 more
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Research on road centerline extraction from aerial image based on Sorting
2009 17th International Conference on Geoinformatics, 2009According to the road extraction from moderate and low resolution aerial image, this paper presents a fast method which is based on Sorting. In the initial stage of the method, an algorithm for detecting ridge or ribbon like linear features based on sorting and simple judgment scheme is adopted; after thinning the centerline, using the initial image ...
null BingXuan Guo +2 more
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