The Global Road Extraction Approach from Synthetic Aperture Radar Images

Author

Xin, Yang ; Shunji, Huang

Author_Institution

Sch. of Electron. Eng., UESTC, Chengdu

fYear

2009

fDate

28-29 April 2009

Firstpage

1

Lastpage

3

Abstract

The extraction of road networks from synthetic aperture radar imagery is of fundamental importance for geospatial applications. The methods basically go through the steps such as road sharpening, road finding, road tracking and road linking. In this paper, a new global approach to road detection that is motivated by Kohonen neural network is proposed. It makes the joint of the roads more fluent and reduces detection errors. The computer simulation results show the highest extraction quality from the real SAR images.

Keywords

feature extraction; geophysical signal processing; geophysics computing; neural nets; radar imaging; remote sensing by radar; roads; synthetic aperture radar; Kohonen neural network; geospatial applications; global road extraction approach; road detection; road finding; road linking; road sharpening; road tracking; synthetic aperture radar images; Data mining; Humans; Image edge detection; Neural networks; Radar tracking; Remote monitoring; Roads; Spatial resolution; Synthetic aperture radar; Topology;

fLanguage

English

Publisher

ieee

Conference_Titel

Testing and Diagnosis, 2009. ICTD 2009. IEEE Circuits and Systems International Conference on

Conference_Location

Chengdu

Print_ISBN

978-1-4244-2587-7

Type

conf

DOI

10.1109/CAS-ICTD.2009.4960891

Filename

4960891