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Spatial Attention Network for Road Extraction
IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, 2020Road extraction from high-resolution remote sensing images has become an important method to achieve real-time updating of road network to meet the application requirements. However, due to the diversity of road scenes, various road width, and occlusion, the detected roads in recent researches are often discontinuous and these narrow or fragmented road
Ruonan Chen, Yuan Hu, Tong Wu, Ling Peng
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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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Context-Supported Road Extraction
1997Contextual information can facilitate automatic extraction of objects from digital imager). This paper addresses the use of context for the automatic extraction of roads from aerial imagery. Context is restricted to knowledge about relations between roads and other objects and is hierarchically structured.
A. Baumgartner +4 more
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Spatial information inference net: Road extraction using road-specific contextual information
ISPRS Journal of Photogrammetry and Remote Sensing, 2019Abstract Deep neural networks perform well in road extraction from very high-resolution satellite imagery. A network with certain reasoning ability will give more satisfactory road network extraction results. In this study, we designed a spatial information inference structure, which enables multidirectional message passing between pixels when it is ...
Chao Tao +4 more
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Road Structure Refined CNN for Road Extraction in Aerial Image
IEEE Geoscience and Remote Sensing Letters, 2017In this letter, we propose a road structure refined convolutional neural network (RSRCNN) approach for road extraction in aerial images. In order to obtain structured output of road extraction, both deconvolutional and fusion layers are designed in the architecture of RSRCNN.
Yanan Wei, Zulin Wang, Mai Xu
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Road and Road Intersection Extraction
2013Beginning in 1879 the United States Geological Survey (USGS) began surveying land in the United States. Since then they have developed over 55, 000 1: 24, 000-scale topographic maps covering the 48 coterminous states in a standard, detailed manner. The result is a wealth of data contained in physical documents.
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Road Network Extraction in Suburban Areas
The Photogrammetric Record, 2012AbstractIn this paper, an algorithm for the extraction of road networks in suburban areas is presented. The algorithm is region‐based and uses high‐resolution colour infrared images as well as, optionally, a digital surface model (DSM). The road extraction starts with a segmentation using the normalised cuts algorithm; afterwards the segments are ...
Anne Grote +2 more
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Road extraction using smart phones GPS
Proceedings of the 2nd International Conference on Computing for Geospatial Research & Applications - COM.Geo '11, 2011GPS data crowd-sourced through smart phones is an emerging source of inexpensive data that can be used to provide real-time traffic information, identify traffic patterns, and predict traffic congestions. The same type of data can be very useful for cost-effective, fast updating of road network databases due to its rich spatial and temporal coverage ...
Zheng Niu, Songnian Li, Neda Pousaeid
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Extracting linear road from TM image
Fifth World Congress on Intelligent Control and Automation (IEEE Cat. No.04EX788), 2004To study the automatic extracting system of linear road in TM images. Firstly, the features of TM images were analyzed, an image segmentation algorithm based on multi-spectra was presented. Secondly, some texture features of road area in TM image were analyzed, rapidly fuzzy classification approach was adopted, a dilation algorithm and realizes ...
null Binghan Liu +2 more
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An Optimal Road Seed Extraction Algorithm
2008 International Workshop on Education Technology and Training & 2008 International Workshop on Geoscience and Remote Sensing, 2008The proper extraction of road seeds is the premier step of road network extraction from high resolution remote sensing images. An optimal road seed extraction algorithm is proposed. Firstly, Canny-Deriche edge detection and spatial FCM (fuzzy c means) region extraction are performed separately to detect the details.Secondly, an averaged Hausdorff ...
Yang Hu +3 more
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