Abstract
In this study, the effect of threshold values used for road segments detection in synthetic aperture radar (SAR) images of road network generation is examined. A three-phase method is applied as follows: image smoothing, road segments detection and irrelevant segments removal. Threshold values used in road segment detection phase are evaluated for four different situations and results are compared. The software is developed to apply and test all situations. Two different synthetic aperture radar images are used in experimental studies.
Highlights
Since the developments in space technology increase rapidly, more advanced satellites are built
The effect of threshold values used for road segments detection in synthetic aperture radar (SAR) images on road network generation is examined
We developed the software to evaluate four different situations of thresholds values
Summary
Since the developments in space technology increase rapidly, more advanced satellites are built. Tupin et al [2] present a study which detects linear features like roads They use two different line detectors and Markov random field based connection method. A new method for a feature based supervised classification is presented by Borghys et al [7] They classify SAR images as road, water, forest etc. Cheng et al [14] present a main road extraction method based on Markov Random Field They accelerate their method by utilising GPU and apply their method to polarimetric SAR images. Jin et al [15] develop a constant false alarm line detector for polarimetric SAR images They use Wilks’ test statistic which can detect bright and dark features.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Advanced Computer Science and Applications
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
