By Topic

Road Extraction From SAR Imagery Based on Multiscale Geometric Analysis of Detector Responses

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Chu He ; Signal Processing Laboratory, School of Electronic Information, Wuhan University, Wuhan, China ; Zi-xian Liao ; Fang Yang ; Xin-ping Deng
more authors

In this paper, a road network grouping algorithm for Synthetic Aperture Radar (SAR) images is proposed by exploiting multiscale geometric analysis of detector responses. Before running the algorithm, a response map made up of responses, which is binarized, skeletonized, and vectorized to generate road candidates, is obtained by applying a local detector to a SAR image first. Then the proposed method identifies real road segments among the candidates and fills gaps between them. It works in three steps. 1) Guidance segments are extracted at different resolutions from the response map using multiscale techniques and merged to get a more appropriate approximation. 2) Segments are labeled “road” or “noise” using relaxation labeling techniques, among which “road” ones are grouped as they may lie on different roads. 3) Connection points between candidates are acquired by mapping candidates to grouped “road” guidance segments. Those connection points are linked with straight lines or curvilinear segments after a segmentation process. The experiments on TerraSAR images show the effectiveness of this new method.

Published in:

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  (Volume:5 ,  Issue: 5 )