DocumentCode :
1549581
Title :
Semi-Automated Road Detection From High Resolution Satellite Images by Directional Morphological Enhancement and Segmentation Techniques
Author :
Chaudhuri, D. ; Kushwaha, N.K. ; Samal, A.
Author_Institution :
DEAL, IAC, Dehradun, India
Volume :
5
Issue :
5
fYear :
2012
Firstpage :
1538
Lastpage :
1544
Abstract :
Extraction of map objects such roads, rivers and buildings from high resolution satellite imagery is an important task in many civilian and military applications. We present a semi-automatic approach for road detection that achieves high accuracy and efficiency. This method exploits the properties of road segments to develop customized operators to accurately derive the road segments. The customized operators include directional morphological enhancement, directional segmentation and thinning. We have systematically evaluated the algorithm on a variety of images from IKONOS, QuickBird, CARTOSAT-2A satellites and carefully compared it with the techniques presented in literature. The results demonstrate that the algorithm proposed is both accurate and efficient.
Keywords :
geophysical image processing; geophysical techniques; image enhancement; image resolution; image segmentation; object detection; remote sensing; CARTOSAT-2A satellite; IKONOS satellite; QuickBird satellite; civilian applications; customized operators; directional morphological enhancement techniques; directional segmentation techniques; high resolution satellite images; map object extraction; military applications; remote sensing; rivers; roads; semiautomated road detection; semiautomatic approach; Image resolution; Image segmentation; Joining processes; Noise; Roads; Satellites; Software algorithms; Enhancement; morphology; remote sensing; resolution; road detection; segmentation;
fLanguage :
English
Journal_Title :
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of
Publisher :
ieee
ISSN :
1939-1404
Type :
jour
DOI :
10.1109/JSTARS.2012.2199085
Filename :
6227311
Link To Document :
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