Road detection in SAR images using a tensor voting algorithm

Dajiang Shen; Chun Hu; Bing Yang; Jinwen Tian; Jian Liu

doi:10.1117/12.749892

15 November 2007 Road detection in SAR images using a tensor voting algorithm

Dajiang Shen, Chun Hu, Bing Yang, Jinwen Tian, Jian Liu

Proceedings Volume 6787, MIPPR 2007: Multispectral Image Processing; 678703 (2007) https://doi.org/10.1117/12.749892
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

In this paper, the problem of the detection of road networks in Synthetic Aperture Radar (SAR) images is addressed. Most of the previous methods extract the road by detecting lines and network reconstruction. Traditional algorithms such as MRFs, GA, Level Set, used in the progress of reconstruction are iterative. The tensor voting methodology we proposed is non-iterative, and non-sensitive to initialization. Furthermore, the only free parameter is the size of the neighborhood, related to the scale. The algorithm we present is verified to be effective when it's applied to the road extraction using the real Radarsat Image.

Citation Download Citation

Dajiang Shen, Chun Hu, Bing Yang, Jinwen Tian, and Jian Liu "Road detection in SAR images using a tensor voting algorithm", Proc. SPIE 6787, MIPPR 2007: Multispectral Image Processing, 678703 (15 November 2007); https://doi.org/10.1117/12.749892

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