Road extraction by point-wise Gaussian models

Fatih M. Porikli

doi:10.1117/12.487461

23 September 2003 Road extraction by point-wise Gaussian models

Fatih M. Porikli

Proceedings Volume 5093, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery IX; (2003) https://doi.org/10.1117/12.487461
Event: AeroSense 2003, 2003, Orlando, Florida, United States

Abstract

We present a Gaussain model based approach for robust and automatic extraction of roads from very low-resolution satellite imagery. First, the input image is filtered to suppress the regions that the likelihood of existing a road pixel is low. Then, the road magnitude and orientation are computed by evaluating the responses from a quadruple orthogonal line filter set. A mapping from the line domain to the vector domain is used to determine the line strength and orientation for each point. A Gaussian model is fitted to point and matching models are updated recursively. The iterative process consists of finding the connected road points, fusing them with the previous image, passing them through the directional line filter set and computing new magnitudes and orientations. The road segments are updated at each iteration, and the process continues until there are no further changes in the roads extracted. Experimental results demonstrate the success of the proposed algorithm.

Citation Download Citation

Fatih M. Porikli "Road extraction by point-wise Gaussian models", Proc. SPIE 5093, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery IX, (23 September 2003); https://doi.org/10.1117/12.487461

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