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Joint Enhancing Filtering for Road Network Extraction
IEEE Transactions on Geoscience and Remote Sensing, 2017In this paper, we propose a task-oriented enhancing technique for extracting road networks from satellite images. By exploiting an approximate estimation of the potential road edges for guidance, we developed a joint enhancing filtering framework to generate a version of the input image that facilitates road network extraction.
Yu Zang +5 more
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Feature Fusion for Road Extraction in SAR Scenes
2006 IEEE International Symposium on Geoscience and Remote Sensing, 2006In this paper we propose a novel procedure for urban road network extraction in high resolution SAR images. It is based on a multi-scale detection step including fusion of multiple features aimed at considering spatial high resolution as well as the spectral characteristics of the SAR images.
Matteo Negri, Paolo Gamba
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2005
Abstract : Our research is focused on an investigation of automated road tracking using multiple images, toward a goal of fully automated extraction of 3D road networks with topology and attribution. The use of multiple images for road tracking makes the process more robust, due to analysis of the scene from different view points.
David M. McKeown +2 more
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Abstract : Our research is focused on an investigation of automated road tracking using multiple images, toward a goal of fully automated extraction of 3D road networks with topology and attribution. The use of multiple images for road tracking makes the process more robust, due to analysis of the scene from different view points.
David M. McKeown +2 more
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Road markings extraction based on threshold segmentation
2012 9th International Conference on Fuzzy Systems and Knowledge Discovery, 2012A method for road markings extraction on urban streets acquired by a camera mounted on a moving vehicle is described. This method works in three stages. First, the search for the road markings is reduced to a suitable bird's eye view of road surface by using inverse perspective mapping.
Zhao Li +3 more
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The Role of Grouping for Road Extraction
1997An approach to complete road networks extracted from aerial images is presented. Since low-level road extraction results will generally be fragmented and contain false hypotheses, this task involves selecting the correct roads from the extraction results as well as connecting them to construct the road network.
Carsten Steger +2 more
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Extraction of road region using stereo images
Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170), 2002Extracting the road region in an observed image is an important technique for visual navigation of an autonomous vehicle. In this paper, we propose a road extraction method using stereo images. The method does not rely on the existence of any specific road painting or texture. Instead, it supposes that a road (or a passable part) can be approximated by
Masatoshi Okutomi, Suguru Noguchi
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Road Extraction for Emergencies from Satellite Imagery
2020After earthquakes, international and national organizations must overcome many challenges in rescue operations. Among these, the knowledge of the territory and of the roads is fundamental for international aid. The maps that volunteers make are a valuable asset, showing the roads in the area affected by the seismic events, a knowledge which is ...
Vincenzo Barrile +3 more
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2007 International Symposium on Information Technology Convergence (ISITC 2007), 2007
Yun-Woong Choi +3 more
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Yun-Woong Choi +3 more
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Multi-scale and snakes for automatic road extraction
1998This paper proposes an approach for automatic road extraction in aerial imagery which exploits the scale-space behavior of roads in combination with geometric constrained snake-based edge extraction. The approach not only has few parameters to be adjusted, but for the first time allows for a bridging of shadows and partially occluded areas using the ...
Helmut Mayer 0001 +2 more
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A Global Context-aware and Batch-independent Network for road extraction from VHR satellite imagery
ISPRS Journal of Photogrammetry and Remote Sensing, 2021Qiqi Zhu, Yanan Zhang, Yanfei Zhong
exaly