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This paper proposes an unsupervised method to obtain road maps from highly resolved (better than 1m) panchromatic images. As a starting point it is assumed that an incomplete skeletal representation of the road map, i.e. the basic road network, is available. For example this can easily be gained through a straightforward thresholding. In the first step of the road map creation the network is completed using a maximum likelihood extrapolation approach. In a series of evaluations it was shown that this increases the network completeness, on average, by slightly over a tenth of the actual road network. In the second step the network is converted to the road map, i.e. the representation of areas that are part of the actual roads. Again, a maximum likelihood approach was applied with its parameters described through the local neighbourhood. In total completeness and correctness of more than 90% and 95%, respectively, were achieved.

1.1 Road detection in panchromatic SPOT satellite images 2.1.2 Efficient algorithm for detection of road-like structures in satellite images 2.1.3 Robust detection of road segments in noisy aerial images 2.1.4 Vehicle detection on aerial images: a structural approach 2.1.5 Automatic finding of main roads in aerial images by using geometric-stochastic models and estimation 2.1.6 An image analysis system, application for aerial imagery interpretation 2.1.7 Automatic road extraction using fuzzy mask concepts 16 2.1.8 Automated detection of road intersections from ERS-1 SAR imagery 2.1.9 Road detection in spaceborne SAR images using a genetic algorithm 2.1.10 Application of spatial reasoning methods to the extraction of roads from high resolution satellite imagery. 2.1.11 The line segment match method for extracting road network from high-resolution satellite images 2.1.12 A wavelet transform based method for road extraction from high-resolution remotely sensed data 2.1.13 Road network extraction from airborne digital camera images: a multi-resolution comparison 2.1.14 The research of road extraction for high resolution satellite image 2.1.15 Towards knowledge-based extraction of roads from 1m resolution satellite images 2.1.16 Detection and extraction of road networks from high resolution satellite images 2.2 OVERVIEW AND CONCLUSIONS 2.2.1 Overview 2.2.