JOURNAL ARTICLE

Road Network Extraction in High Resolution SAR Images

Wang Chao Chen Wei-rong

Year: 2011 Journal:   Yaogan jishu yu yingyong Vol: 20 (1)Pages: 137-140   Publisher: Chinese Academy of Sciences

Abstract

The application of high-resolution synthetic aperture radar (SAR) images from aerial and satellite sensors challenges the researchers for new and effective interpretation tools. Although most of the main axes in the road network may be detected by a skilled human observer looking for dark or bright linear structures, automatic detection remains a difficult task. In this paper, we proposed a new simple approach to extract main road network in high-resolution SAR images automatically. The approach is based on three steps. The first step is pre-filtering the initial SAR images by using a two-way thresholding process in order to discard uninteresting parts of image. In the second step, the results of the first step are input and use the Hough Transform to identify the roads respectively. The last step is based on a feature fusion technique. The road networks detected are combined with the fusion operators. We show the improved results from some examples. It is proved that this approach is effective for the straight highways in high-resolution images.

Keywords:
Thresholding Artificial intelligence Computer science Synthetic aperture radar Computer vision Hough transform High resolution Image fusion Remote sensing Pattern recognition (psychology) Image (mathematics) Geography

Metrics

3
Cited By
0.00
FWCI (Field Weighted Citation Impact)
0
Refs
0.55
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Topics

Automated Road and Building Extraction
Physical Sciences →  Engineering →  Ocean Engineering
Remote Sensing and LiDAR Applications
Physical Sciences →  Environmental Science →  Environmental Engineering
Image and Object Detection Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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